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Part III - Language and Cognitive Plasticity and Processing

Published online by Cambridge University Press:  12 December 2025

Edna Andrews
Affiliation:
Duke University, North Carolina
Swathi Kiran
Affiliation:
Boston University
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Publisher: Cambridge University Press
Print publication year: 2025

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References

Abel, S., Weiller, C., Huber, W., Willmes, K., & Specht, K. (2015). Therapy-induced brain reorganization patterns in aphasia. Brain, 138, 10971112.10.1093/brain/awv022CrossRefGoogle ScholarPubMed
Abo, M., Senoo, A., Watanabe, S., Miyano, S., Doseki, K., Sasaki, N., Kobayashi, K., Kikuchi, Y., & Yonemoto, K. (2004). Language-related brain function during word repetition in post-stroke aphasics. Neuroreport, 15(12), 18911894.10.1097/00001756-200408260-00011CrossRefGoogle ScholarPubMed
Albert, M. L., Sparks, R. W., & Helm, N. A. (1973). Melodic intonation therapy for aphasia. Archives of Neurology, 29(2), 130131.10.1001/archneur.1973.00490260074018CrossRefGoogle ScholarPubMed
Baliki, M. N., Babbitt, E. M., & Cherney, L. R. (2018). Brain network topology influences response to intensive comprehensive aphasia treatment. Neurorehabilitation, 43(1), 6376.10.3233/NRE-182428CrossRefGoogle ScholarPubMed
Bitan, T., Simic, T., Saverino, C., Jones, C., Glazer, J., Collela, B., Wiseman-Hakes, C., Green, R., & Rochon, E. (2018). Changes in resting-state connectivity following melody-based therapy in a patient with aphasia. Neural Plasticity, 2018, 13.10.1155/2018/6214095CrossRefGoogle Scholar
Callan, D. E., Tsytsarev, V., Hanakawa, T., Callan, A. M., Katsuhara, M., Fukuyama, H., & Turner, R. (2006). Song and speech: Brain regions involved with perception and covert production. Neuroimage, 31(3), 13271342.10.1016/j.neuroimage.2006.01.036CrossRefGoogle Scholar
Chan, M. Y., Park, D. C., Savalia, N. K., Petersen, S. E., & Wig, G. S. (2014). Decreased segregation of brain systems across the healthy adult lifespan. Proceedings of the National Academy of Sciences, 111(46), E4997E5006.10.1073/pnas.1415122111CrossRefGoogle ScholarPubMed
Chu, R., Meltzer, J. A., & Bitan, T. (2018). Interhemispheric interactions during sentence comprehension in patients with aphasia. Cortex, 109, 7491.10.1016/j.cortex.2018.08.022CrossRefGoogle ScholarPubMed
Cohen, J. R., & D’Esposito, M. (2016). The segregation and integration of distinct brain networks and their relationship to cognition. Journal of Neuroscience, 36(48), 1208312094.10.1523/JNEUROSCI.2965-15.2016CrossRefGoogle ScholarPubMed
Deco, G., Jirsa, V. K., & McIntosh, A. R. (2011). Emerging concepts for the dynamical organization of resting-state activity in the brain. Nature Reviews Neuroscience, 12(1), 4356.10.1038/nrn2961CrossRefGoogle ScholarPubMed
Duncan, E. S., & Small, S. L. (2018). Changes in dynamic resting state network connectivity following aphasia therapy. Brain Imaging and Behavior, 12(4), 11411149.10.1007/s11682-017-9771-2CrossRefGoogle ScholarPubMed
Durand, E., Masson-Trottier, M., Sontheimer, A., & Ansaldo, A. I. (2021). Increased links between language and motor areas: A proof-of-concept study on resting-state functional connectivity following personalized observation, execution and mental imagery therapy in chronic aphasia. Brain and Cognition, 148.10.1016/j.bandc.2020.105659CrossRefGoogle ScholarPubMed
Fedorenko, E., & Thompson-Schill, S. L. (2014). Reworking the language network. Trends in Cognitive Sciences, 18(3), 120126.10.1016/j.tics.2013.12.006CrossRefGoogle ScholarPubMed
Fridriksson, J. (2010). Preservation and modulation of specific left hemisphere regions is vital for treated recovery from anomia in stroke. Journal of Neuroscience, 30(35), 1155811564.10.1523/JNEUROSCI.2227-10.2010CrossRefGoogle ScholarPubMed
Fridriksson, J., Baker, J. M., & Moser, D. (2009). Cortical mapping of naming errors in aphasia. Human Brain Mapping, 30(8), 24872498.10.1002/hbm.20683CrossRefGoogle ScholarPubMed
Friston, K. J., Harrison, L., & Penny, W. (2003). Dynamic causal modelling. Neuroimage, 19(4), 12731302.10.1016/S1053-8119(03)00202-7CrossRefGoogle ScholarPubMed
Geranmayeh, F., Leech, R., & Wise, R. J. S. (2016). Network dysfunction predicts speech production after left hemisphere stroke. Neurology, 86(14), 1296.10.1212/WNL.0000000000002537CrossRefGoogle ScholarPubMed
Gili, T., Fiori, V., De Pasquale, G., Sabatini, U., Caltagirone, C., & P. Marangolo, P. (2017). Right sensory-motor functional networks subserve action observation therapy in aphasia. Brain Imaging Behav, 11(5), 13971411.10.1007/s11682-016-9635-1CrossRefGoogle ScholarPubMed
Harvey, D. Y., Wei, T., Ellmore, T. M., Hamilton, A. C., & Schnur, T. T. (2013). Neuropsychological evidence for the functional role of the uncinate fasciculus in semantic control. Neuropsychologia, 51(5), 789801.10.1016/j.neuropsychologia.2013.01.028CrossRefGoogle ScholarPubMed
Heiss, W. D., Karbe, H., WeberLuxenburger, G., Herholz, K., Kessler, J., Pietrzyk, U., & Pawlik, G. (1997). Speech-induced cerebral metabolic activation reflects recovery from aphasia. Journal of Neuroscience, 145(2), 213217.Google ScholarPubMed
Heiss, W. D., Thiel, A., Kessler, J., & Herholz, K. (2003). Disturbance and recovery of language function: Correlates in PET activation studies. Neuroimage, 20, Supplement 1, S42S49.10.1016/j.neuroimage.2003.09.005CrossRefGoogle ScholarPubMed
Hope, T. M. H., Leff, A. P., & Price, C. J. (2018). Predicting language outcomes after stroke: Is structural disconnection a useful predictor? Neuroimage-Clinical, 19, 2229.10.1016/j.nicl.2018.03.037CrossRefGoogle ScholarPubMed
Johnson, J. P., Meier, E. L., Pan, Y., & Kiran, S. (2020). Pre-treatment graph measures of a functional semantic network are associated with naming therapy outcomes in chronic aphasia. Brain and Language, 207.10.1016/j.bandl.2020.104809CrossRefGoogle ScholarPubMed
Johnson, J. P., Meier, E. L., Pan, Y., & Kiran, S. (2021). Abnormally weak functional connections get stronger in chronic stroke patients who benefit from naming therapy. Brain and Language, 223.10.1016/j.bandl.2021.105042CrossRefGoogle ScholarPubMed
Keator, L. M., Yourganov, G., Basilakos, A., Hillis, A. E., Hickok, G., Bonilha, L., Rorden, C., & Fridriksson, J. (2021). Independent contributions of structural and functional connectivity: Evidence from a stroke model. Network Neuroscience, 5(4), 911928.10.1162/netn_a_00207CrossRefGoogle ScholarPubMed
Klingbeil, J., Wawrzyniak, M., Stockert, A., & Saur, D. (2019). Resting-state functional connectivity: An emerging method for the study of language networks in post-stroke aphasia. Brain and Cognition, 131, 2233.10.1016/j.bandc.2017.08.005CrossRefGoogle Scholar
Marcotte, K., Perlbarg, V., Marrelec, G., Benali, H., & Ansaldo, A. I. (2013). Default-mode network functional connectivity in aphasia: Therapy-induced neuroplasticity. Brain and Language, 124(1), 4555.10.1016/j.bandl.2012.11.004CrossRefGoogle ScholarPubMed
Masson-Trottier, M., Sontheimer, A., Durand, E., & Ansaldo, A. I. (2021). Resting-state functional connectivity following phonological component analysis: The combined action of phonology and visual orthographic cues.” Brain sciences, 11(11), 1458.10.3390/brainsci11111458CrossRefGoogle ScholarPubMed
Meier, E. L., Johnson, J. P., & Kiran, S. (2018). Left frontotemporal effective connectivity during semantic feature judgments in patients with chronic aphasia and age-matched healthy controls. Cortex, 108, 173192.10.1016/j.cortex.2018.08.006CrossRefGoogle ScholarPubMed
Meier, E. L., Johnson, J. P, Pan, Y. & Kiran, S. (2019). “A lesion and connectivity-based hierarchical model of chronic aphasia recovery dissociates patients and healthy controls.” Neuroimage-Clinical, 23.10.1016/j.nicl.2019.101919CrossRefGoogle ScholarPubMed
Meltzer, J. A., Wagage, S., Ryder, J., Solomon, B., & Braun, A. R. (2013). Adaptive significance of right hemisphere activation in aphasic language comprehension. Neuropsychologia, 51(7), 12481259.10.1016/j.neuropsychologia.2013.03.007CrossRefGoogle ScholarPubMed
Naeser, M. A., Martin, P. I., Baker, E. H., Hodge, S. M., Sczerzenie, S. E., Nicholas, M., Palumbo, C. L., Goodglass, H., Wingfield, A., Samaraweera, R., Harris, G., Baird, A., Renshaw, P., & Yurgelun-Todd, D. (2004). Overt propositional speech in chronic nonfluent aphasia studied with the dynamic susceptibility contrast fMRI method. Neuroimage, 22(1), 2941.10.1016/j.neuroimage.2003.11.016CrossRefGoogle ScholarPubMed
New, A. B., Robin, D. A., Parkinson, A. L., Duffy, J. R., McNeil, M. R., O. Piguet, O., Hornberger, M., Price, C. J., Eickhoff, S. B., & Ballard, K. J. (2015). Altered resting-state network connectivity in stroke patients with and without apraxia of speech. NeuroImage: Clinical, 8, 429439.10.1016/j.nicl.2015.03.013CrossRefGoogle ScholarPubMed
Postman-Caucheteux, W. A., Birn, R. M., Pursley, R. H., Butman, J. A., Solomon, J. M., Picchioni, D., McArdle, J., & Braun, A. R. (2010). Single-trial fMRI shows contralesional activity linked to overt naming errors in chronic aphasic patients. Journal of Cognitive Neuroscience, 22(6), 12991318.10.1162/jocn.2009.21261CrossRefGoogle ScholarPubMed
Price, C. J., & Crinion, J. (2005). The latest on functional imaging studies of aphasic stroke. Current Opinion in Neurology, 18(4), 429434.10.1097/01.wco.0000168081.76859.c1CrossRefGoogle ScholarPubMed
Sandberg, C. W. (2017). Hypoconnectivity of resting-state networks in persons with aphasia compared with healthy age-matched adults. Frontiers in Human Neuroscience, 11.10.3389/fnhum.2017.00091CrossRefGoogle ScholarPubMed
Saur, D., Lange, R., Baumgaertner, A., Schraknepper, V., Willmes, K., Rijntjes, M., & Weiller, C. (2006). Dynamics of language reorganization after stroke. Brain, 129(6), 13711384.10.1093/brain/awl090CrossRefGoogle ScholarPubMed
Siegel, J. S., Ramsey, L. E., Snyder, A. Z., Metcalf, N. V., Chacko, R. V., Weinberger, K., Baldassarre, A., Hacker, C. D., Shulman, G. L., & Corbetta, M. (2016). Disruptions of network connectivity predict impairment in multiple behavioral domains after stroke. Proceedings of the National Academy of Sciences, 113(30), E4367E4376.10.1073/pnas.1521083113CrossRefGoogle ScholarPubMed
Siegel, J. S., Seitzman, B. A., Ramsey, L. E., Ortega, M., Gordon, E. M., Dosenbach, N. U. F., Petersen, S. E., Shulman, G. L., & Corbetta, M. (2018). Re-emergence of modular brain networks in stroke recovery. Cortex, 101, 4459.10.1016/j.cortex.2017.12.019CrossRefGoogle ScholarPubMed
Sparks, R., Helm, N., & Albert, M. (1974). Aphasia rehabilitation resulting from melodic intonation therapy. Cortex, 10(4), 303316.10.1016/S0010-9452(74)80024-9CrossRefGoogle ScholarPubMed
Thiel, A., Herholz, K., Koyuncu, A., Ghaemi, M., Kracht, L. W., Habedank, B., & Heiss, W. D. (2001). Plasticity of language networks in patients with brain tumors: A positron emission tomography activation study. Annals of Neurology, 50(5), 620629.10.1002/ana.1253CrossRefGoogle ScholarPubMed
Tinaz, S., Lauro, P., Hallett, M., & Horovitz, S. G. (2016). Deficits in task-set maintenance and execution networks in Parkinson’s disease. Brain Structure and Function, 221(3), 14131425.10.1007/s00429-014-0981-8CrossRefGoogle ScholarPubMed
Truzman, T., Rochon, E., Meltzer, J., Leonard, C., & Bitan, T. (2021). Simultaneous normalization and compensatory changes in right hemisphere connectivity during aphasia therapy. Brain Sciences, 11(10), 1330.10.3390/brainsci11101330CrossRefGoogle ScholarPubMed
van Hees, S., McMahon, K., Angwin, A., de Zubicaray, G., Read, S., & Copland, D. A. (2014). A functional MRI study of the relationship between naming treatment outcomes and resting state functional connectivity in post-stroke aphasia. Human Brain Mapping, 35(8), 39193931.10.1002/hbm.22448CrossRefGoogle ScholarPubMed
Wilson, S. M., Eriksson, D. K., Yen, M., Demarco, A. T., Schneck, S. M., & Lucanie, J. M. (2019). Language mapping in aphasia. Journal of Speech, Language, and Hearing Research, 62(11), 39373946.10.1044/2019_JSLHR-L-RSNP-19-0031CrossRefGoogle ScholarPubMed
Xu, L., Huang, L., Cui, W., & Yu, Q. (2020). Reorganized functional connectivity of language centers as a possible compensatory mechanism for basal ganglia aphasia. Brain Injury, 34(3), 430437.10.1080/02699052.2020.1716995CrossRefGoogle ScholarPubMed
Yang, H. Q., Bai, L., Zhou, Y., Kang, S., Liang, P. P., Wang, L. H., & Zhu, Y. F. (2017). Increased inter-hemispheric resting-state functional connectivity in acute lacunar stroke patients with aphasia. Experimental Brain Research, 235(3), 941948.10.1007/s00221-016-4851-xCrossRefGoogle ScholarPubMed
Zhang, C., Xia, Y. Y., Feng, T., Yu, K., Zhang, H. Y., Sami, M. U., Xiang, J., & Xu, K. (2021). Disrupted functional connectivity within and between resting-state networks in the subacute stage of post-stroke aphasia. Frontiers in Neuroscience, 15.10.3389/fnins.2021.746264CrossRefGoogle ScholarPubMed
Zhu, D., Chang, J., Freeman, S., Tan, Z., Xiao, J., Gao, Y., & Kong, J. (2014). Changes of functional connectivity in the left frontoparietal network following aphasic stroke. Frontiers in Behavioral Neuroscience, 8.10.3389/fnbeh.2014.00167CrossRefGoogle ScholarPubMed
Zhu, L., Fan, Y., Zou, Q., Wang, J., Gao, J.-H., & Niu, Z. (2014). Temporal reliability and lateralization of the resting-state language network. PLoS ONE, 9(1).Google ScholarPubMed

References

Alyahya, R. S. W., Halai, A. D., Conroy, P., & Lambon Ralph, M. A. (2018). Noun and verb processing in aphasia: Behavioural profiles and neural correlates. NeuroImage: Clinical, 18, 215230. https://doi.org/10.1016/j.nicl.2018.01.023CrossRefGoogle ScholarPubMed
Alyahya, R. S. W., Halai, A. D., Conroy, P., & Lambon Ralph, M. A. (2020). A unified model of post-stroke language deficits including discourse production and their neural correlates. Brain, 143(5), 15411554. https://doi.org/10.1093/brain/awaa074CrossRefGoogle ScholarPubMed
Barsalou, L. W. (2008). Grounded cognition. Annual Review of Psychology, 59(1), 617645. https://doi.org/10.1146/annurev.psych.59.103006.093639CrossRefGoogle ScholarPubMed
Berndt, R. S., Haendiges, A. N., Mitchum, C. C., & Sandson, J. (1997). Verb retrieval in aphasia. 2. Relationship to sentence processing. Brain and Language, 56(1), 107137. https://doi.org/10.1006/brln.1997.1728CrossRefGoogle ScholarPubMed
Berndt, R. S., Mitchum, C. C., & Haendiges, A. N. (1996). Comprehension of reversible sentences in “agrammatism”: A meta-analysis. Cognition, 58(3), 289308. https://doi.org/10.1016/0010-0277(95)00682-6CrossRefGoogle ScholarPubMed
Binder, J. R. (2016). Phoneme perception. In Neurobiology of Language (pp. 447461). Elsevier. https://doi.org/10.1016/B978-0-12-407794-2.00037-7CrossRefGoogle Scholar
Binder, J. R., & Desai, R. H. (2011). The neurobiology of semantic memory. Trends in Cognitive Sciences, 15(11), 527536. https://doi.org/10.1016/j.tics.2011.10.001CrossRefGoogle ScholarPubMed
Binder, J. R., Desai, R. H., Graves, W. W., & Conant, L. L. (2009). Where is the semantic system? A critical review and meta-analysis of 120 functional neuroimaging studies. Cerebral Cortex, 19(12), 27672796. https://doi.org/10.1093/cercor/bhp055CrossRefGoogle Scholar
Bird, H., Howard, D., & Franklin, S. (2003). Verbs and nouns: The importance of being imageable. Journal of Neurolinguistics, 16(2–3), 113149. https://doi.org/10.1016/S0911-6044(02)00016-7CrossRefGoogle Scholar
Blumstein, S. E. (2016). Psycholinguistic approaches to the study of syndromes and symptoms of aphasia. In Neurobiology of Language (pp. 923933). Elsevier. https://doi.org/10.1016/B978-0-12-407794-2.00074-2CrossRefGoogle Scholar
Bolhuis, J. J., Tattersall, I., Chomsky, N., & Berwick, R. C. (2014). How could language have evolved?PLoS Biology, 12(8), e1001934. https://doi.org/10.1371/journal.pbio.1001934CrossRefGoogle ScholarPubMed
Borghi, A. M., Barca, L., Binkofski, F., Castelfranchi, C., Pezzulo, G., & Tummolini, L. (2019). Words as social tools: Language, sociality and inner grounding in abstract concepts. Physics of Life Reviews, 29, 120153. https://doi.org/10.1016/j.plrev.2018.12.001CrossRefGoogle ScholarPubMed
Breier, J. I., Hasan, K. M., Zhang, W., Men, D., & Papanicolaou, A. C. (2008). Language dysfunction after stroke and damage to white matter tracts evaluated using diffusion tensor imaging. American Journal of Neuroradiology, 29(3), 483487. https://doi.org/10.3174/ajnr.A0846CrossRefGoogle Scholar
Breier, J. I., Juranek, J., & Papanicolaou, A. C. (2011). Changes in maps of language function and the integrity of the arcuate fasciculus after therapy for chronic aphasia. Neurocase, 17(6), 506517. https://doi.org/10.1080/13554794.2010.547505CrossRefGoogle ScholarPubMed
Broca, P. (1861). Nouvelle observation d’aphémie produite par une lésion de la moitié postérieure des deuxième et troisième circonvolution frontales gauches. Bull Soc Anat Paris, 36, 398407.Google Scholar
Bucur, M., & Papagno, C. (2021). An ALE meta-analytical review of the neural correlates of abstract and concrete words. Scientific Reports, 11(1), 15727. https://doi.org/10.1038/s41598-021-94506-9CrossRefGoogle ScholarPubMed
Butler, R. A., Lambon Ralph, M. A., & Woollams, A. M. (2014). Capturing multidimensionality in stroke aphasia: Mapping principal behavioural components to neural structures. Brain, 137(12), 32483266. https://doi.org/10.1093/brain/awu286CrossRefGoogle ScholarPubMed
Caplan, D. (1993). Toward a psycholinguistic approach to acquired neurogenic language disorders. American Journal of Speech-Language Pathology, 2(1), 5983. https://doi.org/10.1044/1058-0360.0201.59CrossRefGoogle Scholar
Caplan, D. (2015). The neural basis of syntatic processing. In Hillis, A. E. (Ed.), The Handbook of Adult Language Disorders (2nd ed., pp. 355374). Psychology Press.Google Scholar
Caplan, D., & Hanna, J. E. (1998). Sentence production by aphasic patients in a constrained task. Brain and Language, 63(2), 184218. https://doi.org/10.1006/brln.1998.1930CrossRefGoogle Scholar
Caplan, D., Michaud, J., & Hufford, R. (2013). Short-term memory, working memory, and syntactic comprehension in aphasia. Cognitive Neuropsychology, 30(2), 77109. https://doi.org/10.1080/02643294.2013.803958CrossRefGoogle ScholarPubMed
Caplan, D., & Waters, G. S. (1999). Verbal working memory and sentence comprehension. Behavioral and Brain Sciences, 22(01). https://doi.org/10.1017/S0140525X99001788CrossRefGoogle ScholarPubMed
Caramazza, A., & Shelton, J. R. (1998). Domain-specific knowledge systems in the brain: The animate-inanimate distinction. Journal of Cognitive Neuroscience, 10(1), 134. https://doi.org/10.1162/089892998563752CrossRefGoogle ScholarPubMed
Caramazza, A., & Zurif, E. B. (1976). Dissociation of algorithmic and heuristic processes in language comprehension: Evidence from aphasia. Brain and Language, 3(4), 572582. https://doi.org/10.1016/0093-934X(76)90048-1CrossRefGoogle ScholarPubMed
Catani, M., & ffytche, D. H. (2005). The rises and falls of disconnection syndromes. Brain: A Journal of Neurology, 128(Pt 10), 22242239. https://doi.org/10.1093/brain/awh622CrossRefGoogle ScholarPubMed
Chang, F., Dell, G. S., & Bock, K. (2006). Becoming syntactic. Psychological Review, 113(2), 234272. https://doi.org/10.1037/0033-295X.113.2.234CrossRefGoogle ScholarPubMed
Chapman, C. A., Hasan, O., Schulz, P. E., & Martin, R. C. (2020). Evaluating the distinction between semantic knowledge and semantic access: Evidence from semantic dementia and comprehension-impaired stroke aphasia. Psychonomic Bulletin & Review, 27(4), 607639. https://doi.org/10.3758/s13423-019-01706-6CrossRefGoogle ScholarPubMed
Charidimou, A., Kasselimis, D., Varkanitsa, M., Selai, C., Potagas, C., & Evdokimidis, I. (2014). Why is it difficult to predict language impairment and outcome in patients with aphasia after stroke? Journal of Clinical Neurology, 10(2), 75. https://doi.org/10.3988/jcn.2014.10.2.75CrossRefGoogle ScholarPubMed
Cloutman, L., Gottesman, R., Chaudhry, P., Davis, C., Kleinman, J. T., Pawlak, M., Herskovits, E. H., Kannan, V., Lee, A., Newhart, M., Heidler-Gary, J., & Hillis, A. E. (2009). Where (in the brain) do semantic errors come from?Cortex, 45(5), 641649. https://doi.org/10.1016/j.cortex.2008.05.013CrossRefGoogle ScholarPubMed
Collins, A. M., & Loftus, E. F. (1975). A spreading-activation theory of semantic processing. Psychological Review, 82(6), 407428. https://doi.org/10.1037/0033-295X.82.6.407CrossRefGoogle Scholar
Coltheart, M., Rastle, K., Perry, C., Langdon, R., & Ziegler, J. (2001). DRC: A dual route cascaded model of visual word recognition and reading aloud. Psychological Review, 108(1), 204256. https://doi.org/10.1037/0033-295X.108.1.204CrossRefGoogle Scholar
Conca, F., Borsa, V. M., Cappa, S. F., & Catricalà, E. (2021). The multidimensionality of abstract concepts: A systematic review. Neuroscience & Biobehavioral Reviews, 127, 474491. https://doi.org/10.1016/j.neubiorev.2021.05.004CrossRefGoogle ScholarPubMed
DeLeon, J., Gottesman, R. F., Kleinman, J. T., Newhart, M., Davis, C., Heidler-Gary, J., Lee, A., & Hillis, A. E. (2007). Neural regions essential for distinct cognitive processes underlying picture naming. Brain, 130(5), 14081422. https://doi.org/10.1093/brain/awm011CrossRefGoogle ScholarPubMed
Dell, G. S., & O’Seaghdha, P. G. (1992). Stages of lexical access in language production. Cognition, 42(1–3), 287314. https://doi.org/10.1016/0010-0277(92)90046-KCrossRefGoogle ScholarPubMed
Dell, G. S., Schwartz, M. F., Martin, N., Saffran, E. M., & Gagnon, D. A. (1997). Lexical access in aphasic and nonaphasic speakers. Psychological Review, 104(4), 801838.10.1037/0033-295X.104.4.801CrossRefGoogle ScholarPubMed
Dell, G. S., Schwartz, M. F., Nozari, N., Faseyitan, O., & Branch Coslett, H. (2013). Voxel-based lesion-parameter mapping: Identifying the neural correlates of a computational model of word production. Cognition, 128(3), 380396. https://doi.org/10.1016/j.cognition.2013.05.007CrossRefGoogle ScholarPubMed
den Ouden, D. B., Malyutina, S., Basilakos, A., Bonilha, L., Gleichgerrcht, E., Yourganov, G., Hillis, A. E., Hickok, G., Rorden, C., & Fridriksson, J. (2019). Cortical and structural‐connectivity damage correlated with impaired syntactic processing in aphasia. Human Brain Mapping, 40(7), 21532173. https://doi.org/10.1002/hbm.24514CrossRefGoogle ScholarPubMed
Desai, R. H., Reilly, M., & van Dam, W. (2018). The multifaceted abstract brain. Philosophical Transactions of the Royal Society B: Biological Sciences, 373(1752), 20170122. https://doi.org/10.1098/rstb.2017.0122CrossRefGoogle ScholarPubMed
Devinsky, O. (2009). Norman Geschwind: Influence on his career and comments on his course on the neurology of behavior. Epilepsy & Behavior, 15(4), 413416. https://doi.org/10.1016/j.yebeh.2009.04.029CrossRefGoogle Scholar
Diveica, V., Koldewyn, K., & Binney, R. J. (2021). Establishing a role of the semantic control network in social cognitive processing: A meta-analysis of functional neuroimaging studies. NeuroImage, 245, 118702. https://doi.org/10.1016/j.neuroimage.2021.118702CrossRefGoogle ScholarPubMed
Dronkers, N. F., Plaisant, O., Iba-Zizen, M. T., & Cabanis, E. A. (2007). Paul Broca’s historic cases: High resolution MR imaging of the brains of Leborgne and Lelong. Brain, 130(5), 14321441. https://doi.org/10.1093/brain/awm042CrossRefGoogle ScholarPubMed
Duncan, J. (2010). The multiple-demand (MD) system of the primate brain: Mental programs for intelligent behaviour. Trends in Cognitive Sciences, 14(4), 172179. https://doi.org/10.1016/j.tics.2010.01.004CrossRefGoogle ScholarPubMed
Ellis, A. W., & Young, A. W. (1988). Human Cognitive Neuropsychology. L. Erlbaum Associates, Publishers.Google Scholar
Fedorenko, E., Behr, M. K., & Kanwisher, N. (2011). Functional specificity for high-level linguistic processing in the human brain. Proceedings of the National Academy of Sciences, 108(39), 1642816433. https://doi.org/10.1073/pnas.1112937108CrossRefGoogle ScholarPubMed
Fedorenko, E., & Thompson-Schill, S. L. (2014). Reworking the language network. Trends in Cognitive Sciences, 18(3), 120126. https://doi.org/10.1016/j.tics.2013.12.006CrossRefGoogle ScholarPubMed
Fodor, J. A. (1975). The Language of Thought (Digit. repr). Harvard University Press.Google Scholar
Fridriksson, J., Bonilha, L., & Rorden, C. (2007). Severe Broca’s aphasia without Broca’s area damage. Behavioural Neurology, 18(4), 237238. https://doi.org/10.1155/2007/785280CrossRefGoogle ScholarPubMed
Fridriksson, J., den Ouden, D.-B., Hillis, A. E., Hickok, G., Rorden, C., Basilakos, A., Yourganov, G., & Bonilha, L. (2018). Anatomy of aphasia revisited. Brain, 141(3), 848862. https://doi.org/10.1093/brain/awx363CrossRefGoogle ScholarPubMed
Fridriksson, J., Kjartansson, O., Morgan, P. S., Hjaltason, H., Magnusdottir, S., Bonilha, L., & Rorden, C. (2010). Impaired speech repetition and left parietal lobe damage. The Journal of Neuroscience, 30(33), 1105711061. https://doi.org/10.1523/JNEUROSCI.1120-10.2010CrossRefGoogle ScholarPubMed
Friederici, A. D. (2011). The brain basis of language processing: From structure to function. Physiological Reviews, 91(4), 13571392. https://doi.org/10.1152/physrev.00006.2011CrossRefGoogle ScholarPubMed
Friederici, A. D., Chomsky, N., Berwick, R. C., Moro, A., & Bolhuis, J. J. (2017). Language, mind and brain. Nature Human Behaviour, 1(10), 713722. https://doi.org/10.1038/s41562-017-0184-4CrossRefGoogle ScholarPubMed
Friederici, A. D., & Gierhan, S. M. (2013). The language network. Current Opinion in Neurobiology, 23(2), 250254. https://doi.org/10.1016/j.conb.2012.10.002CrossRefGoogle ScholarPubMed
Gainotti, G. (2010). The influence of anatomical locus of lesion and of gender-related familiarity factors in category-specific semantic disorders for animals, fruits and vegetables: A review of single-case studies. Cortex, 46(9), 10721087. https://doi.org/10.1016/j.cortex.2010.04.002CrossRefGoogle ScholarPubMed
Garrett, M. F. (1975). The analysis of sentence production. In Psychology of Learning and Motivation (Vol. 9, pp. 133177). Elsevier. https://doi.org/10.1016/S0079-7421(08)60270-4Google Scholar
Geschwind, N. (1965a). Disconnexion syndromes in animals and man. Part I. Brain: A Journal of Neurology, 88(2), 237294. https://doi.org/10.1093/brain/88.2.237CrossRefGoogle Scholar
Geschwind, N. (1965b). Disconnexion syndromes in animals and man. Part II. Brain, 88(3), 585585. https://doi.org/10.1093/brain/88.3.585CrossRefGoogle Scholar
Geschwind, N. (1970). The organization of language and the brain. Science (New York, N.Y.), 170(3961), 940944. https://doi.org/10.1126/science.170.3961.940CrossRefGoogle ScholarPubMed
Geva, S., Correia, M. M., & Warburton, E. A. (2015). Contributions of bilateral white matter to chronic aphasia symptoms as assessed by diffusion tensor MRI. Brain and Language, 150, 117128. https://doi.org/10.1016/j.bandl.2015.09.001CrossRefGoogle ScholarPubMed
Gibson, E. (2000). The dependency locality theory: A distance-based theory of linguistic complexity. Image, Language, Brain: Papers from the First Mind Articulation Project Symposium., 94–126.Google Scholar
Gibson, E., Sandberg, C., Fedorenko, E., Bergen, L., & Kiran, S. (2016). A rational inference approach to aphasic language comprehension. Aphasiology, 30(11), 13411360. https://doi.org/10.1080/02687038.2015.1111994CrossRefGoogle Scholar
Gleichgerrcht, E., Roth, R., Fridriksson, J., den Ouden, D., Delgaizo, J., Stark, B., Hickok, G., Rorden, C., Wilmskoetter, J., Hillis, A., & Bonilha, L. (2021). Neural bases of elements of syntax during speech production in patients with aphasia. Brain and Language, 222, 105025. https://doi.org/10.1016/j.bandl.2021.105025CrossRefGoogle ScholarPubMed
Gorno-Tempini, M. L., Hillis, A. E., Weintraub, S., Kertesz, A., Mendez, M., Cappa, S. F., Ogar, J. M., Rohrer, J. D., Black, S., Boeve, B. F., Manes, F., Dronkers, N. F., Vandenberghe, R., Rascovsky, K., Patterson, K., Miller, B. L., Knopman, D. S., Hodges, J. R., Mesulam, M. M., & Grossman, M. (2011). Classification of primary progressive aphasia and its variants. Neurology, 76(11), 10061014. https://doi.org/10.1212/WNL.0b013e31821103e6CrossRefGoogle ScholarPubMed
Grodzinsky, Y. (1995). A restrictive theory of agrammatic comprehension. Brain and Language, 50(1), 2751. https://doi.org/10.1006/brln.1995.1039CrossRefGoogle ScholarPubMed
Hagoort, P. (2013). MUC (memory, unification, control) and beyond. Frontiers in Psychology, 4. https://doi.org/10.3389/fpsyg.2013.00416CrossRefGoogle ScholarPubMed
Halai, A. D., Woollams, A. M., & Lambon Ralph, M. A. (2017). Using principal component analysis to capture individual differences within a unified neuropsychological model of chronic post-stroke aphasia: Revealing the unique neural correlates of speech fluency, phonology and semantics. Cortex, 86, 275289. https://doi.org/10.1016/j.cortex.2016.04.016CrossRefGoogle ScholarPubMed
Halai, A. D., Woollams, A. M., & Lambon Ralph, M. A. (2018). Predicting the pattern and severity of chronic post-stroke language deficits from functionally-partitioned structural lesions. NeuroImage: Clinical, 19, 113. https://doi.org/10.1016/j.nicl.2018.03.011CrossRefGoogle ScholarPubMed
Han, Z., Ma, Y., Gong, G., He, Y., Caramazza, A., & Bi, Y. (2013). White matter structural connectivity underlying semantic processing: Evidence from brain damaged patients. Brain, 136(10), 29522965. https://doi.org/10.1093/brain/awt205CrossRefGoogle ScholarPubMed
Henseler, I., Regenbrecht, F., & Obrig, H. (2014). Lesion correlates of patholinguistic profiles in chronic aphasia: Comparisons of syndrome-, modality- and symptom-level assessment. Brain, 137(3), 918930. https://doi.org/10.1093/brain/awt374CrossRefGoogle ScholarPubMed
Hickok, G., & Poeppel, D. (2004). Dorsal and ventral streams: A framework for understanding aspects of the functional anatomy of language. Cognition, 92(1–2), 6799. https://doi.org/10.1016/j.cognition.2003.10.011CrossRefGoogle ScholarPubMed
Hickok, G., & Poeppel, D. (2007). The cortical organization of speech processing. Nature Reviews Neuroscience, 8(5), 393402. https://doi.org/10.1038/nrn2113CrossRefGoogle ScholarPubMed
Hillis, A. E., & Caramazza, A. (1995). Representation of grammatical categories of words in the brain. Journal of Cognitive Neuroscience, 7(3), 396407. https://doi.org/10.1162/jocn.1995.7.3.396CrossRefGoogle ScholarPubMed
Hillis, A. E., & Heidler, J. (2002). Mechanisms of early aphasia recovery. Aphasiology, 16(9), 885895. https://doi.org/10.1080/0268703CrossRefGoogle Scholar
Hillis, A. E., Kane, A., Tuffiash, E., Ulatowski, J. A., Barker, P. B., Beauchamp, N. J., & Wityk, R. J. (2001). Reperfusion of specific brain regions by raising blood pressure restores selective language functions in subacute stroke. Brain and Language, 79(3), 495510. https://doi.org/10.1006/brln.2001.2563CrossRefGoogle ScholarPubMed
Hillis, A. E., Kleinman, J. T., Newhart, M., Heidler-Gary, J., Gottesman, R., Barker, P. B., Aldrich, E., Llinas, R., Wityk, R., & Chaudhry, P. (2006). Restoring cerebral blood flow reveals neural regions critical for naming. Journal of Neuroscience, 26(31), 80698073. https://doi.org/10.1523/JNEUROSCI.2088-06.2006CrossRefGoogle ScholarPubMed
Hillis, A. E., Wityk, R. J., Tuffiash, E., Beauchamp, N. J., Jacobs, M. A., Barker, P. B., & Selnes, O. A. (2001). Hypoperfusion of Wernicke’s area predicts severity of semantic deficit in acute stroke. Annals of Neurology, 50(5), 561566. https://doi.org/10.1002/ana.1265CrossRefGoogle ScholarPubMed
Hodgson, V. J., Lambon Ralph, M. A., & Jackson, R. L. (2021). Multiple dimensions underlying the functional organization of the language network. NeuroImage, 241, 118444. https://doi.org/10.1016/j.neuroimage.2021.118444CrossRefGoogle ScholarPubMed
Hoffman, P., Binney, R. J., & Lambon Ralph, M. A. (2015). Differing contributions of inferior prefrontal and anterior temporal cortex to concrete and abstract conceptual knowledge. Cortex, 63, 250266. https://doi.org/10.1016/j.cortex.2014.09.001CrossRefGoogle ScholarPubMed
Hoffman, P., & Lambon Ralph, M. A. (2011). Reverse concreteness effects are not a typical feature of semantic dementia: Evidence for the hub-and-spoke model of conceptual representation. Cerebral Cortex, 21(9), 21032112. https://doi.org/10.1093/cercor/bhq288CrossRefGoogle Scholar
Indefrey, P., & Levelt, W. J. M. (2004). The spatial and temporal signatures of word production components. Cognition, 92(1–2), 101144. https://doi.org/10.1016/j.cognition.2002.06.001CrossRefGoogle ScholarPubMed
Ivanova, M. V., Isaev, D. Yu., Dragoy, O. V., Akinina, Y. S., Petrushevskiy, A. G., Fedina, O. N., Shklovsky, V. M., & Dronkers, N. F. (2016). Diffusion-tensor imaging of major white matter tracts and their role in language processing in aphasia. Cortex, 85, 165181. https://doi.org/10.1016/j.cortex.2016.04.019CrossRefGoogle ScholarPubMed
Jefferies, E., & Lambon Ralph, M. A. (2006). Semantic impairment in stroke aphasia versus semantic dementia: A case-series comparison. Brain, 129(8), 21322147. https://doi.org/10.1093/brain/awl153CrossRefGoogle ScholarPubMed
Kasselimis, D. S., Simos, P. G., Peppas, C., Evdokimidis, I., & Potagas, C. (2017). The unbridged gap between clinical diagnosis and contemporary research on aphasia: A short discussion on the validity and clinical utility of taxonomic categories. Brain and Language, 164, 6367. https://doi.org/10.1016/j.bandl.2016.10.005CrossRefGoogle Scholar
Kemmerer, D. (2014). Word classes in the brain: Implications of linguistic typology for cognitive neuroscience. Cortex, 58, 2751. https://doi.org/10.1016/j.cortex.2014.05.004CrossRefGoogle ScholarPubMed
Kemmerer, D. (2022). Cognitive Neuroscience of Language (2nd ed.). Routledge. https://doi.org/10.4324/9781138318427CrossRefGoogle Scholar
Kolk, H. (1995). A time-based approach to agrammatic production. Brain and Language, 50(3), 282303. https://doi.org/10.1006/brln.1995.1049CrossRefGoogle ScholarPubMed
Kolk, H. H. J., & Van Grunsven, M. M. F. (1985). Agrammatism as a variable phenomenon. Cognitive Neuropsychology, 2(4), 347384. https://doi.org/10.1080/02643298508252666CrossRefGoogle Scholar
Kummerer, D., Hartwigsen, G., Kellmeyer, P., Glauche, V., Mader, I., Klöppel, S., Suchan, J., Karnath, H.-O., Weiller, C., & Saur, D. (2013). Damage to ventral and dorsal language pathways in acute aphasia. Brain, 136(2), 619629. https://doi.org/10.1093/brain/aws354CrossRefGoogle ScholarPubMed
Lacey, E. H., Skipper-Kallal, L. M., Xing, S., Fama, M. E., & Turkeltaub, P. E. (2017). Mapping common aphasia assessments to underlying cognitive processes and their neural substrates. Neurorehabilitation and Neural Repair, 31(5), 442450. https://doi.org/10.1177/1545968316688797CrossRefGoogle ScholarPubMed
Lambon Ralph, M. A., Jefferies, E., Patterson, K., & Rogers, T. T. (2017). The neural and computational bases of semantic cognition. Nature Reviews Neuroscience, 18(1), 4255. https://doi.org/10.1038/nrn.2016.150CrossRefGoogle Scholar
Landrigan, J.-F., Zhang, F., & Mirman, D. (2021). A data-driven approach to post-stroke aphasia classification and lesion-based prediction. Brain, awab010. https://doi.org/10.1093/brain/awab010CrossRefGoogle Scholar
Levelt, W. (2012). A History of Psycholinguistics: The Pre-Chomskyan Era. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199653669.001.0001CrossRefGoogle Scholar
Levelt, W. J. M. (1989). Speaking: From Intention to Articulation (pp. xiv, 566). The MIT Press.10.7551/mitpress/6393.003.0003CrossRefGoogle Scholar
Lichtheim, L. (1885). On aphasia. Brain, 7, 433484. https://doi.org/10.7551/mitpress/6393.001.0001CrossRefGoogle Scholar
Linebarger, M. C., Schwartz, M. F., & Saffran, E. M. (1983). Sensitivity to grammatical structure in so-called agrammatic aphasics. Cognition, 13(3), 361392. https://doi.org/10.1016/0010-0277(83)90015-XCrossRefGoogle ScholarPubMed
Lohndal, T. (2014). Introduction. In Lohndal, T., Phrase Structure and Argument Structure (1st ed., pp. 121). Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199677115.003.0001CrossRefGoogle Scholar
Lorca-Puls, D. L., Gajardo-Vidal, A., White, J., Seghier, M. L., Leff, A. P., Green, D. W., Crinion, J. T., Ludersdorfer, P., Hope, T. M. H., Bowman, H., & Price, C. J. (2018). The impact of sample size on the reproducibility of voxel-based lesion-deficit mappings. Neuropsychologia, 115, 101111. https://doi.org/10.1016/j.neuropsychologia.2018.03.014CrossRefGoogle ScholarPubMed
Love, T., & Oster, E. (2002). On the categorization of aphasic typologies: The SOAP (a test of syntactic complexity). Journal of Psycholinguistic Research, 31(5), 503529. https://doi.org/10.1023/A:1021208903394CrossRefGoogle ScholarPubMed
Lwi, S. J., Herron, T. J., Curran, B. C., Ivanova, M. V., Schendel, K., Dronkers, N. F., & Baldo, J. V. (2021). Auditory comprehension deficits in post-stroke aphasia: Neurologic and demographic correlates of outcome and recovery. Frontiers in Neurology, 12, 680248. https://doi.org/10.3389/fneur.2021.680248CrossRefGoogle ScholarPubMed
Madden, E., Kendall, D., & Riley, E. (2022). Acquired disorders of reading: Modeling, assessment, and treatment. In Papathanasiou, I. & Coppens, P. (Eds.), Aphasia and Related Neurogenic Communication Disorders (3rd ed.). Jones & Bartlett Learning.Google Scholar
Magnusdottir, S., Fillmore, P., den Ouden, D. B., Hjaltason, H., Rorden, C., Kjartansson, O., Bonilha, L., & Fridriksson, J. (2013). Damage to left anterior temporal cortex predicts impairment of complex syntactic processing: A lesion-symptom mapping study. Human Brain Mapping, 34(10), 27152723. https://doi.org/10.1002/hbm.22096CrossRefGoogle ScholarPubMed
Mahon, B. Z., & Caramazza, A. (2009). Concepts and categories: A cognitive neuropsychological perspective. Annual Review of Psychology, 60(1), 2751. https://doi.org/10.1146/annurev.psych.60.110707.163532CrossRefGoogle ScholarPubMed
Mahon, B. Z., & Caramazza, A. (2011). What drives the organization of object knowledge in the brain?Trends in Cognitive Sciences, 15(3), 97103. https://doi.org/10.1016/j.tics.2011.01.004CrossRefGoogle ScholarPubMed
Martin, N. (2022). Disorders of word production. In Papathanasiou, I. & Coppens, P. (Eds.), Aphasia and Related Neurogenic Communication Disorders (3rd ed.). Jones & Bartlett Learning.Google Scholar
Martin, R. C., & Romani, C. (1994). Verbal working memory and sentence comprehension: A multiple-components view. Neuropsychology, 8(4), 506.10.1037/0894-4105.8.4.506CrossRefGoogle Scholar
Matchin, W., & Hickok, G. (2020). The cortical organization of syntax. Cerebral Cortex, 30(3), 14811498. https://doi.org/10.1093/cercor/bhz180CrossRefGoogle ScholarPubMed
McNeil, M. R., & Pratt, S. R. (2001). Defining aphasia: Some theoretical and clinical implications of operating from a formal definition. Aphasiology, 15(10–11), 901911. https://doi.org/10.1080/02687040143000276CrossRefGoogle Scholar
Meier, E. L., Sheppard, S. M., Goldberg, E. B., Kelly, C. R., Walker, A., Ubellacker, D. M., Vitti, E., Ruch, K., & Hillis, A. E. (2021). Dysfunctional tissue correlates of unrelated naming errors in acute left hemisphere stroke. Language, Cognition and Neuroscience, 1–18. https://doi.org/10.1080/23273798.2021.1980593Google Scholar
Mirman, D., Chen, Q., Zhang, Y., Wang, Z., Faseyitan, O. K., Coslett, H. B., & Schwartz, M. F. (2015). Neural organization of spoken language revealed by lesion-symptom mapping. Nature Communications, 6, 6762. https://doi.org/10.1038/ncomms7762CrossRefGoogle ScholarPubMed
Mirman, D., Landrigan, J.-F., & Britt, A. E. (2017). Taxonomic and thematic semantic systems. Psychological Bulletin, 143(5), 499520. https://doi.org/10.1037/bul0000092CrossRefGoogle ScholarPubMed
Mirman, D., Zhang, Y., Wang, Z., Coslett, H. B., & Schwartz, M. F. (2015). The ins and outs of meaning: Behavioral and neuroanatomical dissociation of semantically-driven word retrieval and multimodal semantic recognition in aphasia. Neuropsychologia, 76, 208219. https://doi.org/10.1016/j.neuropsychologia.2015.02.014CrossRefGoogle ScholarPubMed
Miyake, A., Carpenter, P. A., & Just, M. A. (1994). A capacity approach to syntactic comprehension disorders: Making normal adults perform like aphasic patients. Cognitive Neuropsychology, 11(6), 671717. https://doi.org/10.1080/02643299408251989CrossRefGoogle Scholar
Mohr, J. P., Pessin, M. S., Finkelstein, S., Funkenstein, H. H., Duncan, G. W., & Davis, K. R. (1978). Broca aphasia: Pathologic and clinical. Neurology, 28(4), 311311. https://doi.org/10.1212/WNL.28.4.311CrossRefGoogle ScholarPubMed
Noonan, K. A., Jefferies, E., Visser, M., & Lambon Ralph, M. A. (2013). Going beyond inferior prefrontal involvement in semantic control: Evidence for the additional contribution of dorsal angular gyrus and posterior middle temporal cortex. Journal of Cognitive Neuroscience, 25(11), 18241850. https://doi.org/10.1162/jocn_a_00442CrossRefGoogle ScholarPubMed
Norris, D., & McQueen, J. M. (2008). Shortlist B: A Bayesian model of continuous speech recognition. Psychological Review, 115(2), 357395. https://doi.org/10.1037/0033-295X.115.2.357CrossRefGoogle Scholar
Novick, J. M., Trueswell, J. C., & Thompson-Schill, S. L. (2005). Cognitive control and parsing: Reexamining the role of Broca’s area in sentence comprehension. Cognitive, Affective, & Behavioral Neuroscience, 5(3), 263281. https://doi.org/10.3758/CABN.5.3.263CrossRefGoogle ScholarPubMed
Ostrin, R. K., & Schwartz, M. F. (1986). Reconstructing from a degraded trace: A study of sentence repetition in agrammatism. Brain and Language, 28(2), 328345. https://doi.org/10.1016/0093-934X(86)90109-4CrossRefGoogle Scholar
Paivio, A. (1971). Imagery and language. In Imagery (pp. 732). Elsevier. https://doi.org/10.1016/B978-0-12-635450-8.50008-XCrossRefGoogle Scholar
Pillay, S. B., Stengel, B. C., Humphries, C., Book, D. S., & Binder, J. R. (2014). Cerebral localization of impaired phonological retrieval during rhyme judgment. Annals of Neurology, 76(5), 738746. https://doi.org/10.1002/ana.24266CrossRefGoogle ScholarPubMed
Riccardi, N., Yourganov, G., Rorden, C., Fridriksson, J., & Desai, R. (2020). Degradation of praxis brain networks and impaired comprehension of manipulable nouns in stroke. Journal of Cognitive Neuroscience, 32(3), 467483. https://doi.org/10.1162/jocn_a_01495CrossRefGoogle ScholarPubMed
Rogalsky, C., Pitz, E., Hillis, A. E., & Hickok, G. (2008). Auditory word comprehension impairment in acute stroke: Relative contribution of phonemic versus semantic factors. Brain and Language, 107(2), 167169. https://doi.org/10.1016/j.bandl.2008.08.003CrossRefGoogle ScholarPubMed
Rolheiser, T., Stamatakis, E. A., & Tyler, L. K. (2011). Dynamic processing in the human language system: Synergy between the arcuate fascicle and extreme capsule. Journal of Neuroscience, 31(47), 1694916957. https://doi.org/10.1523/JNEUROSCI.2725-11.2011CrossRefGoogle ScholarPubMed
Saffran, E. M., & Martin, N. (1990). 16. Short-term memory impairment and sentence processing: A case study. Neuropsychological Impairments of Short-Term Memory, 428. https://doi.org/10.1017/CBO9780511665547.021CrossRefGoogle Scholar
Saffran, E. M., Schwartz, M. F., & Marin, O. S. (1980). The word order problem in agrammatism: II. Production. Brain and Language, 10(2), 263280. https://doi.org/10.1016/0093-934X(80)90056-5CrossRefGoogle Scholar
Sandberg, C. W., & Kiran, S. (2014). Analysis of abstract and concrete word processing in persons with aphasia and age-matched neurologically healthy adults using fMRI. Neurocase, 20(4), 361388. https://doi.org/10.1080/13554794.2013.770881CrossRefGoogle ScholarPubMed
Schumacher, R., Halai, A. D., & Lambon Ralph, M. A. (2019). Assessing and mapping language, attention and executive multidimensional deficits in stroke aphasia. Brain, 142(10), 32023216. https://doi.org/10.1093/brain/awz258CrossRefGoogle ScholarPubMed
Schwanenflugel, P. J., & Shoben, E. J. (1983). Differential context effects in the comprehension of abstract and concrete verbal materials. Journal of Experimental Psychology: Learning, Memory, and Cognition, 9(1), 82102. https://doi.org/10.1037/0278-7393.9.1.82Google Scholar
Schwartz, M. F. (1984). What the classical aphasia categories can’t do for us, and why. Brain and Language, 21(1), 38. https://doi.org/10.1016/0093-934X(84)90031-2CrossRefGoogle Scholar
Schwartz, M. F., Faseyitan, O., Kim, J., & Coslett, H. B. (2012). The dorsal stream contribution to phonological retrieval in object naming. Brain, 135(12), 37993814. https://doi.org/10.1093/brain/aws300CrossRefGoogle ScholarPubMed
Schwartz, M. F., Kimberg, D. Y., Walker, G. M., Faseyitan, O., Brecher, A., Dell, G. S., & Coslett, H. B. (2009). Anterior temporal involvement in semantic word retrieval: Voxel-based lesion-symptom mapping evidence from aphasia. Brain, 132(12), 34113427. https://doi.org/10.1093/brain/awp284CrossRefGoogle ScholarPubMed
Schwartz, M. F., Saffran, E. M., & Marin, O. S. M. (1980). The word order problem in agrammatism. Brain and Language, 10(2), 249262. https://doi.org/10.1016/0093-934X(80)90055-3CrossRefGoogle ScholarPubMed
Shain, C., Blank, I. A., Fedorenko, E., Gibson, E., & Schuler, W. (2021). Robust effects of working memory demand during naturalistic language comprehension in language-selective cortex [Preprint]. Neuroscience. https://doi.org/10.1101/2021.09.18.460917CrossRefGoogle Scholar
Sheppard, S. M., Meier, E. L., Kim, K. T., Breining, B. L., Keator, L. M., Tang, B., Caffo, B. S., & Hillis, A. E. (2022). Neural correlates of syntactic comprehension: A longitudinal study. Brain and Language, 225, 105068. https://doi.org/10.1016/j.bandl.2021.105068CrossRefGoogle ScholarPubMed
Thompson, C. K. (2003). Unaccusative verb production in agrammatic aphasia: The argument structure complexity hypothesis. Journal of Neurolinguistics, 16(2–3), 151167. https://doi.org/10.1016/S0911-6044(02)00014-3CrossRefGoogle ScholarPubMed
Thothathiri, M., Kimberg, D. Y., & Schwartz, M. F. (2012). The Neural basis of reversible sentence comprehension: Evidence from voxel-based lesion symptom mapping in aphasia. Journal of Cognitive Neuroscience, 24(1), 212222. https://doi.org/10.1162/jocn_a_00118CrossRefGoogle ScholarPubMed
Tremblay, P., & Dick, A. S. (2016). Broca and Wernicke are dead, or moving past the classic model of language neurobiology. Brain and Language, 162, 6071. https://doi.org/10.1016/j.bandl.2016.08.004CrossRefGoogle ScholarPubMed
Troche, J., Crutch, S., & Reilly, J. (2014). Clustering, hierarchical organization, and the topography of abstract and concrete nouns. Frontiers in Psychology, 5. https://doi.org/10.3389/fpsyg.2014.00360CrossRefGoogle ScholarPubMed
Tsapkini, K., Jarema, G., & Kehayia, E. (2002). A morphological processing deficit in verbs but not in nouns: A case study in a highly inflected language. Journal of Neurolinguistics, 15(3–5), 265288. https://doi.org/10.1016/S0911-6044(01)00039-2CrossRefGoogle Scholar
Ullman, M. T. (2013). The role of declarative and procedural memory in disorders of language. Linguistic Variation, 13(2), 133154. https://doi.org/10.1075/lv.13.2.01ullCrossRefGoogle Scholar
Varkanitsa, M., & Caplan, D. (2018). On the association between memory capacity and sentence comprehension: Insights from a systematic review and meta-analysis of the aphasia literature. Journal of Neurolinguistics, 48, 425. https://doi.org/10.1016/j.jneuroling.2018.03.003CrossRefGoogle Scholar
Walenski, M., Europa, E., Caplan, D., & Thompson, C. K. (2019). Neural networks for sentence comprehension and production: An ALE‐based meta‐analysis of neuroimaging studies. Human Brain Mapping, 40(8), 22752304. https://doi.org/10.1002/hbm.24523CrossRefGoogle ScholarPubMed
Walker, G. M., Schwartz, M. F., Kimberg, D. Y., Faseyitan, O., Brecher, A., Dell, G. S., & Coslett, H. B. (2011). Support for anterior temporal involvement in semantic error production in aphasia: New evidence from VLSM. Brain and Language, 117(3), 110122. https://doi.org/10.1016/j.bandl.2010.09.008CrossRefGoogle ScholarPubMed
Wang, J., Conder, J. A., Blitzer, D. N., & Shinkareva, S. V. (2010). Neural representation of abstract and concrete concepts: A meta-analysis of neuroimaging studies. Human Brain Mapping, 31(10), 14591468. https://doi.org/10.1002/hbm.20950CrossRefGoogle ScholarPubMed
Warrington, E. K. (1975). The selective impairment of semantic memory. Quarterly Journal of Experimental Psychology, 27(4), 635657. https://doi.org/10.1080/14640747508400525CrossRefGoogle ScholarPubMed
Warrington, E. K., & Mccarthy, R. A. (1987). Categories of knowledge. Further fractionations and an attempted integration. Brain, 110(5), 12731296. https://doi.org/10.1093/brain/110.5.1273CrossRefGoogle Scholar
Webster, J., & Whitworth, A. (2012). Treating verbs in aphasia: Exploring the impact of therapy at the single word and sentence levels: Verb therapy in aphasia. International Journal of Language & Communication Disorders, 47(6), 619636. https://doi.org/10.1111/j.1460-6984.2012.00174.xCrossRefGoogle ScholarPubMed
Wernicke, C. (1874). Der Aphasische Symptomencomplex: Eine Psychologische Studie auf Anatomischer Basis. Cohn & Weigert.Google Scholar
Willmes, K., & Poeck, K. (1993). To what extent can aphasic syndromes be localized?Brain, 116(6), 15271540. https://doi.org/10.1093/brain/116.6.1527CrossRefGoogle ScholarPubMed
Woollams, A. M., Halai, A., & Lambon Ralph, M. A. (2018). Mapping the intersection of language and reading: The neural bases of the primary systems hypothesis. Brain Structure and Function, 223(8), 37693786. https://doi.org/10.1007/s00429-018-1716-zCrossRefGoogle ScholarPubMed
Yarkoni, T., Poldrack, R. A., Nichols, T. E., Van Essen, D. C., & Wagner, T. D. (2011). NeuroSynth: A new platform for large-scale automated synthesis of human functional neuroimaging data. Frontiers in Neuroinformatics, 5. https://doi.org/10.3389/conf.fninf.2011.08.00058Google Scholar
Yourganov, G., Fridriksson, J., Rorden, C., Gleichgerrcht, E., & Bonilha, L. (2016). Multivariate connectome-based symptom mapping in post-stroke patients: Networks supporting language and speech. Journal of Neuroscience, 36(25), 66686679. https://doi.org/10.1523/JNEUROSCI.4396-15.2016CrossRefGoogle ScholarPubMed
Yourganov, G., Smith, K. G., Fridriksson, J., & Rorden, C. (2015). Predicting aphasia type from brain damage measured with structural MRI. Cortex, 73, 203215. https://doi.org/10.1016/j.cortex.2015.09.005CrossRefGoogle ScholarPubMed
Zhao, Y., Halai, A. D., & Lambon Ralph, M. A. (2020). Evaluating the granularity and statistical structure of lesions and behaviour in post-stroke aphasia. Brain Communications, 2(2), fcaa062. https://doi.org/10.1093/braincomms/fcaa062CrossRefGoogle ScholarPubMed

References

Alves, P., Foulon, C., Karolis, V., Bzdok, D., Margulies, D., Volle, E., & Thiebaut de Schotten, M. (2019). An improved neuroanatomical model of the default-mode network reconciles previous neuroimaging and neuropathological findings. Communications Biology, 2, 370.10.1038/s42003-019-0611-3CrossRefGoogle ScholarPubMed
Andrews-Hanna, J. (2012). The brains default network and its adaptive role in internal mentation. The Neuroscientist, 18(3), 251270.10.1177/1073858411403316CrossRefGoogle ScholarPubMed
Andrews-Hanna, J., Reidler, J., Huang, C., & Buckner, R. (2010). Evidence for the default networks role in spontaneous cognition. Journal of Neurophysiology, 104(1), 322335.10.1152/jn.00830.2009CrossRefGoogle ScholarPubMed
Balaev, V., Petrushevsky, A., & Martynova, O. (2016). Changes in functional connectivity of default mode network with auditory and right frontoparietal networks in poststroke aphasia. Brain Connectivity, 6(9), 714723.10.1089/brain.2016.0419CrossRefGoogle ScholarPubMed
Baliki, M., Babbitt, E., & Cherney, L. (2018). Brain network topology influences response to intensive comprehensive aphasia treatment. NeuroRehabilitation, 43(1), 6376.10.3233/NRE-182428CrossRefGoogle ScholarPubMed
Bergeron, D., Beauregard, J., Soucy, J., Verret, L., Poulin, S., Matias-Guiu, J., Cabrera-Martín, M., Bouchard, R., & Laforce, R. (2020). Posterior cingulate cortex hypometabolism in non-amnestic variants of Alzheimer’s disease. Journal of Alzheimer’s Disease, 77(4), 15691577.10.3233/JAD-200567CrossRefGoogle ScholarPubMed
Binder, J., Desai, R., Graves, W., & Conant, L. (2009). Where is the semantic system? A critical review and meta-analysis of 120 functional neuroimaging studies. Cerebral Cortex, 19(12), 27672796.10.1093/cercor/bhp055CrossRefGoogle Scholar
Biswal, B., Yetkin, F., Haughton, V., & Hyde, J. (1995). Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magnetic Resonance in Medicine, 34(4).10.1002/mrm.1910340409CrossRefGoogle ScholarPubMed
Bonakdarpour, B., Rogalski, E., Wang, A., Sridhar, J., Mesulam, M., & Hurley, R. (2017). Functional connectivity is reduced in early-stage primary progressive aphasia when atrophy is not prominent. Alzheimer Disease and Associated Disorders, 31(2), 101106.10.1097/WAD.0000000000000193CrossRefGoogle Scholar
Braga, R., DiNicola, L., Becker, H., & Buckner, R. (2020). Situating the left-lateralized language network in the broader organization of multiple specialized large-scale distributed networks. Journal of Neurophysiology, 124(5), 14151448.10.1152/jn.00753.2019CrossRefGoogle ScholarPubMed
Buckner, R., Andrews-Hanna, J., & Schacter, D. (2008.) The brain’s default network: Anatomy, function, and relevance to disease. Annals of the New York Academy of Sciences, 1124, 138.10.1196/annals.1440.011CrossRefGoogle ScholarPubMed
Buckner, R., & Krienen, F. (2013). The evolution of distributed association networks in the human brain. Trends in Cognitive Sciences, 17(12), 648665.10.1016/j.tics.2013.09.017CrossRefGoogle ScholarPubMed
Buckner, R., Sepulcre, J., Talukdar, T., Krienen, F., Liu, H., Hedden, T., Andrews-Hanna, J., Sperling, R., & Johnson, K. (2009). Cortical hubs revealed by intrinsic functional connectivity: Mapping, assessment of stability, and relation to Alzheimer’s disease. The Journal of Neuroscience, 29(6), 18601873.10.1523/JNEUROSCI.5062-08.2009CrossRefGoogle ScholarPubMed
Campbell, K., & Tyler, L. (2018). Language-related domain-specific and domain-general systems in the human brain. Current Opinion in Behavioral Sciences, 21, 132137.10.1016/j.cobeha.2018.04.008CrossRefGoogle ScholarPubMed
Clemens, B., Jung, S., Mingoia, G., Weyer, D., Domahs, F., & Willmes, K. (2014). Influence of anodal transcranial direct current stimulation (tDCS) over the right angular gyrus on brain activity during rest. PLoS ONE, 9(4), e95984.10.1371/journal.pone.0095984CrossRefGoogle ScholarPubMed
Collins, J., Montal, V., Hochberg, D., Quimby, M., Mandelli, M., Makris, N., Seeley, W., Gorno-Tempini, M., & Dickerson, B. (2017). Focal temporal pole atrophy and network degeneration in semantic variant primary progressive aphasia. Brain, 140(2), 457471.10.1093/brain/aww313CrossRefGoogle ScholarPubMed
Cordes, D., Haughton, V. M., Arfanakis, K., Wendt, G. J., Turski, P. A., Moritz, C. H., Quigley, M. A., & Meyerand, M. E. (2000). Mapping functionally related regions of brain with functional connectivity MR imaging. American Journal of Neuroradiology, 21(9), 16361644.Google ScholarPubMed
Damoiseaux, J., Beckmann, C., Arigita, E., Barkhof, F., Scheltens, P., Stam, C., Smith, S., & Rombouts, S. (2008). Reduced resting-state brain activity in the “default network” in normal aging. Cerebral Cortex, 18(8), 18561864.10.1093/cercor/bhm207CrossRefGoogle Scholar
Davey, C., Pujol, J., & Harrison, B. (2016). Mapping the self in the brain’s default mode network. NeuroImage, 132, 390397.10.1016/j.neuroimage.2016.02.022CrossRefGoogle ScholarPubMed
de Aguiar, V., Zhao, Y., Faria, A., Ficek, B., Webster, K., Wendt, H., Wang, Z., Hillis, A., Onyike, C., Frangakis, C., Caffo, B., & Tsapkini, K. (2020). Brain volumes as predictors of tDCS effects in primary progressive aphasia. Brain and Language, 200, 104707.10.1016/j.bandl.2019.104707CrossRefGoogle ScholarPubMed
Dixon, M., Andrews-Hanna, J., Spreng, R., Irving, Z., Mills, C., Girn, M., & Christoff, K. (2017). Interactions between the default network and dorsal attention network vary across default subsystems, time, and cognitive states. NeuroImage, 147, 632649.10.1016/j.neuroimage.2016.12.073CrossRefGoogle ScholarPubMed
Dreyer, F., Doppelbauer, L., Büscher, V., Arndt, V., Stahl, B., Lucchese, G., Hauk, O., Mohr, B., & Pulvermüller, F. (2021). Increased recruitment of domain-general neural networks in language processing following intensive language-action therapy: fMRI evidence from people with chronic aphasia. American Journal of Speech-Language Pathology, 30(1S), 455465.10.1044/2020_AJSLP-19-00150CrossRefGoogle ScholarPubMed
Duncan, E.S., Anakkathil-Pradeep, A., & Small, S. (2020). A review of biological interventions in chronic aphasia. Annals of Indian Academy of Neurology, 23(Suppl 2).10.4103/aian.AIAN_549_20CrossRefGoogle ScholarPubMed
Duncan, E. S., & Small, S. L. (2016). Increased modularity of resting state networks supports improved narrative production in aphasia recovery. Brain Connectivity, 6(7), 524529.10.1089/brain.2016.0437CrossRefGoogle ScholarPubMed
Duncan, E. S., & Small, S. L. (2018). Changes in dynamic resting state network connectivity following aphasia therapy. Brain Imaging and Behavior, 12(4), 11411149.10.1007/s11682-017-9771-2CrossRefGoogle ScholarPubMed
Elton, A., & Gao, W. (2015). Task-positive functional connectivity of the default mode network transcends task domain. Journal of Cognitive Neuroscience, 27(12), 23692381.10.1162/jocn_a_00859CrossRefGoogle ScholarPubMed
Farrás-Permanyer, L., Mancho-Fora, N., Montalà-Flaquer, M., Bartrés-Faz, D., Vaqué-Alcázar, L., Peró-Cebollero, M., & Guàrdia-Olmos, J. (2019). Age-related changes in resting-state functional connectivity in older adults. Neural Regeneration Research, 14(9), 15441555.10.4103/1673-5374.255976CrossRefGoogle ScholarPubMed
Ficek, B., Wang, Z., Zhao, Y., Webster, K., Desmond, J., Hillis, A., Frangakis, C., Faria, A., Caffo, B., & Tsapkini, K. (2019). The effect of tDCS on functional connectivity in primary progressive aphasia. NeuroImage: Clinical, 19, 703715.10.1016/j.nicl.2018.05.023CrossRefGoogle Scholar
Flöel, A., Meinzer, M., Kirstein, R., Nijhof, S., Deppe, M., Knecht, S., & Breitenstein, C. (2011). Short-term anomia training and electrical brain stimulation. Stroke, 42(7), 20652067.10.1161/STROKEAHA.110.609032CrossRefGoogle ScholarPubMed
Fox, M. D., Snyder, A. Z., Vincent, J. L., Corbetta, M., Van Essen, D. C., & Raichle, M. E. (2005). The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proceeings of the National Academy of Sciences, 102(27), 96739678.10.1073/pnas.0504136102CrossRefGoogle ScholarPubMed
Geng, W., Zhang, J., Shang, S., Chen, H., Shi, M., Jiang, L., Yin, X., & Chen, Y. (2022). Reduced functional network connectivity is associated with upper limb dysfunction in acute ischemic brainstem stroke. Brain Imaging and Behavior, 16(2), 802810.10.1007/s11682-021-00554-0CrossRefGoogle ScholarPubMed
Geranmayeh, F., Leech, R., & Wise, R. (2016). Network dysfunction predicts speech production after left hemisphere stroke. Neurology, 86(14), 12961305.10.1212/WNL.0000000000002537CrossRefGoogle ScholarPubMed
Gola, K., Thorne, A., Veldhuisen, L., Felix, C., Hankinson, S., Pham, J., Shany-Ur, T., Schauer, G., Stanley, C., Glenn, S., Miller, B., & Rankin, K. (2015). Neural substrates of spontaneous narrative production in focal neurodegenerative disease. Neuropsychologia, 79(Pt A), 158171.10.1016/j.neuropsychologia.2015.10.022CrossRefGoogle ScholarPubMed
Gordon, E., Laumann, T., Marek, S., Raut, R., Gratton, C., Newbold, D., Greene, D., Coalson, R., Snyder, A., Schlaggar, B., Petersen, S., Dosenbach, N., & Nelson, S. (2020). Default-mode network streams for coupling to language and control systems. Proceedings of the National Academy of Sciences, 117(29), 1730817319.10.1073/pnas.2005238117CrossRefGoogle ScholarPubMed
Gorno-Tempini, M. L., Hillis, A. E., Weintraub, S., Kertesz, A., Mendez, M., Cappa, S. F., Ogar, J. M., Rohrer, J. D., Black, S., Boeve, B. F., Manes, F., Dronkers, N. F., Vandenberghe, R., Rascovsky, K., Patterson, K., Miller, B. L., Knopman, D. S., Hodges, J. R., Mesulam, M. M., & Grossman, M. (2011). Classification of primary progressive aphasia and its variants. Neurology, 76(11), 10061014.10.1212/WNL.0b013e31821103e6CrossRefGoogle ScholarPubMed
Griffis, J., Nenert, R., Allendorfer, J., Vannest, J., Holland, S., Dietz, A., & Szaflarski, J. (2017). The canonical semantic network supports residual language function in chronic post-stroke aphasia. Human Brain Mapping, 38(3), 16361658.10.1002/hbm.23476CrossRefGoogle ScholarPubMed
Hampson, M., Peterson, B. S., Skudlarski, P., Gatenby, J. C., & Gore, J. C. (2002). Detection of functional connectivity using temporal correlations in MR images. Human Brain Mapping, 15(4), 247262.10.1002/hbm.10022CrossRefGoogle ScholarPubMed
Huang, Y., Mohan, A., McLeod, S., Luckey, A., Hart, J., & Vanneste, S. (2021). Polarity-specific high-definition transcranial direct current stimulation of the anterior and posterior default mode network improves remote memory retrieval. Brain Stimulation, 14(4), 10051014.10.1016/j.brs.2021.06.007CrossRefGoogle ScholarPubMed
Huber, W., Weniger, D., Poeck, K., & Willmes, K. (1980.) [The Aachen Aphasia Test rationale and construct validity (author’s translation)]. Der Nervenarzt, 51(8), 475482.Google Scholar
Johnson, J., Meier, E., Pan, Y., & Kiran, S. (2020). Pre-treatment graph measures of a functional semantic network are associated with naming therapy outcomes in chronic aphasia. Brain and Language, 207, 104809.10.1016/j.bandl.2020.104809CrossRefGoogle ScholarPubMed
Kertesz, A. (2006). Western Aphasia Battery (Revised), PsychCorp, San Antonio, Tx.10.1037/t15168-000CrossRefGoogle Scholar
Koch, G., Bonnì, S., Pellicciari, M., Casula, E., Mancini, M., Esposito, R., Ponzo, V., Picazio, S., Di Lorenzo, F., Serra, L., Motta, C., Maiella, M., Marra, C., Cercignani, M., Martorana, A., Caltagirone, C., & Bozzali, M. (2018). Transcranial magnetic stimulation of the precuneus enhances memory and neural activity in prodromal Alzheimer’s disease. NeuroImage, 169, 302311.10.1016/j.neuroimage.2017.12.048CrossRefGoogle ScholarPubMed
Laforce, R., Tosun, D., Ghosh, P., Lehmann, M., Madison, C., Weiner, M., Miller, B., Jagust, W., & Rabinovici, G. (2014). Parallel ICA of FDG-PET and PiB-PET in three conditions with underlying Alzheimer’s pathology. NeuroImage: Clinical, 4, 508516.10.1016/j.nicl.2014.03.005CrossRefGoogle ScholarPubMed
Lehmann, M., Ghosh, P., Madison, C., Laforce, R., Corbetta-Rastelli, C., Weiner, M., Greicius, M., Seeley, W., Gorno-Tempini, M., Rosen, H., Miller, B., Jagust, W., & Rabinovici, G. (2013a). Diverging patterns of amyloid deposition and hypometabolism in clinical variants of probable Alzheimer’s disease. Brain, 136(Pt 3), 844858.10.1093/brain/aws327CrossRefGoogle ScholarPubMed
Lehmann, M., Madison, C., Ghosh, P., Miller, Z., Greicius, M., Kramer, J., Coppola, G., Miller, B., Jagust, W., Gorno-Tempini, M., Seeley, W., & Rabinovici, G. (2015). Loss of functional connectivity is greater outside the default mode network in nonfamilial early-onset Alzheimer’s disease variants. Neurobiology of Aging, 36(10), 26782686.10.1016/j.neurobiolaging.2015.06.029CrossRefGoogle ScholarPubMed
Lehmann, M., Madison, C., Ghosh, P., Seeley, W., Mormino, E., Greicius, M., Gorno-Tempini, M., Kramer, J., Miller, B., Jagust, W., & Rabinovici, G. (2013b). Intrinsic connectivity networks in healthy subjects explain clinical variability in Alzheimer’s disease. Proceedings of the National Academy of Sciences, 110(28), 1160611611.10.1073/pnas.1221536110CrossRefGoogle ScholarPubMed
Lustig, C., Snyder, A., Bhakta, M., OBrien, K., McAvoy, M., Raichle, M., Morris, J., & Buckner, R. (2003). Functional deactivations: Change with age and dementia of the Alzheimer type. Proceedings of the National Academy of Sciences, 100(24), 1450414509.10.1073/pnas.2235925100CrossRefGoogle ScholarPubMed
Maddy, K., Capilouto, G., & McComas, K. (2014). The effectiveness of semantic feature analysis: An evidence-based systematic review. Annals of Physical and Rehabilitation Medicine, 57(4), 254267.10.1016/j.rehab.2014.03.002CrossRefGoogle ScholarPubMed
Mak, L., Minuzzi, L., MacQueen, G., Hall, G., Kennedy, S., & Milev, R. (2017). The default mode network in healthy individuals: A systematic review and meta-analysis. Brain Connectivity, 7(1), 2533.10.1089/brain.2016.0438CrossRefGoogle ScholarPubMed
Malagurski, B., Liem, F., Oschwald, J., Mérillat, S., & Jäncke, L. (2020). Longitudinal functional brain network reconfiguration in healthy aging. Human Brain Mapping, 41(17), 48294845.10.1002/hbm.25161CrossRefGoogle ScholarPubMed
Mandelli, M., Vilaplana, E., Brown, J., Hubbard, H., Binney, R., Attygalle, S., Santos-Santos, M., Miller, Z., Pakvasa, M., Henry, M., Rosen, H., Henry, R., Rabinovici, G., Miller, B., Seeley, W., & Gorno-Tempini, M. (2016). Healthy brain connectivity predicts atrophy progression in non-fluent variant of primary progressive aphasia. Brain, 139(Pt 10), 27782791.10.1093/brain/aww195CrossRefGoogle ScholarPubMed
Mandelli, M., Welch, A., Vilaplana, E., Watson, C., Battistella, G., Brown, J., Possin, K., Hubbard, H., Miller, Z., Henry, M., Marx, G., Santos-Santos, M., Bajorek, L., Fortea, J., Boxer, A., Rabinovici, G., Lee, S., Deleon, J., Rosen, H., Miller, B., Seeley, W., & Gorno-Tempini, M. (2018). Altered topology of the functional speech production network in non-fluent/agrammatic variant of PPA. Cortex, 108, 252264.10.1016/j.cortex.2018.08.002CrossRefGoogle ScholarPubMed
Marcotte, K., Perlbarg, V., Marrelec, G., Benali, H., & Ansaldo, A. I. (2013) Default-mode network functional connectivity in aphasia: Therapy-induced neuroplasticity. Brain and Language, 124(1), 4555.10.1016/j.bandl.2012.11.004CrossRefGoogle ScholarPubMed
Margulies, D., Ghosh, S., Goulas, A., Falkiewicz, M., Huntenburg, J., Langs, G., Bezgin, G., Eickhoff, S., Castellanos, F., Petrides, M., Jefferies, E., & Smallwood, J. (2016). Situating the default-mode network along a principal gradient of macroscale cortical organization. Proceedings of the National Academy of Sciences, 113(44), 1257412579.10.1073/pnas.1608282113CrossRefGoogle ScholarPubMed
Mars, R., Neubert, F., Noonan, M., Sallet, J., Toni, I., & Rushworth, M. (2012). On the relationship between the “default mode network” and the “social brain.” Frontiers in Human Neuroscience, 6, 189.10.3389/fnhum.2012.00189CrossRefGoogle Scholar
Martersteck, A., Sridhar, J., Rader, B., Coventry, C., Parrish, T., Mesulam, M., & Rogalski, E. (2020). Differential neurocognitive network perturbation in amnestic and aphasic Alzheimer disease. Neurology, 94(7), e699e704.10.1212/WNL.0000000000008960CrossRefGoogle ScholarPubMed
Mason, M., Norton, M., Van Horn, J., Wegner, D., Grafton, S., & Macrae, C. (2007). Wandering minds: The default network and stimulus-independent thought. Science, 315(5810), 393395.10.1126/science.1131295CrossRefGoogle ScholarPubMed
Mazoyer, B., Zago, L., Mellet, E., Bricogne, S., Etard, O., Houdé, O., Crivello, F., Joliot, M., Petit, L., & Tzourio-Mazoyer, N. (2001). Cortical networks for working memory and executive functions sustain the conscious resting state in man. Brain Research Bulletin, 54(3), 297298.10.1016/S0361-9230(00)00437-8CrossRefGoogle ScholarPubMed
Menke, R., Meinzer, M., Kugel, H., Deppe, M., Baumgärtner, A., Schiffbauer, H., Thomas, M., Kramer, K., Lohmann, H., Flöel, A., Knecht, S., & Breitenstein, C. (2009). Imaging short- and long-term training success in chronic aphasia. BMC Neuroscience, 10, 118.10.1186/1471-2202-10-118CrossRefGoogle Scholar
Mevel, K., Landeau, B., Fouquet, M., La Joie, R., Villain, N., Mézenge, F., Perrotin, A., Eustache, F., Desgranges, B., & Chételat, G. (2013). Age effect on the default mode network, inner thoughts, and cognitive abilities. Neurobiology of Aging, 34(4), 12921301.10.1016/j.neurobiolaging.2012.08.018CrossRefGoogle ScholarPubMed
Miao, G., Rao, B., Wang, S., Fang, P., Chen, Z., Chen, L., Zhang, X., Zheng, J., Xu, H., & Liao, W. (2022). Decreased functional connectivities of low-degree level rich club organization and caudate in post-stroke cognitive impairment based on resting-state fMRI and radiomics features. Frontiers in Neuroscience, 15, 796530.10.3389/fnins.2021.796530CrossRefGoogle ScholarPubMed
Mineroff, Z., Blank, I., Mahowald, K., & Fedorenko, E. (2018). A robust dissociation among the language, multiple demand, and default mode networks: Evidence from inter-region correlations in effect size. Neuropsychologia, 119, 501511.10.1016/j.neuropsychologia.2018.09.011CrossRefGoogle ScholarPubMed
Muller, A. M., & Meyer, M. (2014). Language in the brain at rest: New insights from resting state data and graph theoretical analysis. Frontiers in Human Neuroscience, 8, 228.10.3389/fnhum.2014.00228CrossRefGoogle Scholar
Musso, M., Hübner, D., Schwarzkopf, S., Bernodusson, M., LeVan, P., Weiller, C., & Tangermann, M. (2022). Aphasia recovery by language training using a brain–computer interface: A proof-of-concept study. Brain Communications, 4(1), fcac008.10.1093/braincomms/fcac008CrossRefGoogle ScholarPubMed
Naeser, M., Ho, M., Martin, P., Hamblin, M., & Koo, B. (2020). Increased functional connectivity within intrinsic neural networks in chronic stroke following treatment with red/near-infrared transcranial photobiomodulation: Case series with improved naming in aphasia. Photobiomodulation, Photomedicine, and Laser Surgery, 38(2), 115131.10.1089/photob.2019.4630CrossRefGoogle ScholarPubMed
Ng, K., Lo, J., Lim, J., Chee, M., & Zhou, J. (2016). Reduced functional segregation between the default mode network and the executive control network in healthy older adults: A longitudinal study. NeuroImage, 133, 312330.10.1016/j.neuroimage.2016.03.029CrossRefGoogle ScholarPubMed
Nicolas, K., Goodin, P., Visser, M., Michie, P., Bivard, A., Levi, C., Parsons, M., & Karayanidis, F. (2021). Altered functional connectivity and cognition persists 4 years after a transient ischemic attack or minor stroke. Frontiers in Neurology, 12, 612177.10.3389/fneur.2021.612177CrossRefGoogle ScholarPubMed
Ossenkoppele, R., Cohn-Sheehy, B., La Joie, R., Vogel, J., Möller, C., Lehmann, M., van Berckel, B., Seeley, W., Pijnenburg, Y., Gorno-Tempini, M., Kramer, J., Barkhof, F., Rosen, H., van der Flier, W., Jagust, W., Miller, B., Scheltens, P., & Rabinovici, G. (2015). Atrophy patterns in early clinical stages across distinct phenotypes of Alzheimer’s disease. Human Brain Mapping, 36(11), 44214437.10.1002/hbm.22927CrossRefGoogle ScholarPubMed
Ousdal, O., Kaufmann, T., Kolskår, K., Vik, A., Wehling, E., Lundervold, A., Lundervold, A., & Westlye, L. (2020). Longitudinal stability of the brain functional connectome is associated with episodic memory performance in aging. Human Brain Mapping, 41(3), 697709.10.1002/hbm.24833CrossRefGoogle ScholarPubMed
Pearson, J. (2019). The human imagination: The cognitive neuroscience of visual mental imagery. Nature Reviews Neuroscience, 20(10), 624634.10.1038/s41583-019-0202-9CrossRefGoogle ScholarPubMed
Persson, J., Pudas, S., Nilsson, L., & Nyberg, L. (2014). Longitudinal assessment of default-mode brain function in aging. Neurobiology of Aging, 35(9), 21072117.10.1016/j.neurobiolaging.2014.03.012CrossRefGoogle ScholarPubMed
Popal, H., Quimby, M., Hochberg, D., Dickerson, B., & Collins, J. (2020). Altered functional connectivity of cortical networks in semantic variant primary progressive aphasia. NeuroImage: Clinical, 28, 102494.10.1016/j.nicl.2020.102494CrossRefGoogle ScholarPubMed
Putcha, D., Eckbo, R., Katsumi, Y., Dickerson, B., Touroutoglou, A., & Collins, J. (2022). Tau and the fractionated default mode network in atypical Alzheimer’s disease. Brain Communications, 4(2), fcac055.10.1093/braincomms/fcac055CrossRefGoogle ScholarPubMed
Pytel, V., Cabrera-Martín, M., Delgado-Álvarez, A., Ayala, J., Balugo, P., Delgado-Alonso, C., Yus, M., Carreras, M., Carreras, J., Matías-Guiu, J., & Matías-Guiu, J. (2021). Personalized repetitive transcranial magnetic stimulation for primary progressive aphasia. Journal of Alzheimer’s Disease, 84(1), 151167.10.3233/JAD-210566CrossRefGoogle ScholarPubMed
Raichle, M., MacLeod, A., Snyder, A., Powers, W., Gusnard, D., & Shulman, G. (2001). A default mode of brain function. Proceedings of the National Academy of Sciences, 98(2), 676682.10.1073/pnas.98.2.676CrossRefGoogle ScholarPubMed
Sambataro, F., Murty, V., Callicott, J., Tan, H., Das, S., Weinberger, D., & Mattay, V. (2010). Age-related alterations in default mode network: Impact on working memory performance. Neurobiology of Aging, 31(5), 839852.10.1016/j.neurobiolaging.2008.05.022CrossRefGoogle ScholarPubMed
Sandberg, C. W. (2017). Hypoconnectivity of resting-state networks in persons with aphasia compared with healthy age-matched adults. Frontiers in Human Neuroscience, 11.10.3389/fnhum.2017.00091CrossRefGoogle ScholarPubMed
Sandberg, C. W., Bohland, J. W., & Kiran, S. (2015). Changes in functional connectivity related to direct training and generalization effects of a word finding treatment in chronic aphasia. Brain and Language, 150, 103116.10.1016/j.bandl.2015.09.002CrossRefGoogle ScholarPubMed
Schafer, R., & Constable, T. (2009). Modulation of functional connectivity with the syntactic and semantic demands of a noun phrase formation task: A possible role for the default network. NeuroImage, 46(3), 882890.10.1016/j.neuroimage.2009.02.017CrossRefGoogle ScholarPubMed
Seeley, W., Menon, V., Schatzberg, A., Keller, J., Glover, G., Kenna, H., Reiss, A., & Greicius, M. (2007). Dissociable intrinsic connectivity networks for salience processing and executive control. The Journal of Neuroscience, 27(9), 23492356.10.1523/JNEUROSCI.5587-06.2007CrossRefGoogle ScholarPubMed
Seghier, M. L., & Price, C. J. (2012). Functional heterogeneity within the default network during semantic processing and speech production. Frontiers in Psychology, 3, 281.10.3389/fpsyg.2012.00281CrossRefGoogle ScholarPubMed
Siegel, J., Seitzman, B., Ramsey, L., Ortega, M., Gordon, E., Dosenbach, N., Petersen, S., Shulman, G., & Corbetta, M. (2018). Re-emergence of modular brain networks in stroke recovery. Cortex, 101, 4459.10.1016/j.cortex.2017.12.019CrossRefGoogle ScholarPubMed
Sihvonen, A., Leo, V., Ripollés, P., Lehtovaara, T., Ylönen, A., Rajanaro, P., Laitinen, S., Forsblom, A., Saunavaara, J., Autti, T., Laine, M., Rodríguez-Fornells, A., Tervaniemi, M., Soinila, S., & Särkämö, T. (2020). Vocal music enhances memory and language recovery after stroke: Pooled results from two RCTs. Annals of Clinical and Translational Neurology, 7(11), 22722287.10.1002/acn3.51217CrossRefGoogle ScholarPubMed
Skipper, J. (2022). A voice without a mouth no more: The neurobiology of language and consciousness. Neuroscience and Biobehavioral Reviews, 140, 104772.10.1016/j.neubiorev.2022.104772CrossRefGoogle ScholarPubMed
Smits, M., Jiskoot, L., & Papma, J. (2014). White matter tracts of speech and language. Seminars in Ultrasound, CT, and MR, 35(5), 504516.10.1053/j.sult.2014.06.008CrossRefGoogle ScholarPubMed
Spinelli, E., Mandelli, M., Miller, Z., Santos-Santos, M., Wilson, S., Agosta, F., Grinberg, L., Huang, E., Trojanowski, J., Meyer, M., Henry, M., Comi, G., Rabinovici, G., Rosen, H., Filippi, M., Miller, B., Seeley, W., & Gorno-Tempini, M. (2017). Typical and atypical pathology in primary progressive aphasia variants. Annals of Neurology, 81(3), 430443.10.1002/ana.24885CrossRefGoogle ScholarPubMed
Spreng, R., & Schacter, D. (2012). Default network modulation and large-scale network interactivity in healthy young and old adults. Cerebral Cortex, 22(11), 26102621.10.1093/cercor/bhr339CrossRefGoogle ScholarPubMed
Staffaroni, A., Brown, J., Casaletto, K., Elahi, F., Deng, J., Neuhaus, J., Cobigo, Y., Mumford, P., Walters, S., Saloner, R., Karydas, A., Coppola, G., Rosen, H., Miller, B., Seeley, W., & Kramer, J. (2018). The longitudinal trajectory of default mode network connectivity in healthy older adults varies as a function of age and is associated with changes in episodic memory and processing speed. The Journal of Neuroscience, 38(11), 28092817.10.1523/JNEUROSCI.3067-17.2018CrossRefGoogle ScholarPubMed
Tomasi, D., & Volkow, N. (2012). Resting functional connectivity of language networks: Characterization and reproducibility. Molecular Psychiatry, 17(8), 841854.10.1038/mp.2011.177CrossRefGoogle ScholarPubMed
Tuladhar, A., Snaphaan, L., Shumskaya, E., Rijpkema, M., Fernandez, G., Norris, D., & de Leeuw, F. (2013). Default mode network connectivity in stroke patients. PLoS ONE, 8(6), e66556.10.1371/journal.pone.0066556CrossRefGoogle ScholarPubMed
Uddin, L., Yeo, B., & Spreng, R. (2019). Towards a universal taxonomy of macro-scale functional human brain networks. Brain Topography, 32(6), 926942.10.1007/s10548-019-00744-6CrossRefGoogle ScholarPubMed
van Hees, S., McMahon, K., Angwin, A., de Zubicaray, G., Read, S., & Copland, D. A. (2014). A functional MRI study of the relationship between naming treatment outcomes and resting state functional connectivity in post-stroke aphasia. Human Brain Mapping, 35(8), 39193931.10.1002/hbm.22448CrossRefGoogle ScholarPubMed
Vitali, P., Abutalebi, J., Tettamanti, M., Danna, M., Ansaldo, A., Perani, D., Joanette, Y., & Cappa, S. (2007). Training-induced brain remapping in chronic aphasia: A pilot study. Neurorehabilitation and Neural Repair, 21(2), 152160.10.1177/1545968306294735CrossRefGoogle ScholarPubMed
Weiler, M., Fukuda, A., Massabki, L., Lopes, T., Franco, A., Damasceno, B., Cendes, F., & Balthazar, M. (2014). Default mode, executive function, and language functional connectivity networks are compromised in mild Alzheimer’s disease. Current Alzheimer Research, 11(3), 274282.10.2174/1567205011666140131114716CrossRefGoogle ScholarPubMed
Whitwell, J., Jones, D., Duffy, J., Strand, E., Machulda, M., Przybelski, S., Vemuri, P., Gregg, B., Gunter, J., Senjem, M., Petersen, R., Jack, C., & Josephs, K. (2015). Working memory and language network dysfunctions in logopenic aphasia: A task-free fMRI comparison with Alzheimer’s dementia. Neurobiology of Aging, 36(3), 12451252.10.1016/j.neurobiolaging.2014.12.013CrossRefGoogle ScholarPubMed
Williams, K., Numssen, O., & Hartwigsen, G. (2022). Task-specific network interactions across key cognitive domains. Cerebral Cortex, 32(22), 50505071.10.1093/cercor/bhab531CrossRefGoogle ScholarPubMed
Xu, K., Niu, N., Li, X., Chen, Y., Wang, D., Zhang, J., Chen, Y., Li, H., Wei, D., Chen, K., Cui, R., Zhang, Z., & Yao, L. (2022). The characteristics of glucose metabolism and functional connectivity in posterior default network during nondemented aging: Relationship with executive function performance. Cerebral Cortex, 33(6), 29012911.10.1093/cercor/bhac248CrossRefGoogle Scholar
Xu, X., Yuan, H., & Lei, X. (2016). Activation and connectivity within the default mode network contribute independently to future-oriented thought. Scientific Reports, 6, 21001.10.1038/srep21001CrossRefGoogle ScholarPubMed
Yeshurun, Y., Nguyen, M., & Hasson, U. (2021). The default mode network: Where the idiosyncratic self meets the shared social world. Nature Reviews Neuroscience, 22(3), 181192.10.1038/s41583-020-00420-wCrossRefGoogle ScholarPubMed
Zhang, C., Cahill, N. D., Arbabshirani, M. R., White, T., Baum, S. A., & Michael, A. M. (2016). Sex and age effects of functional connectivity in early adulthood. Brain Connectivity, 6(9), 700713.10.1089/brain.2016.0429CrossRefGoogle ScholarPubMed
Zhang, C., Xia, Y., Feng, T., Yu, K., Zhang, H., Sami, M., Xiang, J., & Xu, K. (2021). Disrupted functional connectivity within and between resting-state networks in the subacute stage of post-stroke aphasia. Frontiers in Neuroscience, 15, 746264.10.3389/fnins.2021.746264CrossRefGoogle ScholarPubMed
Zhu, D., Chang, J., Freeman, S., Tan, Z., Xiao, J., Gao, Y., & Kong, J. (2014). Changes of functional connectivity in the left frontoparietal network following aphasic stroke. Frontiers in Behavioral Neuroscience, 8, 167.10.3389/fnbeh.2014.00167CrossRefGoogle ScholarPubMed
Zhu, H., Zhou, P., Alcauter, S., Chen, Y., Cao, H., Tian, M., Ming, D., Qi, H., Wang, X., Zhao, X., He, F., Ni, H., & Gao, W. (2016). Changes of intranetwork and internetwork functional connectivity in Alzheimer’s disease and mild cognitive impairment. Journal of Neural Engineering, 13(4), 046008.10.1088/1741-2560/13/4/046008CrossRefGoogle ScholarPubMed

References

Ackerman, D. J., & Friedman-Krauss, A. H. (2017). Preschoolers’ executive function: Importance, contributors, research needs and assessment options. ETS Research Report Series, 2017(1), 124. https://doi.org/10.1002/ets2.12148CrossRefGoogle Scholar
Alarcón-Rubio, D., Sánchez-Medina, J. A., & Prieto-García, J. R. (2014). Executive function and verbal self-regulation in childhood: Developmental linkages between partially internalized private speech and cognitive flexibility. Early Childhood Research Quarterly, 29(2), 95105. https://doi.org/10.1016/j.ecresq.2013.11.002CrossRefGoogle Scholar
Alexander, M. P. (2006). Impairments of procedures for implementing complex language are due to disruption of frontal attention processes. Journal of the International Neuropsychological Society, 12(2), 236247. https://doi.org/10.1017/s1355617706060309CrossRefGoogle ScholarPubMed
Annese, J., Schenker-Ahmed, N. M., Bartsch, H., Maechler, P., Sheh, C., Thomas, N., … & Corkin, S. (2014). Postmortem examination of patient HM’s brain based on histological sectioning and digital 3D reconstruction. Nature Communications, 5(1), 3122. https://doi.org/10.1038/ncomms4122CrossRefGoogle Scholar
Archibald, L. M., & Gathercole, S. E. (2006). Short‐term and working memory in specific language impairment. International Journal of Language & Communication Disorders, 41(6), 675693. https://doi.org/10.1080/13682820500442602CrossRefGoogle ScholarPubMed
Atilgan, H., Town, S. M., Wood, K. C., Jones, G. P., Maddox, R. K., Lee, A. K., & Bizley, J. K. (2018). Integration of visual information in auditory cortex promotes auditory scene analysis through multisensory binding. Neuron, 97(3), 640655. https://doi.org/10.1016/j.neuron.2017.12.034CrossRefGoogle ScholarPubMed
Atkinson, R. C., & Shiffrin, R. M. (1968). Human memory: A proposed system and its control processes. Psychology of Learning and Motivation, 89 –195. https://doi.org/10.1016/s0079-7421(08)60422-3CrossRefGoogle Scholar
Avons, S. E., Wragg, C. A., Cupples, W. L., & Lovegrove, W. J. (1998). Measures of phonological short-term memory and their relationship to vocabulary development. Applied Psycholinguistics, 19(4), 583601. https://doi.org/10.1017/s0142716400010377CrossRefGoogle Scholar
Baddeley, A. (1992). Working memory. Science, 255(5044), 556559. https://doi.org/10.1126/science.1736359CrossRefGoogle ScholarPubMed
Baddeley, A. (2000). The episodic buffer: A new component of working memory? Trends in Cognitive Sciences, 4 (11), 417423. https://doi.org/10.1016/s1364-6613(00)01538-2CrossRefGoogle ScholarPubMed
Baddeley, A. (2003). Working memory and language: An overview. Journal of Communication Disorders, 36(3), 189208. https://doi.org/10.1016/s0021-9924(03)00019-4CrossRefGoogle ScholarPubMed
Baddeley, A. (2012). Working memory: Theories, models, and controversies. Annual Review of Psychology, 63(1), 129. https://doi.org/10.1146/annurev-psych-120710-100422CrossRefGoogle ScholarPubMed
Baddeley, A. D. (1966). Short-term memory for word sequences as a function of acoustic, semantic and formal similarity. Quarterly Journal of Experimental Psychology, 18(4), 362365. https://doi.org/10.1080/14640746608400055CrossRefGoogle ScholarPubMed
Baddeley, A. D., & Hitch, G. J. (1974). Working memory. In Bower, G. A. (Ed.), The Psychology of Learning and Motivation: Advances in Research and Theory (Vol. 8, pp. 4789). Academic Press. http://doi.org/10.1016/s0079-7421(08)60452-1Google Scholar
Baddeley, A. D., Thomson, N., & Buchanan, M. (1975). Word length and the structure of short-term memory. Journal of Verbal Learning and Verbal Behavior, 14(6), 575589. https://doi.org/10.1016/s0022-5371(75)80045-4CrossRefGoogle Scholar
Baddeley, A., & Wilson, B. (1985). Phonological coding and short-term memory in patients without speech. Journal of Memory and Language, 24(4), 490502. https://doi.org/10.1016/0749-596x(85)90041-5CrossRefGoogle Scholar
Baddeley, A., Gathercole, S., & Papagno, C. (1998). The phonological loop as a language learning device. Psychological Review, 105(1), 158173. https://doi.org/10.1037/0033-295x.105.1.158CrossRefGoogle ScholarPubMed
Banerjee, S., Snyder, A. C., Molholm, S., & Foxe, J. J. (2011). Oscillatory alpha-band mechanisms and the deployment of spatial attention to anticipated auditory and visual target locations: Supramodal or sensory-specific control mechanisms? Journal of Neuroscience, 31(27), 99239932. https://doi.org/10.1523/jneurosci.4660-10.2011CrossRefGoogle ScholarPubMed
Barry, D. N., & Maguire, E. A. (2019). Remote memory and the hippocampus: A constructive critique. Trends in Cognitive Sciences, 23(2), 128142. https://doi.org/10.1016/j.tics.2018.11.005CrossRefGoogle ScholarPubMed
Best, V., Ozmeral, E. J., & Shinn-Cunningham, B. G. (2007). Visually-guided attention enhances target identification in a complex auditory scene. Journal for the Association for Research in Otolaryngology, 8 (2), 294304. https://doi.org/10.1007/s10162-007-0073-zCrossRefGoogle Scholar
Bisaz, R., Travaglia, A., & Alberini, C. M. (2014). The neurobiological bases of memory formation: From physiological conditions to psychopathology. Psychopathology, 47(6), 347356. https://doi.org/10.1159/000363702CrossRefGoogle ScholarPubMed
Blumenfeld, R. S., & Ranganath, C. (2007). Prefrontal cortex and long-term memory encoding: An integrative review of findings from neuropsychology and neuroimaging. The Neuroscientist, 13(3), 280291. https://doi.org/10.1177/1073858407299290CrossRefGoogle ScholarPubMed
Bosse, M.-L., Tainturier, M. J., & Valdois, S. (2007). Developmental dyslexia: The visual attention span deficit hypothesis. Cognition, 104(2), 198230. https://doi.org/10.1016/j.cognition.2006.05.009CrossRefGoogle ScholarPubMed
Botvinick, M., & Braver, T. (2015). Motivation and cognitive control: From behavior to neural mechanism. Annual Review of Psychology, 66, 83113. https://doi.org/10.1146/annurev-psych-010814-015044CrossRefGoogle ScholarPubMed
Bozeat, S., Lambon Ralph, M. A., Graham, K. S., Patterson, K., Wilkin, H., Rowland, J., Rogers, T. T., & Hodges, J. R. (2003). A duck with four legs: Investigating the structure of conceptual knowledge using picture drawing in semantic dementia. Cognitive neuropsychology, 20(1), 2747. https://doi.org/10.1080/02643290244000176CrossRefGoogle ScholarPubMed
Bregman, A. S. (1990). Auditory Scene Analysis: The Perceptual Organization of Sound. The MIT Press. https://doi.org/10.7551/mitpress/1486.001.0001CrossRefGoogle Scholar
Brill-Schuetz, K., & Morgan-Short, K. (2014). The role of procedural memory in adult second langauge acquisition. Proceedings of the Annual Meeting of the Cognitive Science Society, 36(36). https://doi.org/10.1037/e502412013–500Google Scholar
Broadbent, D. E. (1952). Failures of attention in selective listening. Journal of Experimental Psychology, 44(6), 428433. https://doi.org/10.1037/h0057163CrossRefGoogle ScholarPubMed
Brod, G., Werkle-Bergner, M., & Shing, Y. L. (2013). The influence of prior knowledge on memory: A developmental cognitive neuroscience perspective. Frontiers in Behavioral Neuroscience, 7, 139. https://doi.org/10.3389/fnbeh.2013.00139CrossRefGoogle ScholarPubMed
Brown, G. J., Ferry, R. T., & Meddis, R. (2010). A computer model of auditory efferent suppression: Implications for the recognition of speech in noise. The Journal of the Acoustical Society of America, 127(2), 943954. https://doi.org/10.1121/1.3273893CrossRefGoogle ScholarPubMed
Buckner, R. L. (2002). Frontally mediated control processes contribute to source memory retrieval. Neuron, 35(5), 817818. https://doi.org/10.1016/s0896-6273(02)00866-8CrossRefGoogle ScholarPubMed
Cabeza, R., & Moscovitch, M. (2013). Memory systems, processing modes, and components: Functional neuroimaging evidence. Perspectives on Psychological Science, 8(1), 4955. https://doi.org/10.1177/1745691612469033CrossRefGoogle ScholarPubMed
Cain, K., Oakhill, J., & Bryant, P. (2004). Children’s reading comprehension ability: Concurrent prediction by working memory, verbal ability, and component skills. Journal of Educational Psychology, 96(1), 3142. https://doi.org/10.1037/0022-0663.96.1.31CrossRefGoogle Scholar
Caplan, D., & Waters, G. S. (1999). Verbal working memory and sentence comprehension. Behavioral and Brain Sciences, 22, 77126. https://doi.org/10.1017/S0140525X99001788CrossRefGoogle ScholarPubMed
Chavez-Arana, C., Catroppa, C., Carranza-Escarcega, E., Godfrey, C., Yanez-Tellez, G., Prieto-Corona, B., … Anderson, V. (2018). A systematic review of interventions for hot and cold executive functions in children and adolescents with acquired brain injury. Journal of Pediatric Psychology, 43(8), 928942. https://doi.org/10.1093/jpepsy/jsy013CrossRefGoogle ScholarPubMed
Cherry, E.C. (1953) Some experiments on the recognition of speech, with one and with two ears. Journal of the Acoustical Society of America, 25, 974979. http://dx.doi.org/10.1121/1.1907229CrossRefGoogle Scholar
Cheung, H. (1996). Nonword span as a unique predictor or second-language vocabulary language. Developmental Psychology, 32(5), 867. https://doi.org/10.1037/0012-1649.32.5.867CrossRefGoogle Scholar
Chiou, H. S., & Kennedy, M. R. T. (2009). Switching in adults with aphasia. Aphasiology, 23(7–8), 10651075. https://doi.org/10.1080/02687030802642028CrossRefGoogle Scholar
Choinski, M., Szelag, E., Wolak, T., & Szymaszek, A. (2020). Working memory in aphasia: The role of temporal information processing. Frontiers in Human Neuroscience, 14. https://doi.org/10.3389/fnhum.2020.589802CrossRefGoogle ScholarPubMed
Ciaramelli, E., Burioanová, H., Vallesi, A., Cabeza, R., & Moscovitch, M. (2020). Funcitonal interplay between posterior parietal cortex and hippocampus durign detection of memory targets and non-targets. Frontiers in Neuroscience, 14. https://doi.org/10.3389/fnins.2020.563768CrossRefGoogle Scholar
Coelho, C. A. (2007). Management of discourse deficits following traumatic brain injury: Progress, caveats, and needs. Seminars in Speech and Language, 28(2), 122135. https://doi.org/10.1055/s-2007-970570CrossRefGoogle ScholarPubMed
Conrad, R., & Hull, A. J. (1964). Information, acoustic confusion and memory span. British Journal of Psychology, 55(4), 429432. https://doi.org/10.1111/j.2044-8295.1964.tb00928.xCrossRefGoogle ScholarPubMed
Conti-Ramsden, G., Ullman, M. T., & Lum, J. A. (2015). The relation between receptive grammar and procedural, declarative, and working memory in specific language impairment. Frontiers in Psychology, 6, 1090. https://doi.org/10.3389/fpsyg.2015.01090CrossRefGoogle ScholarPubMed
Conway, A. R. A., Kane, M. J., Bunting, M. F., Hambrick, D. Z., Wilhelm, O., & Engle, R. W. (2005). Working memory span tasks: A methodological review and user’s guide. Psychonomic Bulletin & Review, 12(5), 769786. https://doi.org/10.3758/bf03196772CrossRefGoogle ScholarPubMed
Corbetta, M., & Shulman, G. L. (2002). Control of goal-directed and stimulus-driven attention in the brain. Nature Reviews Neuroscience, 3(3), 201215. https://doi.org/10.1038/nrn755CrossRefGoogle ScholarPubMed
Corkin, S. (1968). Acquisition of motor skill after bilateral medial temporal-lobe excision. Neuropsychologia. 6(3), 255265.10.1016/0028-3932(68)90024-9CrossRefGoogle Scholar
Covington, M. A., He, C., Brown, C., Naçi, L., McClain, J. T., Fjordbak, B. S., Semple, J., & Brown, J. (2005). Schizophrenia and the structure of language: The linguist’s view. Schizophrenia Research, 77(1), 8598. https://doi.org/10.1016/j.schres.2005.01.016CrossRefGoogle ScholarPubMed
Cowan, N. (2008). What are the differences between long-term, short-term, and working memory?. In Sossin, W. S., Lacaille, J.-C., Castellucci, V. F., & Belleville, S. (Eds.), Progress in Brain Research (Vol. 169, pp. 323338). Elsevier. https://doi.org/10.1016/S0079-6123(07)00020-9Google Scholar
Daneman, M., & Carpenter, P. A. (1980). Individual differences in working memory and reading. Journal of Verbal Learning & Verbal Behavior, 19(4), 450466. https://doi.org/10.1016/S0022-5371(80)90312-6CrossRefGoogle Scholar
Datta, R., & DeYoe, E. A. (2009). I know where you are secretly attending! The topography of human visual attention revealed with fMRI. Vision Research, 49(10), 10371044. https://10.1016/j.visres.2009.01.01410.1016/j.visres.2009.01.014CrossRefGoogle ScholarPubMed
Davachi, L., & Dobbins, I. G. (2008). Declarative memory. Current Directions in Psychological Science, 17(2), 112118. https://doi.org/10.1111/j.1467-8721.2008.00559.xCrossRefGoogle ScholarPubMed
de Abreu, P. M. J. E., Gathercole, S. E., & Martin, R. (2011). Disentangling the relationship between working memory and language: The roles of short-term storage and cognitive control. Learning and Individual Differences, 21(5), 569574. https://doi.org/10.1016/j.lindif.2011.06.002CrossRefGoogle Scholar
DeDe, G., Ricca, M., Knilans, J., & Trubl, B. (2014). Construct validity and reliability of working memory tasks for people with aphasia. Aphasiology, 28(6), 692712. https://doi.org/10.1080/02687038.2014.895973CrossRefGoogle Scholar
Dew, I. T. Z., & Cabeza, R. (2011). The porous boundaries between explicit and implicit memory: Behavioral and neural evidence. Annals of the New York Academy of Sciences, 1224(1), 174190. https://doi.org/10.1111/j.1749-6632.2010.05946.xCrossRefGoogle ScholarPubMed
Diamond, A. (2013). Executive functions. Annual Review of Psychology, 64(1), 135168. https://doi.org/10.1146/annurev-psych-113011-143750CrossRefGoogle ScholarPubMed
Dickerson, B. C., & Eichenbaum, H. (2010). The episodic memory system: Neurocircuitry and disorders. Neuropsychopharmacology, 35(1), 86104. https://doi.org/10.1038/npp.2009.126CrossRefGoogle ScholarPubMed
Dudai, Y., & Morris, R. G. (2013). Memorable trends. Neuron, 80(3), 742750. https://doi.org/10.1016/j.neuron.2013.09.039CrossRefGoogle ScholarPubMed
Durlach, N. I., Mason, C. R., Kidd, G. Jr., Arbogast, T. L., Colburn, H. S., & Shinn-Cunningham, B. G. (2003). Note on informational masking (L). The Journal of the Acoustical Society of America, 113(6), 29842987. https://doi.org/10.1121/1.1570435CrossRefGoogle Scholar
Ebert, K. D., & Kohnert, K. (2011). Sustained attention in children with primary language impairment: A meta-analysis. Journal of Speech, Language, and Hearing Research, 54(5), 13721384. https://doi.org/10.1044/1092-4388(2011/10-0231)CrossRefGoogle ScholarPubMed
Eichenbaum, H. (2001). The hippocampus and declarative memory: Cognitive mechanisms and neural codes. Behavioral Brain Research, 127(1–2), 199207. https://doi.org/10.1016/s0166-4328(01)00365-5CrossRefGoogle ScholarPubMed
El Hachioui, H., Visch-Brink, E. G., Lingsma, H. F., van de Sandt-Koenderman, M. W., Dippel, D. W., Koudstaal, P. J., & Middelkoop, H. A. (2014). Nonlinguistic cognitive impairment in poststroke aphasia. Neurorehabilitation and Neural Repair, 28(3), 273281. https://doi.org/10.1177/1545968313508467CrossRefGoogle ScholarPubMed
Engle, R. W. (2002). Working memory capacity as executive attention. Current Directions in Psychological Science, 11(1), 1923. https://doi.org/10.1111/1467-8721.00160CrossRefGoogle Scholar
Engle, R. W., Tuholski, S. W., Laughlin, J. E., & Conway, A. R. (1999). Working memory, short-term memory, and general fluid intelligence: A latent-variable approach. Journal of Experimental Psychology: General, 128(3), 309331. https://doi.org/10.1037/0096-3445.128.3.309CrossRefGoogle ScholarPubMed
Estes, K. G., Evans, J. L., & Else-Quest, N. M. (2007). Differences in the nonword repetition performance of children with and without specific language impairment: A meta-analysis. Journal of Speech, Language, and Hearing Research, 50, 177195. https://doi.org/10.1044/1092-4388(2007/015)CrossRefGoogle Scholar
Ettlinger, M., Bradlow, A. R., & Wong, P. C. (2014). Variability in the learning of complex morphophonology. Applied Psycholinguistics, 35(4), 807831. https://doi.org/10.1017/S0142716412000586CrossRefGoogle Scholar
Fahy, J. K. (2014). Language and executive functions: Self-talk for self-regulation. Perspectives on Language Learning and Education, 21(2), 6171. https://doi.org/10.1044/lle21.2.61CrossRefGoogle Scholar
Failing, M., & Theeuwes, J. (2018). Selection history: How reward modulates selectivity of visual attention. Psychonomic Bulletin & Review, 25(2), 514538. https://doi.org/10.3758/s13423-017-1380-yCrossRefGoogle ScholarPubMed
Fallon, M., Peelle, J. E., & Wingfield, A. (2006). Spoken sentence processing in young and older adults modulated by task demands: Evidence from self-paced listening. The Journals of Gerontology. Series B, Psychological Sciences and Social Sciences, 61, P10–7. https://doi.org/10.1093/Geronb/61.1.P10Google Scholar
Fatzer, S. T., & Roebers, C. M. (2012). Language and executive functions: The effect of articulatory suppression on executive functioning in children. Journal of Cognition and Development, 13(4), 454472. https://doi.org/10.1080/15248372.2011.608322CrossRefGoogle Scholar
Fernández, G. (2017). The medial prefrontal cortex is a critical hub in the declarative memory system. In Axmacher, N. & Rasch, B. (Eds.), Cognitive Neuroscience of Memory Consolidation (pp. 4556). Springer. https://doi.org/10.1007/978-3-319-45066-7_3CrossRefGoogle Scholar
Foster, J. J., & Awh, E. (2019). The role of alpha oscillations in spatial attention: Limited evidence for a suppression account. Current Opinion in Psychology, 29, 3440. https://doi.org/10.1016/j.copsyc.2018.11.001CrossRefGoogle ScholarPubMed
Foster, J. L., Shipstead, Z., Harrison, T. L., Hicks, K. L., Redick, T. S., & Engle, R. W. (2014). Shortened complex span tasks can reliably measure working memory capacity. Memory & Cognition, 43(2), 226236. https://doi.org/10.3758/s13421-014-0461-7CrossRefGoogle Scholar
Frankland, P. W., Josselyn, S. A., & Köhler, S. (2019). The neurobiological foundation of memory retrieval. Nature neuroscience, 22(10), 15761585. https://doi.org/10.1038/s41593-019-0493-1CrossRefGoogle ScholarPubMed
Fridriksson, J., Nettles, C., Davis, M., Morrow, L., & Montgomery, A. (2006). Functional communication and executive function in aphasia. Clinical Linguistics & Phonetics, 20(6), 401410. https://doi.org/10.1080/02699200500075781CrossRefGoogle ScholarPubMed
Friedman, N. P., & Robbins, T. W. (2021). The role of the prefrontal cortex in cognitive control and executive function. Neuropsychopharmacology, 47(1), 7289. https://doi.org/10.1038/s41386-021-01132-0CrossRefGoogle ScholarPubMed
Friedman, N. P., Miyake, A., Altamirano, L. J., Corley, R. P., Young, S. E., Rhea, S. A., & Hewitt, J. K. (2016). Stability and change in executive function abilities from late adolescence to early adulthood: A longitudinal twin study. Developmental Psychology, 52(2), 326340. https://doi.org/10.1037/dev0000075CrossRefGoogle ScholarPubMed
Friedman, N. P., Miyake, A., Robinson, J. L., & Hewitt, J. K. (2011). Developmental trajectories in toddlers’ self-restraint predict individual differences in executive functions 14 years later: A behavioral genetic analysis. Developmental Psychology, 47(5), 14101430. https://doi.org/10.1037/a0023750CrossRefGoogle Scholar
Friedman, N. P., Miyake, A., Young, S. E., DeFries, J. C., Corley, R. P., & Hewitt, J. K. (2008). Individual differences in executive functions are almost entirely genetic in origin. Journal of Experimental Psychology: General, 137(2), 201225. https://doi.org/10.1037/0096-3445.137.2.201CrossRefGoogle ScholarPubMed
Fritz, J. B., Elhilali, M., David, S. V., & Shamma, S. A. (2007). Auditory attention: Focusing the searchlight on sound. Current Opinion in Neurobiology, 17(4), 437455. https://doi.org/10.1016/j.conb.2007.07.011CrossRefGoogle ScholarPubMed
Fuhs, M. W., & Day, J. D. (2011). Verbal ability and executive functioning development in preschoolers at head start. Developmental Psychology, 47(2), 404416. https://doi.org/10.1037/a0021065CrossRefGoogle ScholarPubMed
Garon, N., Bryson, S. E., & Smith, I. M. (2008). Executive function in preschoolers: A review using an integrative framework. Psychological Bulletin, 134(1), 3160. https://doi.org/10.1037/0033-2909.134.1.31CrossRefGoogle ScholarPubMed
Gathercole, S. E. (2006). Complexities and constraints in nonword repetition and word learning. Applied Psycholinguistics, 27(4), 599613. https://doi.org/10.1017/S014271640606053XCrossRefGoogle Scholar
Gathercole, S. E., Alloway, T. P., Willis, C., & Adams, A.-M. (2006). Working memory in children with reading disabilities. Journal of Experimental Child Psychology, 93(3), 265281. https://doi.org/10.1016/j.jecp.2005.08.003CrossRefGoogle ScholarPubMed
Gathercole, S. E., Hitch, G. J., Service, E., & Martin, A. J. (1997). Phonological short-term memory and new word learning in children. Developmental Psychology, 33(6), 966979. https://doi.org/10.1037/0012-1649.33.6.966CrossRefGoogle ScholarPubMed
Gathercole, S. E., & Masoura, E. V. (2005). Contrasting contributions of phonological short‐term memory and long‐term knowledge to vocabulary learning in a foreign language. Memory, 13(3–4), 422429. https://doi.org/10.1080/09658210344000323CrossRefGoogle Scholar
Gherri, E., & Eimer, M. (2011). Active listening impairs visual perception and selectivity: An ERP study of auditory dual-task costs on visual attention. Journal of Cognitive Neuroscience, 23(4), 832844. https://doi.org/10.1162/jocn.2010.21468CrossRefGoogle ScholarPubMed
Gordon, J. K., & Dell, G. S. (2003). Learning to divide the labor: An account of deficits in light and heavy verb production. Cognitive Science, 27(1), 140. https://doi.org/10.1207/s15516709cog2701_1CrossRefGoogle Scholar
Graf Estes, K., Evans, J. L., & Else-Quest, N. M. (2007). Differences in the nonword repetition performance of children with and without specific language impairment: A meta-analysis. Journal of Speech, Language, and Hearing Research, 50(1), 177195. https://doi.org/10.1044/1092-4388(2007/015)CrossRefGoogle ScholarPubMed
Graf, P., & Schacter, D. L. (1985). Implicit and explicit memory for new associations in normal and amnesic subjects. Journal of Experimental Psychology: Learning, Memory, and Cognition, 11(3), 501518. https://doi.org/10.1037/0278-7393.11.3.501Google ScholarPubMed
Gray, S. I., Levy, R., Alt, M., Hogan, T. P., & Cowan, N. (2022). Working memory predicts new word learning over and above existing vocabulary and nonverbal IQ. Journal of Speech, Language, and Hearing Research, 65(3), 10441069. https://doi.org/10.1044/2021_jslhr-21-00397CrossRefGoogle ScholarPubMed
Green, J. J., Doesburg, S. M., Ward, L. M., & McDonald, J. J. (2011). Electrical neuroimaging of voluntary audio spatial attention: Evidence for a supramodal attention control network. Journal of Neuroscience, 31(10), 35603564. https://doi.org/10.1523/jneurosci.5758-10.2011CrossRefGoogle Scholar
Green, J. J., Teder-Sälejärvi, W. A., & McDonald, J. J. (2005). Control mechanisms mediating shifts of attention in auditory and visual space: A spatio-temporal ERP analysis. Experimental Brain Research, 166(3), 358369. https://doi.org/10.1007/s00221-005-2377-8CrossRefGoogle ScholarPubMed
Händel, B. F., Haarmeier, T., & Jensen, O. (2011). Alpha oscillations correlate with the successful inhibition of unattended stimuli. Journal of Cognitive Neuroscience, 23(9), 2494-2502. https://doi.org/10.1162/jocn.2010.21557CrossRefGoogle ScholarPubMed
Helm-Estabrooks, N. (2002). Cognition and aphasia: A discussion and a study. Journal of Communication Disorders, 35(2), 171186. https://doi.org/10.1016/s0021-9924(02)00063-1CrossRefGoogle ScholarPubMed
Henson, R. N. A., Burgess, N., & Frith, C. D. (2000). Recoding, storage, rehearsal and grouping in verbal short-term memory: An fMRI study. Neuropsychologia, 38(4), 426440. https://doi.org/10.1016/s0028-3932(99)00098-6CrossRefGoogle ScholarPubMed
Hodges, J. R., & Graham, K. S. (2001). Episodic memory: Insights from semantic dementia. Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences, 356(1413), 14231434. https://doi.org/10.1098/rstb.2001.0943CrossRefGoogle ScholarPubMed
Hodges, J. R., & Patterson, K. (2007). The neuropsychology of frontotemporal dementia. Frontotemporal Dementia Syndromes, 35(102–133), 2036. https://doi.org/10.1017/cbo9781316135457.006Google Scholar
Howland, K. (2014). Developing executive control skills in preschool children with language impairment. Perspectives on Language Learning and Education, 21(2), 5160. https://doi.org/10.1044/lle21.2.51CrossRefGoogle Scholar
Hughes, C., Ensor, R., Wilson, A., & Graham, A. (2010). Tracking executive function across the transition to school: A latent variable approach. Developmental Neuropsychology, 35(1), 2036. https://doi.org/10.1080/87565640903325691CrossRefGoogle Scholar
Hughes, R. W., & Marsh, J. E. (2017). The functional determinants of short-term memory: Evidence from perceptual-motor interference in verbal serial recall. Journal of Experimental Psychology: Learning, Memory, and Cognition, 43(4), 537551. https://doi.org/10.1037/xlm0000325Google ScholarPubMed
Hula, W. D., & McNeil, M. R. (2008). Models of attention and dual-task performance as explanatory constructs in aphasia. Seminars in Speech and Language, 29(3), 169187. https://doi.org/10.1055/s-0028-1082882CrossRefGoogle ScholarPubMed
Humphreys, G. W., & Forde, E. M. (2001). Hierarchies, similarity, and interactivity in object recognition: “Category-specific” neuropsychological deficits. Behavioral and Brain Sciences, 24(3), 453509. https://doi.org/10.1017/s0140525x01004150CrossRefGoogle ScholarPubMed
Humphreys, G. W., Price, C. J., & Riddoch, M. J. (1999). From objects to names: A cognitive neuroscience approach. Psychological Research, 62(2–3), 118130. https://doi.org/10.1007/s004260050046CrossRefGoogle Scholar
Hunt, R. R., & McDaniel, M. A. (1993). The enigma of organization and distinctiveness. Journal of Memory and Language, 32(4), 421445. https://doi.org/10.1006/jmla.1993.1023CrossRefGoogle Scholar
Hurlstone, M. J., & Hitch, G. J. (2018). How is the serial order of a visual sequence represented? Insights from transposition latencies. Journal of Experimental Psychology: Learning, Memory, and Cognition, 44(2), 167192. https://doi.org/10.1037/xlm0000440Google Scholar
Hurlstone, M. J., Hitch, G. J., & Baddeley, A. D. (2014). Memory for serial order across domains: An overview of the literature and directions for future research. Psychological Bulletin, 140(2), 339373. https://doi.org/10.1037/a0034221CrossRefGoogle ScholarPubMed
Itti, L., & Koch, C. (2001). Computational modeling of visual attention. Nature Reviews Neuroscience, 2(3), 194203. https://doi.org/10.1038/35058500CrossRefGoogle ScholarPubMed
Jarrold, C., Thorn, A. S. C., & Stephens, E. (2009). The relationships among verbal short-term memory, phonological awareness, and new word learning: Evidence from typical development and Down syndrome. Journal of Experimental Child Psychology, 102(2), 196218. https://doi.org/10.1016/j.jecp.2008.07.001CrossRefGoogle ScholarPubMed
Javadi, A. H., & Walsh, V. (2012). Transcranial direct current stimulation (tDCS) of the left dorsolateral the prefrontal cortex modulates declarative memory. Brain Stimulation, 5(3), 231241. https://doi.org/10.1016/j.brs.2011.06.007CrossRefGoogle ScholarPubMed
Jensen, O., Bonnefond, M., & VanRullen, R. (2012). An oscillatory mechanism for prioritizing salient unattended stimuli. Trends in Cognitive Sciences, 16(4), 200206. https://doi.org/10.1016/j.tics.2012.03.002CrossRefGoogle ScholarPubMed
Joanisse, M. F., & Seidenberg, M. S. (1999). Impairments in verb morphology after brain injury: A connectionist model. Proceedings of the National Academy of Sciences, 96(13), 75927597. https://doi.org/10.1073/pnas.96.13.7592CrossRefGoogle ScholarPubMed
Jones, S. M., Bailey, R., Barnes, S. P., & Partee, A. (2016). Executive function mapping project: Untangling the terms and skills related to executive function and self-regulation in early childhood. OPRE Report # 2016-88, Office of Planning, Research and Evaluation, Administration for Children and Families, U.S. Department of Health and Human Services. www.acf.hhs.gov/sites/default/files/documents/opre/efmapping_report_101416_final_508.pdfGoogle Scholar
Jonker, T. R., Seli, P., & MacLeod, C. M. (2015). Retrieval-induced forgetting and context. Current Directions in Psychological Science, 24(4), 273278. https://doi.org/10.1177/0963721415573203CrossRefGoogle Scholar
Just, M. A., & Carpenter, P. A. (1992). A capacity theory of comprehension: Individual differences in working memory. Psychological Review, 99(1), 122149. https://doi.org/10.1037/0033-295x.99.1.122CrossRefGoogle ScholarPubMed
Kahneman, D. (1973). Attention and Effort (Vol. 1063). Prentice-Hall.Google Scholar
Kane, M. J., Hambrick, D. Z., Tuholski, S. W., Wilhelm, O., Payne, T. W., & Engle, R. W. (2004). The generality of working memory capacity: A latent-variable approach to verbal and visuospatial memory span and reasoning. Journal of Experimental Psychology: General, 133(2), 189217. https://doi.org/10.1037/0096-3445.133.2.189CrossRefGoogle ScholarPubMed
Kapa, L. L., & Erikson, J. A. (2020). The relationship between word learning and executive function in preschoolers with and without developmental language disorder. Journal of Speech, Language, and Hearing Research, 63(7), 22932307. https://doi.org/10.1044/2020_jslhr-19-00342CrossRefGoogle ScholarPubMed
Kapa, L. L., & Plante, E. (2015). Executive function in SLI: Recent advances and future directions. Current Developmental Disorders Reports, 2(3), 245252. https://doi.org/10.1007/s40474–015-0050-xCrossRefGoogle ScholarPubMed
Karr, J. E., Areshenkoff, C. N., Rast, P., Hofer, S. M., Iverson, G. L., & Garcia-Barrera, M. A. (2018). The unity and diversity of executive functions: A systematic review and re-analysis of latent variable studies. Psychological Bulletin, 144(11), 11471185. https://doi.org/10.1037/bul0000160CrossRefGoogle ScholarPubMed
Kaushanskaya, M., Park, J. S., Gangopadhyay, I., Davidson, M. M., & Weismer, S. E. (2017). The relationship between executive functions and language abilities in children: A latent variable approach. Journal of Speech, Language, and Hearing Research, 60(4), 912923. https://doi.org/10.1044/2016_jslhr-l-15-0310CrossRefGoogle Scholar
Kelly, S. P., Lalor, E. C., Reilly, R. B., & Foxe, J. J. (2006). Increases in alpha oscillatory power reflect an active retinotopic mechanism for distracter suppression during sustained visuospatial attention. Journal of Neurophysiology, 95(6), 38443851. https://doi.org/10.1152/jn.01234.2005CrossRefGoogle ScholarPubMed
Kempe, V., Brooks, P. J., & Kharkhurin, A. (2010). Cognitive predictors of generalization of Russian grammatical gender categories. Language Learning, 60(1), 127153. https://doi.org/10.1111/j.1467-9922.2009.00553.xCrossRefGoogle Scholar
Kennedy, M. R. T., & Coelho, C. (2005). Self-regulation after traumatic brain injury: A framework for intervention of memory and problem solving. Seminars in Speech and Language, 26(04), 242255. https://doi.org/10.1055/s-2005-922103CrossRefGoogle ScholarPubMed
Kidd, G. Jr., (2017). Enhancing auditory selective attention using a visually guided hearing aid. Journal of Speech, Language, and Hearing Research, 60(10), 30273038. https://doi.org/10.1044/2017_jslhr-h-17-0071CrossRefGoogle ScholarPubMed
Kidd, G. Jr., & Colburn, H. S. (2017). Informational masking in speech recognition. In Middlebrooks, J. C., Simon, J. Z., Popper, A. N., & Fay, R. R. (Eds.), The Auditory System at the Cocktail Party (pp. 75109). Springer.10.1007/978-3-319-51662-2_4CrossRefGoogle Scholar
Kidd, G. Jr., Favrot, S., Desloge, J. G., Streeter, T. M., & Mason, C. R. (2013). Design and preliminary testing of a visually guided hearing aid. The Journal of the Acoustical Society of America, 133(3), EL202EL207. https://doi.org/10.1121/1.4791710CrossRefGoogle ScholarPubMed
Kidd, G. Jr., Jennings, T. R., & Byrne, A. J. (2020). Enhancing the perceptual segregation and localization of sound sources with a triple beamformer. The Journal of the Acoustical Society of America, 148(6), 35983611. https://doi.org/10.1121/10.0002779CrossRefGoogle ScholarPubMed
Kidd, G. Jr., Mason, C. R., Swaminathan, J., Roverud, E., Clayton, K. K., & Best, V. (2016). Determining the energetic and informational components of speech-on-speech masking. The Journal of the Acoustical Society of America, 140(1), 132-144. https://doi.org/10.1121/1.4954748CrossRefGoogle ScholarPubMed
Kim, W. B., & Cho, J.-H. (2020). Encoding of contextual fear memory in hippocampal–amygdala circuit. Nature Communications, 11(1), 122. https://doi.org/10.1038/s41467-020-15121-2Google ScholarPubMed
Kintsch, W., Patel, V. L., & Ericsson, K. A. (1999). The role of long-term working memory in text comprehension. Psychologia, 42(4), 186198.Google Scholar
Kirchner, W. K. (1958). Age differences in short-term retention of rapidly changing information. Journal of Experimental Psychology, 55(4), 352358. https://doi.org/10.1037/h0043688CrossRefGoogle ScholarPubMed
Kirkham, N. Z., Cruess, L., & Diamond, A. (2003). Helping children apply their knowledge to their behavior on a dimension-switching task. Developmental Science, 6(5), 449467. https://doi.org/10.1111/1467-7687.00300CrossRefGoogle Scholar
Klatte, M., Lee, N., & Hellbruck, J. (2002). Effects of irrelevant speech and articulatory suppression on serial recall of heard and read materials. Psychologische Beiträge, 44(2), 166186.Google Scholar
Klauer, K. C., & Zhao, Z. (2004). Double dissociations in visual and spatial short-term memory. Journal of Experimental Psychology: General, 133(3), 355381. https://doi.org/10.1037/0096-3445.133.3.355CrossRefGoogle ScholarPubMed
Klimesch, W. (2012). Alpha-band oscillations, attention, and controlled access to stored information. Trends in Cognitive Sciences, 16(12), 606617. https://doi.org/10.1016/j.tics.2012.10.007CrossRefGoogle ScholarPubMed
Kuhn, L. J., Willoughby, M. T., Vernon-Feagans, L., Blair, C. B., & The Family Life Project Key Investigators. (2016). The contribution of children’s time-specific and longitudinal expressive language skills on developmental trajectories of executive function. Journal of Experimental Child Psychology, 148, 2034. https://doi.org/10.1016/j.jecp.2016.03.008CrossRefGoogle ScholarPubMed
Kuperberg, G. R., Kreher, D. A., & Ditman, T. (2010). What can event-related potentials tell us about language, and perhaps even thought, in schizophrenia? International Journal of Psychophysiology, 75(2), 6676. https://doi.org/10.1016/j.ijpsycho.2009.09.005CrossRefGoogle ScholarPubMed
Lang, C. J., & Quitz, A. (2012). Verbal and nonverbal memory impairment in aphasia. Journal of Neurology, 259(8), 16551661. https://doi.org/10.1007/s00415-011-6394-1CrossRefGoogle ScholarPubMed
LeDoux, J. E. (2014). Coming to terms with fear. Proceedings of the National Academy of Sciences, 111(8), 28712878. https://doi.org/10.1073/pnas.1400335111CrossRefGoogle ScholarPubMed
Levine, B., Dawson, D., Boutet, I., Schwartz, M. L., & Stuss, D. T. (2000). Assessment of strategic self-regulation in traumatic brain injury: Its relationship to injury severity and psychosocial outcome. Neuropsychology, 14(4), 491500. https://doi.org/10.1037/0894-4105.14.4.491CrossRefGoogle ScholarPubMed
Lidstone, J. S. M., Meins, E., & Fernyhough, C. (2010). The roles of private speech and inner speech in planning during middle childhood: Evidence from a dual task paradigm. Journal of Experimental Child Psychology, 107(4), 438451. https://doi.org/10.1016/j.jecp.2010.06.002CrossRefGoogle ScholarPubMed
Liew, J. (2011). Effortful control, executive functions, and education: Bringing self-regulatory and social-emotional competencies to the table. Child Development Perspectives, 6(2), 105111. https://doi.org/10.1111/j.1750-8606.2011.00196.xCrossRefGoogle Scholar
Logue, S. F., & Gould, T. J. (2014). The neural and genetic basis of executive function: Attention, cognitive flexibility, and response inhibition. Pharmacology Biochemistry and Behavior, 123, 4554. https://doi.org/10.1016/j.pbb.2013.08.007CrossRefGoogle ScholarPubMed
Lu, K., Xu, Y., Yin, P., Oxenham, A. J., Fritz, J. B., & Shamma, S. A. (2017). Temporal coherence structure rapidly shapes neuronal interactions. Nature Communications, 8(1), 112. https://doi.org/10.1038/ncomms13900CrossRefGoogle ScholarPubMed
Maddox, R. K., Atilgan, H., Bizley, J. K., & Lee, A. K. (2015). Auditory selective attention is enhanced by a task-irrelevant temporally coherent visual stimulus in human listeners. eLife, 4. https://doi.org/10.7554/elife.04995CrossRefGoogle ScholarPubMed
Mädebach, A., Jescheniak, J. D., Oppermann, F., & Schriefers, H. (2011). Ease of processing constrains the activation flow in the conceptual-lexical system during speech planning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 37(3), 649660. https://doi.org/10.1037/a0022330Google ScholarPubMed
Majerus, S. (2019). Verbal working memory and the phonological buffer: The question of serial order. Cortex, 112, 122133. https://doi.org/10.1016/j.cortex.2018.04.016CrossRefGoogle ScholarPubMed
Majerus, S., Poncelet, M., Grefee, C., & Van der Linden, M. (2006). Relations between vocabulary development and verbal short-term memory for serial order and item information. Journal of Experimental Child Psychology, 93(2), 95119. https://doi.org/10.1016/j.jecp.2005.07.005CrossRefGoogle ScholarPubMed
Martella, D., Casagrande, M., & Lupiáñez, J. (2011). Alerting, orienting and executive control: The effects of sleep deprivation on attentional networks. Experimental Brain Research, 210(1), 8189. https://doi.org/10.1007/s00221-011-2605-3CrossRefGoogle ScholarPubMed
Martin, K. I., & Ellis, N. C. (2012). The roles of phonological short-term memory and working memory in L2 grammar and vocabulary learning. Studies in Second Language Acquisition, 34(3), 379413. https://doi.org/10.1017/S0272263112000125CrossRefGoogle Scholar
Martin, N., Kohen, F., Kalinyak-Fliszar, M., Soveri, A., & Laine, M. (2012). Effects of working memory load on processing of sounds and meanings of words in aphasia. Aphasiology, 26(3–4), 462493. https://doi.org/10.1080/02687038.2011.619516CrossRefGoogle ScholarPubMed
Martin, R. C. (2021). The critical role of semantic working memory in language comprehension and production. Current Directions in Psychological Science, 30(4), 283291. https://doi.org/10.1177/0963721421995178CrossRefGoogle ScholarPubMed
McDermott, K. B., & Roediger, H. L. (2018). Memory (encoding, storage, retrieval). In Biswas-Diener, R. & Diener, E. (Eds.), General Psychology FA18 (pp. 117140). Noba Project.Google Scholar
McGaugh, J. L., Cahill, L., & Roozendaal, B. (1996). Involvement of the amygdala in memory storage: Interaction with other brain systems. Proceedings of the National Academy of Sciences, 93(24), 1350813514. https://doi.org/10.1073/pnas.93.24.13508CrossRefGoogle ScholarPubMed
Melton, A. W. (1963). Implications of short-term memory for a general theory of memory. Journal of Verbal Learning and Verbal Behavior, 2(1), 121. https://doi.org/10.1016/s0022-5371(63)80063-8CrossRefGoogle Scholar
Meneghetti, C., De Beni, R., Pazzaglia, F., & Gyselinck, V. (2011). The role of visuo-spatial abilities in recall of spatial descriptions: A mediation model. Learning and Individual Differences, 21(6), 719723. https://doi.org/10.1016/j.lindif.2011.07.015CrossRefGoogle Scholar
Menon, V., & D’Esposito, M. (2022). The role of PFC networks in cognitive control and executive function. Neuropsychopharmacology, 47(1), 90103. https://doi.org/10.1038/s41386-021-01152-wCrossRefGoogle ScholarPubMed
Mesgarani, N., Fritz, J., & Shamma, S. (2010). A computational model of rapid task-related plasticity of auditory cortical receptive fields. Journal of Computational Neuroscience, 28(1), 1927. https://doi.org/10.1007/s10827-009-0181-3CrossRefGoogle ScholarPubMed
Metcalfe, J., & Mischel, W. (1999). A hot/cool-system analysis of delay of gratification: Dynamics of willpower. Psychological Review, 106(1), 319. https://doi.org/10.1037/0033-295X.106.1.3CrossRefGoogle ScholarPubMed
Miller, E. K. (2013). The “working” of working memory. Dialogues in Clinical Neuroscience, 15(4), 411418. https://doi.org/10.31887/dcns.2013.15.4/emillerCrossRefGoogle Scholar
Miller, E. K., & Cohen, J. D. (2001). An integrative theory of prefrontal cortex function. Annual Review of Neuroscience, 24(1), 167202. https://doi.org/10.1146/annurev.neuro.24.1.167CrossRefGoogle ScholarPubMed
Miller, E. K., Lundqvist, M., & Bastos, A. M. (2018). Working memory 2.0. Neuron, 100(2), 463475. https://doi.org/10.1016/j.neuron.2018.09.023CrossRefGoogle ScholarPubMed
Miller, S., McCulloch, S., & Jarrold, C. (2015). The development of memory maintenance strategies: Training cumulative rehearsal and interactive imagery in children aged between 5 and 9. Frontiers in Psychology, 6, 110. https://doi.org/10.3389/fpsyg.2015.00524CrossRefGoogle ScholarPubMed
Milner, B., Corkin, S., & Teuber, H. L. (1968). Further analysis of the hippocampal amnesic syndrome: A 14-year follow-up study of H.M. Neuropsychologia, 6(3), 215234. https://doi.org/10.1016/0028-3932(68)90021-3CrossRefGoogle Scholar
Milner, B., Squire, L. R., & Kandel, E. R. (1998). Cognitive neuroscience and the study of memory. Neuron, 20(3), 445468. https://doi.org/10.1016/s0896–6273(00)80987-3CrossRefGoogle Scholar
Mirsky, A. F., Anthony, B. J., Duncan, C. C., Ahearn, M. B., & Kellam, S. G. (1991). Analysis of the elements of attention: A neuropsychological approach. Neuropsychology Review, 2(2), 109145. https://doi.org/10.1007/bf01109051CrossRefGoogle ScholarPubMed
Miyake, A., & Friedman, N. P. (2012). The nature and organization of individual differences in executive functions. Current Directions in Psychological Science, 21(1), 814. https://doi.org/10.1177/0963721411429458CrossRefGoogle ScholarPubMed
Miyake, A., Emerson, M. J., Padilla, F., & Ahn, J. (2004). Inner speech as a retrieval aid for task goals: The effects of cue type and articulatory suppression in the random task cueing paradigm. Acta Psychologica, 115, 123142. https://doi.org/10.1016/j.actpsy.2003.12.004CrossRefGoogle Scholar
Miyake, A., Friedman, N. P., Emerson, M. J., Witzki, A. H., Howerter, A., & Wager, T. D. (2000). The unity and diversity of executive functions and their contributions to complex “frontal lobe” tasks: A latent variable analysis. Cognitive Psychology, 41(1), 49100. https://doi.org/10.1006/cogp.1999.0734CrossRefGoogle ScholarPubMed
Mohapatra, B., & Marshall, R. S. (2019). Performance differences between aphasia and healthy aging on an executive function test battery. International Journal of Speech-Language Pathology, 22(4), 487497. https://doi.org/10.1080/17549507.2019.1691262CrossRefGoogle Scholar
Morey, C. C., Cowan, N., Morey, R. D., & Rouder, J. N. (2011). Flexible attention allocation to visual and auditory working memory tasks: Manipulating reward induces a trade-off. Attention, Perception, & Psychophysics, 73(2), 458472. https://doi.org/10.3758/s13414-010-0031-4CrossRefGoogle ScholarPubMed
Morgan-Short, K., Faretta-Stutenberg, M., Brill-Schuetz, K. A., Carpenter, H., & Wong, P. C. (2014). Declarative and procedural memory as individual differences in second language acquisition. Bilingualism: Language and Cognition, 17(1), 5672. https://doi.org/10.1017/S1366728912000715CrossRefGoogle Scholar
Morgan-Short, K., Steinhauer, K., Sanz, C., & Ullman, M. T. (2012). Explicit and implicit langauge training differentially affect the achievement of native-like brain activation patterns. Journal of Cognitive Neuroscience, 24(4), 933947. https://doi.org/10.1162/jocn_a_00119CrossRefGoogle Scholar
Morris, N., & Jones, D. M. (1990). Memory updating in working memory: The role of the central executive. British Journal of Psychology, 81(2), 111121. https://doi.org/10.1111/j.2044-8295.1990.tb02349.xCrossRefGoogle Scholar
Mosse, E. K., & Jarrold, C. (2008). Short article: Hebb learning, verbal short-term memory, and the acquisition of phonological forms in children. Quarterly Journal of Experimental Psychology, 61(4), 505514. https://doi.org/10.1080/17470210701680779CrossRefGoogle ScholarPubMed
Müller, U., Kerns, K. A., & Konkin, K. (2012). Test-retest reliability and practice effects of executive function tasks in preschool children. The Clinical Neuropsychologist, 26(2), 271287. https://doi.org/10.1080/13854046.2011.645558CrossRefGoogle ScholarPubMed
Munson, B., Kurtz, B. A., & Windsor, J. (2005). The influence of vocabulary size, phonotactic probability, and word likeness on nonword repetitions of children with and without specific language impairment. Journal of Speech, Language, and Hearing Research, 48(5), 10331047. https://doi.org/10.1044/1092-4388(2005/072)CrossRefGoogle Scholar
Murayama, K., Miyatsu, T., Buchli, D., & Storm, B. C. (2014). Forgetting as a consequence of retrieval: A meta-analytic review of retrieval-induced forgetting. Psychological Bulletin, 140(5), 13831409. https://doi.org/10.1037/a0037505CrossRefGoogle ScholarPubMed
Murray, L. L. (1999). Review attention and aphasia: Theory, research and clinical implications. Aphasiology, 13(2), 91111. https://doi.org/10.1080/026870399402226CrossRefGoogle Scholar
Murray, L. L. (2012). Attention and other cognitive deficits in aphasia: Presence and relation to language and communication measures. American Journal of Speech-Language Pathology, 21(2), 5164. https://doi.org/10.1044/1058-0360(2012/11-0067)CrossRefGoogle ScholarPubMed
Murray, L., Salis, C., Martin, N., & Dralle, J. (2018). The use of standardized short-term and working memory tests in aphasia research: A systematic review. Neuropsychological Rehabilitation, 28(3), 309351. https://doi.org/10.1080/09602011.2016.1174718CrossRefGoogle ScholarPubMed
Nadel, L., & Moscovitch, M. (1997). Memory consolidation, retrograde amnesia and the hippocampal complex. Current Opinion in Neurobiology, 7(2), 217227. https://doi.org/10.1016/s0959-4388(97)80010-4CrossRefGoogle ScholarPubMed
Nadel, L., Samsonovich, A., Ryan, L., & Moscovitch, M. (2000). Multiple trace theory of human memory: Computational, neuroimaging, and neuropsychological results. Hippocampus, 10(4), 352368. https://doi.org/10.1002/1098-1063(2000)10:4<352::aid-hipo2>3.0.co;2-d3.0.CO;2-D>CrossRefGoogle ScholarPubMed
Nasar, J., Hecht, P., & Wener, R. (2008). Mobile telephones, distracted attention, and pedestrian safety. Accident Analysis & Prevention, 40(1), 6975. https://doi.org/10.1016/j.aap.2007.04.005CrossRefGoogle ScholarPubMed
Nicholas, M., & Connor, L. T. (2017) People with aphasia using AAC: Are executive functions important? Aphasiology, 31(7), 819836. https://doi.org/10.1080/02687038.2016.1258539CrossRefGoogle Scholar
Nicholas, M., Sinotte, M. P., & Helm-Estabrooks, N. (2011). C-speak aphasia alternative communication program for people with severe aphasia: Importance of executive functioning and semantic knowledge. Neuropsychological Rehabilitation, 21(3), 322366. https://doi.org/10.1080/09602011.2011.559051CrossRefGoogle ScholarPubMed
Norris, D., & Kalm, K. (2021). Chunking and data compression in verbal short-term memory. Cognition, 208, 104534. https://doi.org/10.1016/j.cognition.2020.104534CrossRefGoogle ScholarPubMed
Norris, J., & Ortega, L. (2000). Effectiveness of L2 instruction: A research synthesis and quantitative meta-analysis. Language Learning, 50(3), 417528. https://doi.org/10.1111/0023-8333.00136CrossRefGoogle Scholar
Novick, J. M., Trueswell, J. C., & Thompson-Schill, S. L. (2005). Cognitive control and parsing: Reexamining the role of Broca’s area in sentence comprehension. Cognitive, Affective, & Behavioral Neuroscience, 5(3), 263281. https://doi.org/10.3758/cabn.5.3.263CrossRefGoogle ScholarPubMed
Obermeyer, J., Schlesinger, J., & Martin, N. (2020). Evaluating the contribution of executive functions to language tasks in cognitively demanding contexts. American Journal of Speech-Language Pathology, 29(1S), 463473. https://doi.org/10.1044/2019_ajslp-cac48-18-0216CrossRefGoogle ScholarPubMed
Ojemann, G. A., Schoenfield-McNeill, J., & Corina, D. (2009). The roles of human lateral temporal cortical neuronal activity in recent verbal memory encoding. Cerebral Cortex, 19(1), 197205. https://doi.org/10.1093/cercor/bhn071CrossRefGoogle ScholarPubMed
Olsson, C., Arvidsson, P., & Blom Johansson, M. (2019). Relations between executive function, language, and functional communication in severe aphasia. Aphasiology, 33(7), 821845. https://doi.org/10.1080/02687038.2019.1602813CrossRefGoogle Scholar
Olsson, C., Arvidsson, P., & Blom Johansson, M. (2020). Measuring executive function in people with severe aphasia: Comparing neuropsychological tests and informant ratings. NeuroRehabilitation, 46(3), 299310. https://doi.org/10.3233/nre-192998CrossRefGoogle ScholarPubMed
Oppermann, F., Jescheniak, J. D., & Görges, F. (2014). Resolving competition when naming an object in a multiple-object display. Psychonomic Bulletin & Review, 21(1), 7884. https://doi.org/10.3758/s13423-013-0465-5CrossRefGoogle Scholar
Oswald, F. L., McAbee, S. T., Redick, T. S., & Hambrick, D. Z. (2015). The development of a short domain-general measure of working memory capacity. Behavior Research Methods, 47(4), 13431355. https://doi.org/10.3758/s13428-014-0543-2CrossRefGoogle Scholar
Packard, M. G., and McGaugh, J. L. (1996). Inactivation of hippocampus or caudate nucleus with lidocaine differentially affects expression of place and response learning. Neurobiology of Learning and Memory, 65(1), 6572. https://doi.org/10.1006/nlme.1996.0007CrossRefGoogle ScholarPubMed
Papagno, C., & Vallar, G. (1992). Phonological short-term memory and learning of novel words: The effect of phonological similarity and item length. The Quarterly Journal of Experimental Psychology Section A, 44 (1), 4767. https://doi.org/10.1080/14640749208401283CrossRefGoogle Scholar
Papagno, C., Valentine, T., & Baddeley, A. (1991). Phonological short-term memory and foreign-language vocabulary learning. Journal of Memory & Language, 30(3), 331347. https://doi.org/10.1016/0749-596x(91)90040-qCrossRefGoogle Scholar
Park, J., Miller, C. A., Sanjeevan, T., van Hell, J. G., Weiss, D. J., & Mainela-Arnold, E. (2019). Bilingualism and attention in typically developing children and children with developmental language disorder. Journal of Speech, Language, and Hearing Research, 62(11), 41054118. https://doi.org/10.1044/2019_jslhr-l-18-0341CrossRefGoogle ScholarPubMed
Pauls, L. J., & Archibald, L. M. (2016). Executive functions in children with specific language impairment: A meta-analysis. Journal of Speech, Language, and Hearing Research, 59(5), 10741086. https://doi.org/10.1044/2016_jslhr-l-15-0174CrossRefGoogle ScholarPubMed
Peng, P., Barnes, M., Wang, C., Wang, W., Li, S., Swanson, H. L., Dardick, W., & Tao, S. (2018). A meta-analysis on the relation between reading and working memory. Psychological Bulletin, 144(1), 4876. https://doi.org/10.1037/bul0000124CrossRefGoogle ScholarPubMed
Peristeri, E., Tsimpli, I. M., Dardiotis, E., & Tsapkini, K. (2020). Effects of executive attention on sentence processing in aphasia. Aphasiology, 34(8), 943969. https://doi.org/10.1080/02687038.2019.1622647CrossRefGoogle ScholarPubMed
Peteranderl, S., & Oberauer, K. (2018). Serial recall of colors: Two models of memory for serial order applied to continuous visual stimuli. Memory & Cognition, 46(1), 116. https://doi.org/10.3758/s13421-017-0741-0CrossRefGoogle ScholarPubMed
Poldrack, R. A., & Gabrieli, J. D. (1997). Functional anatomy of long-term memory. Journal of Clinical Neurophysiology, 14(4), 294310. https://doi.org/10.1097/00004691-199707000-00003CrossRefGoogle ScholarPubMed
Posner, M. I., & Petersen, S. E. (1990). The attention system of the human brain. Annual Review of Neuroscience, 13(1), 2542. https://doi.org/10.1146/annurev.ne.13.030190.000325CrossRefGoogle ScholarPubMed
Posner, M. I., Snyder, C. R., & Davidson, B. J. (1980). Attention and the detection of signals. Journal of Experimental Psychology: General, 109(2), 160174. https://doi.org/10.1037/0096-3445.109.2.160CrossRefGoogle ScholarPubMed
Potagas, C., Kasselimis, D., & Evdokimidis, I. (2011). Short-term and working memory impairments in aphasia. Neuropsychologia, 49(10), 28742878. https://doi.org/10.1016/j.neuropsychologia.2011.06.013CrossRefGoogle ScholarPubMed
Purdy, M. (2002). Executive function ability in persons with aphasia. Aphasiology, 16(4–6), 549557. https://doi.org/10.1080/02687030244000176CrossRefGoogle Scholar
Rankin, E., Newton, C., Parker, A., & Bruce, C. (2014). Hearing loss and auditory processing ability in people with aphasia. Aphasiology, 28(5), 576595. https://doi.org/10.1080/02687038.2013.878452CrossRefGoogle Scholar
Reber, P. J. (2008). Cognitive neuroscience of declarative and nondeclarative memory. In Guadagnoli, M., Benjamin, A. S., de Belle, J. S., Etnyre, B., & Polk, T. A. (Eds.), Human Learning: Biology, Brain and Neuroscience (Vol. 139, pp. 113123). Elsevier.10.1016/S0166-4115(08)10010-3CrossRefGoogle Scholar
Reber, P. J. (2013). The neural basis of implicit learning and memory: A review of neuropsychological and neuroimaging research. Neuropsychologia, 51(10), 20262042. https:/doi.org/10.1016/j.neuropsychologia.2013.06.019CrossRefGoogle ScholarPubMed
Richmond, J., & Nelson, C. A. (2007). Accounting for change in declarative memory: A cognitive neuroscience perspective. Developmental Review, 27(3), 349373. https://doi.org/10.1016/j.dr.2007.04.002CrossRefGoogle ScholarPubMed
Roelofs, A., & Piai, V. (2011). Attention demands of spoken word planning: A review. Frontiers in Psychology, 2. https://doi.org/10.3389/fpsyg.2011.00307CrossRefGoogle ScholarPubMed
Rogalsky, C., Matchin, W., & Hickok, G. (2008). Broca’s area, sentence comprehension, and working memory: An fMRI study. Frontiers in Human Neuroscience, 2. https://doi.org/10.3389/neuro.09.014.2008CrossRefGoogle ScholarPubMed
Rogers, T., Hodges, J., Patterson, K., & Lambon Ralph, M. (2003). Object recognition under semantic impairment: The effects of conceptual regularities on perceptual decisions. Language and Cognitive Processes, 18(5–6), 625662. https://doi.org/10.1080/01690960344000053CrossRefGoogle Scholar
Rogers, T. T., Lambon Ralph, M. A., Garrard, P., Bozeat, S., McClelland, J. L., Hodges, J. R., & Patterson, K. (2004). Structure and deterioration of semantic memory: A neuropsychological and computational investigation. Psychological Review, 111(1), 205235. https://doi.org/10.1037/0033-295x.111.1.205CrossRefGoogle ScholarPubMed
Romberg, A. R., & Saffran, J. R. (2010). Statistical learning and language acquisition. WIREs Cognitive Science, 1(6), 906914. https://doi.org/10.1002/wcs.78CrossRefGoogle ScholarPubMed
Romero Lauro, L. J., Reis, J., Cohen, L. G., Cecchetto, C., & Papagno, C. (2010). A case for the involvement of phonological loop in sentence comprehension. Neuropsychologia, 48(14), 40034011. https://doi.org/10.1016/j.neuropsychologia.2010.10.019CrossRefGoogle Scholar
Rudner, M., & Rönnberg, J. (2008). The role of the episodic buffer in working memory for language processing. Cognitive Processing, 9(1), 1928. https://doi.org/10.1007/s10339-007-0183-xCrossRefGoogle ScholarPubMed
Saffran, J. R. (2020). Statistical language learning in infancy. Child Development Perspectives, 14(1), 4954. https://doi.org/10.1111/cdep.12355CrossRefGoogle ScholarPubMed
Saffran, J. R., & Kirkham, N. Z. (2018). Infant statistical learning. Annual Review of Psychology, 69(1), 181203. https://doi.org/10.1146/annurev-psych-122216-011805CrossRefGoogle ScholarPubMed
Schacter, D. L., & Dodson, C. S. (2001). Misattribution, false recognition and the sins of memory. Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences, 356(1413), 13851393. https://doi.org/10.1098/rstb.2001.0938CrossRefGoogle ScholarPubMed
Schendan, H. E. (2012). Semantic memory. In Ramachandran, V. S. (Ed.), Encyclopedia of Human Behavior (pp. 350358). Elsevier. https://doi.org/10.1016/B978-0-12-375000-6.00315-3CrossRefGoogle Scholar
Schmidt-Wilcke, T., Poljansky, S., Hierlmeier, S., Hausner, J., & Ibach, B. (2009). Memory performance correlates with gray matter density in the ento-/perirhinal cortex and posterior hippocampus in patients with mild cognitive impairment and healthy controls: A voxel based morphometry study. NeuroImage, 47(4), 19141920. https://doi.org/10.1016/j.neuroimage.2009.04.092CrossRefGoogle ScholarPubMed
Schneider, D., Herbst, S. K., Klatt, L.-I., & Wöstmann, M. (2021). Target enhancement or distractor suppression? Functionally distinct alpha oscillations form the basis of attention. European Journal of Neuroscience, 55(11–12), 32563265. https://doi.org/10.1111/ejn.15309CrossRefGoogle ScholarPubMed
Schnur, T. T., Schwartz, M. F., Brecher, A., & Hodgson, C. (2006). Semantic interference during blocked-cyclic naming: Evidence from aphasia. Journal of Memory and Language, 54(2),199227. https://doi.org/10.1016/j.jml.2005.10.002CrossRefGoogle Scholar
Seer, C., Sidlauskaite, J., Lange, F., Rodríguez-Nieto, G., & Swinnen, S. P. (2021). Cognition and action: A latent variable approach to study contributions of executive functions to motor control in older adults. Aging, 13(12), 1594215963. https://doi.org/10.18632/aging.203239CrossRefGoogle Scholar
Seidenberg, M. S., & Plaut, D. C. (2014). Quasiregularity and its discontents: The legacy of the past tense debate. Cognitive Science, 38(6), 11901228. https://doi.org/10.1111/cogs.12147CrossRefGoogle ScholarPubMed
Shamma, S. A., Elhilali, M., & Micheyl, C. (2011). Temporal coherence and attention in auditory scene analysis. Trends in Neurosciences, 34(3), 114123. https://doi.org/10.1016/j.tins.2010.11.002CrossRefGoogle ScholarPubMed
Shaywitz, S. E., & Shaywitz, B. A. (2008). Paying attention to reading: The neurobiology of reading and dyslexia. Development and Psychopathology, 20(4), 13291349. https://doi.org/10.1017/s0954579408000631CrossRefGoogle ScholarPubMed
Shiffrin, R. M., & Atkinson, R. C. (1969). Storage and retrieval processes in long-term memory. Psychological Review, 76(2), 179193. https://doi.org/10.1037/h0027277CrossRefGoogle Scholar
Shinn-Cunningham, B. G. (2008). Object-based auditory and visual attention. Trends in Cognitive Sciences, 12(5), 182186. https://doi.org/10.1016/j.tics.2008.02.003CrossRefGoogle ScholarPubMed
Smith, E. E., & Jonides, J. (1997). Working memory: A view from neuroimaging. Cognitive Psychology, 33(1), 542. https://doi.org/10.1006/cogp.1997.0658CrossRefGoogle ScholarPubMed
Smyth, M. M., & Pendleton, L. R. (1990). Space and movement in working memory. The Quarterly Journal of Experimental Psychology Section A, 42(2), 291304. https://doi.org/10.1080/14640749008401223CrossRefGoogle ScholarPubMed
Sohlberg, M. M., & Mateer, C. A. (1987). Effectiveness of an attention-training program. Journal of Clinical and Experimental Neuropsychology, 9(2), 117130. https://doi.org/10.1080/01688638708405352CrossRefGoogle ScholarPubMed
Sohlberg, M. M., & Mateer, C. A. (2001). Cognitive Rehabilitation: An Integrative Neuropsychological Approach. Guilford Press.Google Scholar
Souza, A. S., & Oberauer, K. (2018). Does articulatory rehearsal help immediate serial recall? Cognitive Psychology, 107, 121. https://doi.org/10.1016/j.cogpsych.2018.09.002CrossRefGoogle ScholarPubMed
Squire, L. R. (1992). Declarative and nondeclarative memory: Multiple brain systems supporting learning and memory. Journal of Cognitive Neuroscience, 4(3), 232243. https://doi.org/10.1162/jocn.1992.4.3.232CrossRefGoogle ScholarPubMed
Squire, L. R. (2009a). Memory and brain systems: 1969–2009. Journal of Neuroscience, 29(41), 1271112716. https://doi.org/10.1523/jneurosci.3575-09.2009CrossRefGoogle ScholarPubMed
Squire, L. R. (2009b). The legacy of patient HM for neuroscience. Neuron, 61(1), 69. https://doi.org/10.1016/j.neuron.2008.12.023CrossRefGoogle ScholarPubMed
Squire, L. R., & Alvarez, P. (1995). Retrograde amnesia and memory consolidation: A neurobiological perspective. Current Opinion in Neurobiology, 5(2), 169177. https://doi.org/10.1016/0959-4388(95)80023-9CrossRefGoogle ScholarPubMed
Squire, L. R., Genzel, L., Wixted, J. T., & Morris, R. G. (2015). Memory consolidation. Cold Spring Harbor Perspectives in Biology, 7(8), a021766. https://doi.org/10.1101/cshperspect.a021766CrossRefGoogle ScholarPubMed
Squire, L. R., & Zola, S. M. (1996). Structure and function of declarative and nondeclarative memory systems. Proceedings of the National Academy of Sciences, 93(24), 1351513522. https://doi.org/10.1073/pnas.93.24.13515CrossRefGoogle ScholarPubMed
Squire, L. R., & Zola, S. M. (1998). Episodic memory, semantic memory, and amnesia. Hippocampus, 8(3), 205211. https://doi.org/10.1002/(sici)1098-1063(1998)8:3<205::aid-hipo3>3.0.co;2-i3.0.CO;2-I>CrossRefGoogle ScholarPubMed
Stein, J. (2014). Dyslexia: The role of vision and visual attention. Current Developmental Disorders Reports, 1(4), 267280. https://doi.org/10.1007/s40474-014-0030-6CrossRefGoogle ScholarPubMed
Stern, P., & Shalev, L. (2013). The role of sustained attention and display medium in reading comprehension among adolescents with ADHD and without it. Research in Developmental Disabilities, 34(1), 431439. https://doi.org/10.1016/j.ridd.2012.08.021CrossRefGoogle Scholar
Storm, B. C., & Levy, B. J. (2012). A progress report on the inhibitory account of retrieval-induced forgetting. Memory & Cognition, 40(6), 827843. https://doi.org/10.3758/s13421–012-0211-7CrossRefGoogle ScholarPubMed
Stuss, D. T. (2011). Functions of the frontal lobes: Relation to executive functions. Journal of the International Neuropsychological Society, 17(5), 759765. https://doi.org/10.1017/S1355617711000695CrossRefGoogle ScholarPubMed
Szalárdy, O., Tóth, B., Farkas, D., György, E., & Winkler, I. (2019). Neuronal correlates of informational and energetic masking in the human brain in a multi-talker situation. Frontiers in Psychology, 10. https://doi.org/10.3389/fpsyg.2019.00786CrossRefGoogle Scholar
Teuber, H. L. (1972). Unity and diversity of frontal lobe functions. Acta Neurobiologiae Experimentalis, 32(2), 615656.Google ScholarPubMed
Thakur, C. S., Wang, R. M., Afshar, S., Hamilton, T. J., Tapson, J. C., Shamma, S. A., & van Schaik, A. (2015). Sound stream segregation: A neuromorphic approach to solve the “cocktail party problem” in real-time. Frontiers in Neuroscience, 9. https://doi.org/10.3389/fnins.2015.00309CrossRefGoogle ScholarPubMed
Thut, G., Nietzel, A., Brandt, S. A., & Pascual-Leone, A. (2006). Alpha-band electroencephalographic activity over occipital cortex indexes visuospatial attention bias and predicts visual target detection. Journal of Neuroscience, 26(37), 94949502. https://doi.org/10.1523/jneurosci.0875-06.2006CrossRefGoogle ScholarPubMed
Treisman, A. M. (1960). Contextual cues in selective listening. Quarterly Journal of Experimental Psychology, 12(4), 242248. https://doi.org/10.1080/17470216008416732CrossRefGoogle Scholar
Tucha, L., Aschenbrenner, S., Koerts, J., & Lange, K. W. (2012). The five-point test: Reliability, validity, and normative data for children and adults. PLoS ONE, 7(9), e46080. https://doi.org/10.1371/journal.pone.0046080CrossRefGoogle ScholarPubMed
Tulving, E. (1972). Episodic and semantic memory. In Tulving, E. & Donaldson, W. (Eds.), Organization of Memory (pp. 381403). Academic Press.Google Scholar
Tulving, E. (2002). Does memory encoding exist? In Naveh-Benjamin, M., Moscovitch, M., & Roediger, H. L. III (Eds.), Perspectives on Human Memory and Cognitive Aging: Essays in Honor of Fergus Craik (pp. 627). Psychology Press.Google Scholar
Tulving, E., & Pearlstone, Z. (1966). Availability versus accessibility of information in memory for words. Journal of Verbal Learning and Verbal Behavior, 5(4), 381391. https://doi.org/10.1016/s0022-5371(66)80048-8CrossRefGoogle Scholar
Ullman, M. T. (2001). A neurocognitive perspective on language: The declarative/procedural model. Nature Reviews Neuroscience, 2(10), 717726. https://doi.org/10.1038/35094573CrossRefGoogle ScholarPubMed
Ullman, M.T. (2004). Contributions of memory circuits to language: The declarative/procedural model. Cognition, 92(1–2), 231270. https://doi.org/10.1016/j.cognition.2003.10.008CrossRefGoogle ScholarPubMed
Ullman, M. T. (2016). The declarative/procedural model: A neurobiological model of language learning, knowledge, and use. In Neurobiology of Language (pp. 953968). Academic Press.10.1016/B978-0-12-407794-2.00076-6CrossRefGoogle Scholar
Ullman, M. T. (2020). The declarative/procedural model: A neurobiologically motivated theory of first and second language 1. In Theories in Second Language Acquisition (pp. 128161). Routledge.10.4324/9780429503986-7CrossRefGoogle Scholar
Ullman, M. T., Corkin, S., Coppola, M., Hickok, G., Growdon, J. H., Koroshetz, W. J., & Pinker, S. (1997). A neural dissociation within language: Evidence that the mental dictionary is part of declarative memory, and that grammatical rules are processed by the procedural system. Journal of Cognitive Neuroscience, 9(2), 266276. https://doi.org/10.1162/jocn.1997.9.2.266CrossRefGoogle ScholarPubMed
Unsworth, N., & Engle, R. W. (2007). The nature of individual differences in working memory capacity: Active maintenance in primary memory and controlled search from secondary memory. Psychological Review, 114(1), 104132. https://doi.org/10.1037/0033-295x.114.1.104CrossRefGoogle ScholarPubMed
Vallat-Azouvi, C., Weber, T., Legrand, L., & Azuovi, P. (2007). Working memory after severe traumatic brain injury. Journal of the International Neuropsychological Society, 13(05), 770780. https://doi.org/10.1017/s1355617707070993CrossRefGoogle ScholarPubMed
Verde, M. F. (2012). Retrieval-induced forgetting and inhibition: A critical review. In Ross, B. H. (Ed.), Psychology of Learning and Motivation, (Vol. 56, pp. 4780). Academic Press. https://doi.org/10.1016/b978-0-12-394393-4.00002-9Google Scholar
Villard, S., & Kidd, G. Jr. (2019). Effects of acquired aphasia on the recognition of speech under energetic and informational masking conditions. Trends in Hearing, 23, 122. https://doi.org/10.1177/2331216519884480CrossRefGoogle ScholarPubMed
Villard, S., & Kiran, S. (2015). Between-session intra-individual variability in sustained, selective, and integrational non-linguistic attention in aphasia. Neuropsychologia, 66, 204212. https://doi.org/10.1016/j.neuropsychologia.2014.11.026CrossRefGoogle ScholarPubMed
Villard, S., & Kiran, S. (2017). To what extent does attention underlie language in aphasia? Aphasiology, 31(10), 12261245. https://doi.org/10.1080/02687038.2016.1242711CrossRefGoogle Scholar
Vossel, S., Geng, J. J., & Fink, G. R. (2014). Dorsal and ventral attention systems: Distinct neural circuits but collaborative roles. The Neuroscientist, 20(2), 150159. https://doi.org/10.1177/1073858413494269CrossRefGoogle ScholarPubMed
Vugs, B., Hendriks, M., Cuperus, J., & Verhoeven, L. (2014). Working memory performance and executive function behaviors in young children with SLI. Research in Developmental Disabilities, 35(1), 6274. https://doi.org/10.1016/j.ridd.2013.10.022CrossRefGoogle Scholar
Wager, T. D., & Smith, E. E. (2003). Neuroimaging studies of working memory: A meta-analysis. Cognitive, Affective, & Behavioral Neuroscience, 3(4), 255274. https://doi.org/10.3758/cabn.3.4.255CrossRefGoogle ScholarPubMed
Wagner, A. D., Shannon, B. J., Kahn, I., & Buckner, R. L. (2005). Parietal lobe contributions to episodic memory retrieval. Trends in Cognitive Sciences, 9(9), 445453. https://doi.org/10.1016/j.tics.2005.07.001CrossRefGoogle ScholarPubMed
Waters, G. S., Rochon, E., & Caplan, D. (1992). The role of high-level speech planning in rehearsal: Evidence from patients with apraxia of speech. Journal of Memory and Language, 31(1), 5473. https://doi.org/10.1016/0749-596X(92)90005-ICrossRefGoogle Scholar
Wiebe, S. A., Espy, K. A., & Charak, D. (2008). Using confirmatory factor analysis to understand executive control in preschool children: I. Latent structure. Developmental Psychology, 44(2), 575587. https://doi.org/10.1037/0012-1649.44.2.575CrossRefGoogle ScholarPubMed
Winkielman, P., Schwarz, N., Fazendeiro, T. A., & Reber, R. (2003). The hedonic marking of processing fluency: Implications for evaluative judgment. In Musch, J. & Klauer, K. C. (Eds.), The Psychology of Evaluation: Affective Processes in Cognition and Emotion (pp. 189217). Lawrence Erlbaum Associates Publishers.Google Scholar
Worden, M. S., Foxe, J. J., Wang, N., & Simpson, G. V. (2000). Anticipatory biasing of visuospatial attention indexed by retinotopically specific alpha-bank electroencephalography increases over occipital cortex. Journal of Neuroscience, 20(6), RC63. https://doi.org/10.1523/jneurosci.20-06-j0002.2000CrossRefGoogle Scholar
Yee, E., Chrysikou, E. G., Hoffman, E., & Thompson-Schill, S. L. (2013). Manual experience shapes object representations. Psychological Science, 24(6), 909919. https://doi.org/10.1177/0956797612464658CrossRefGoogle ScholarPubMed
Zhang, M., Alamatsaz, N., & Ihlefeld, A. (2021). Hemodynamic responses link individual differences in informational masking to the vicinity of superior temporal gyrus. Frontiers in Neuroscience, 15. https://doi.org/10.3389/fnins.2021.675326Google Scholar

References

Altmann, G. T., & Kamide, Y. (1999). Incremental interpretation at verbs: Restricting the domain of subsequent reference. Cognition, 73, 247264.10.1016/S0010-0277(99)00059-1CrossRefGoogle ScholarPubMed
Altmann, G. T., & Kamide, Y. (2007). The real-time mediation of visual attention by language and world knowledge: Linking anticipatory (and other) eye movements to linguistic processing. Journal of Memory and Language, 57, 502518.10.1016/j.jml.2006.12.004CrossRefGoogle Scholar
Balota, D. A., Pollatsek, A., & Rayner, K. (1985). The interaction of contextual constraints and parafoveal visual information in reading. Cognitive Psychology, 17, 364390.10.1016/0010-0285(85)90013-1CrossRefGoogle ScholarPubMed
Bonhage, C. E., Mueller, J. L., Friederici, A. D., & Fiebach, C. J. (2015). Combined eye tracking and fMRI reveals neural basis of linguistic predictions during sentence comprehension. Cortex, 68, 3347. https://doi.org/10.1016/j.cortex.2015.03.014CrossRefGoogle ScholarPubMed
Boudewyn, M. A., Long, D. L., & Swaab, T. Y. (2015). Graded expectations: Predictive processing and the adjustment of expectations during spoken language comprehension. Cognitive, Affective, & Behavioral Neuroscience, 15(3), 607624. https://doi.org/10.3758/s13415-015-0340-0CrossRefGoogle ScholarPubMed
Brennan, J. R., Dyer, C., Kuncoro, A., & Hale, J. T. (2020). Localizing syntactic predictions using recurrent neural network grammars. Neuropsychologia, 146, 107479.10.1016/j.neuropsychologia.2020.107479CrossRefGoogle ScholarPubMed
Brothers, T., & Kuperberg, G. R. (2021). Word predictability effects are linear, not logarithmic: Implications for probabilistic models of sentence comprehension. Journal of Memory and Language, 116, 104174.10.1016/j.jml.2020.104174CrossRefGoogle Scholar
Brothers, T., & Traxler, M. J. (2016). Anticipating syntax during reading: Evidence from the boundary change paradigm. Journal of Experimental Psychology: Learning, Memory, and Cognition, 42(12), 1894.Google ScholarPubMed
Brothers, T., Dave, S., Hoversten, L. J., Traxler, M. J., & Swaab, T. Y. (2019). Flexible predictions during listening comprehension: Speaker reliability affects anticipatory processes. Neuropsychologia, 135, 107225.10.1016/j.neuropsychologia.2019.107225CrossRefGoogle ScholarPubMed
Brothers, T., Swaab, T. Y., & Traxler, M. J. (2015). Effects of prediction and contextual support on lexical processing: Prediction takes precedence. Cognition, 136, 135149.10.1016/j.cognition.2014.10.017CrossRefGoogle ScholarPubMed
Brothers, T., Swaab, T. Y., & Traxler, M. J. (2017). Goals and strategies influence lexical prediction during sentence comprehension. Journal of Memory and Language, 93, 203216.10.1016/j.jml.2016.10.002CrossRefGoogle Scholar
Buac, M., Tauzin-Larché, A., Weisberg, E., & Kaushanskaya, M. (2019). Effect of speaker certainty on novel word learning in monolingual and bilingual children. Bilingualism: Language and Cognition, 22(4), 883895.10.1017/S1366728918000536CrossRefGoogle ScholarPubMed
Choi, W., Lowder, M. W., Ferreira, F., Swaab, T. Y., & Henderson, J. M. (2017). Effects of word predictability and preview lexicality on eye movements during reading: A comparison between young and older adults. Psychology and Aging, 32, 232242. https://doi.org/10.1037/pag0000160CrossRefGoogle Scholar
Clark, A. (2013). Expecting the world: Perception, prediction, and the origins of human knowledge. The Journal of Philosophy, 110(9), 469496. https://doi.org/10.5840/jphil20131109/2CrossRefGoogle Scholar
Clement, F, Koenig, M, & Harris, P. (2004). The ontogenesis of trust. Mind & Language, 19, 360379.10.1111/j.0268-1064.2004.00263.xCrossRefGoogle Scholar
Dave, S., Brothers, T. A., & Swaab, T. Y. (2018). 1/f neural noise and electrophysiological indices of contextual prediction in aging. Brain Research, 1691, 3443.10.1016/j.brainres.2018.04.007CrossRefGoogle ScholarPubMed
Dave, S., Brothers, T. A., Traxler, M. J., Ferreira, F., Henderson, J. M., & Swaab, T. Y. (2018). Electrophysiological evidence for preserved primacy of lexical prediction in aging. Neuropsychologia, 117, 135147.10.1016/j.neuropsychologia.2018.05.023CrossRefGoogle ScholarPubMed
Dave, S., Brothers, T., Hoversten, L. J., Traxler, M. J., & Swaab, T. Y. (2021). Cognitive control mediates age-related changes in flexible anticipatory processing during listening comprehension. Brain Research, 1768, 147573.10.1016/j.brainres.2021.147573CrossRefGoogle ScholarPubMed
Delaney-Busch, N., Morgan, E., Lau, E. F., & Kuperberg, G. R. (2017). Comprehenders rationally adapt semantic predictions to the statistics of the local environment: A Bayesian model of trial-by-trial N400 amplitudes. In Proceedings of the 39th Annual Meeting of the Cognitive Science Society, London.Google Scholar
DeLong, K. A., Urbach, T. P., & Kutas, M. (2005). Probabilistic word pre-activation during language comprehension inferred from electrical brain activity. Nature Neuroscience, 8, 11171121.10.1038/nn1504CrossRefGoogle ScholarPubMed
Drieghe, D., Rayner, K., & Pollatsek, A. (2005). Eye movements and word skipping during reading revisited. Journal of Experimental Psychology: Human Perception and Performance, 31, 954969.Google ScholarPubMed
Dussias, P. E., Kroff, J. R. V., Tamargo, R. E. G., & Gerfen, C. (2013). When gender and looking go hand in hand: Grammatical gender processing in L2 Spanish. Studies in Second Language Acquisition, 35(2), 353387. https://doi.org/10.1017/S0272263112000915CrossRefGoogle Scholar
Eddine, S. N., Brothers, T., & Kuperberg, G. R. (2022). The N400 in silico: A review of computational models. Psychology of Learning and Motivation, 76, 123206.Google Scholar
Elman, J. L. (2004). An alternative view of the mental lexicon. Trends in Cognitive Sciences, 8, 301306.10.1016/j.tics.2004.05.003CrossRefGoogle ScholarPubMed
Elman, J. L., & McClelland, J. L. (1988). Cognitive penetration of the mechanisms of perception: Compensation for coarticulation of lexically restored phonemes. Journal of Memory and Language, 27, 143165.10.1016/0749-596X(88)90071-XCrossRefGoogle Scholar
Fazekas, J., Jessop, A., Pine, J., & Rowland, C. (2020). Do children learn from their prediction mistakes? A registered report evaluating error-based theories of language acquisition. Royal Society Open Science, 7(11), 180877. https://doi.org/10.1098/rsos.180877CrossRefGoogle ScholarPubMed
Federmeier, K. D. (2007). Thinking ahead: The role and roots of prediction in language comprehension. Psychophysiology, 44(4), 491505.10.1111/j.1469-8986.2007.00531.xCrossRefGoogle ScholarPubMed
Federmeier, K. D., Wlotko, E. W., De Ochoa-Dewald, E., & Kutas, M. (2007). Multiple effects of sentential constraint on word processing. Brain Research, 1146, 7584.10.1016/j.brainres.2006.06.101CrossRefGoogle ScholarPubMed
Ferreira, F., & Chantavarin, S. (2018). Integration and prediction in language processing: A synthesis of old and new. Current Directions in Psychological Science, 27(6), 443448. https://doi.org/10.1177/0963721418794491CrossRefGoogle ScholarPubMed
Fitz, H., & Chang, F. (2019). Language ERPs reflect learning through prediction error propagation. Cognitive Psychology, 111, 1552. https://doi.org/10.1016/j.cogpsych.2019.03.002CrossRefGoogle ScholarPubMed
Friston, K. (2018). Does predictive coding have a future?Nature Neuroscience, 21(8), Article 8. https://doi.org/10.1038/s41593-018-0200-7CrossRefGoogle ScholarPubMed
Gibson, E., Bergen, L., & Piantadosi, S. T. (2013). Rational integration of noisy evidence and prior semantic expectations in sentence interpretation. Proceedings of the National Academy of Sciences, 110, 80518056.10.1073/pnas.1216438110CrossRefGoogle ScholarPubMed
Gwilliams, L., Marantz, A., Poeppel, D., & King, J.-R. (2023). Top-down information shapes lexical processing when listening to continuous speech. Language, Cognition and Neuroscience, 39, 10451058.10.1080/23273798.2023.2171072CrossRefGoogle Scholar
Hale, J. (2001). A probabilistic Earley parser as a psycholinguistic model. In Second meeting of the North American chapter of the Association for Computational Linguistics.10.3115/1073336.1073357CrossRefGoogle Scholar
Hale, J. (2003). The information conveyed by words in sentences. Journal of Psycholinguistic Research, 32, 101123.10.1023/A:1022492123056CrossRefGoogle ScholarPubMed
Hale, J. (2006). Uncertainty about the rest of the sentence. Cognitive Science, 30, 643672.10.1207/s15516709cog0000_64CrossRefGoogle ScholarPubMed
Hale, J. (2016). Information‐theoretical complexity metrics. Language and Linguistics Compass, 10(9), 397412.10.1111/lnc3.12196CrossRefGoogle Scholar
Heikel, E., Sassenhagen, J., & Fiebach, C. J. (2018). Decoding semantic predictions from EEG prior to word onset (p. 393066). bioRxiv. https://doi.org/10.1101/393066CrossRefGoogle Scholar
Heilbron, M., Armeni, K., Schoffelen, J.-M., Hagoort, P., & de Lange, F. P. (2022). A hierarchy of linguistic predictions during natural language comprehension. Proceedings of the National Academy of Sciences, 119(32), e2201968119. https://doi.org/10.1073/pnas.2201968119CrossRefGoogle ScholarPubMed
Hess, D. J., Foss, D. J., & Carroll, P. (1995). Effects of global and local context on lexical processing during language comprehension. Journal of Experimental Psychology: General, 124, 62.10.1037/0096-3445.124.1.62CrossRefGoogle Scholar
Hintzman, D. L. (1986). “Schema abstraction” in a multiple-trace memory model. Psychological Review, 93, 411428.10.1037/0033-295X.93.4.411CrossRefGoogle Scholar
Huang, K. J., Arehalli, S., Kugemoto, M., Muxica, C., Prasad, G., Dillon, B., & Linzen, T. (2023). Surprisal does not explain syntactic disambiguation difficulty: Evidence from a large-scale benchmark. Preprint on PsyArXiv.10.31234/osf.io/z38u6CrossRefGoogle Scholar
Huettig, F. (2015). Four central questions about prediction in language processing. Brain Research, 1626, 118135. https://doi.org/10.1016/j.brainres.2015.02.014CrossRefGoogle ScholarPubMed
Jaswal, V. K., & Neely, L. A. (2006). Adults don’t always know best: Preschoolers use past reliability over age when learning new words. Psychological Science, 17(9), 757758.10.1111/j.1467-9280.2006.01778.xCrossRefGoogle ScholarPubMed
Johnson, K., & Sjerps, M. J. (2021). Speaker normalization in speech perception. In Pardo, J. S., Nygaard, L. C., Remez, R. E., & Pisoni, D. B., (Eds.), The Handbook of Speech Perception, 145176. John Wiley & Sons.10.1002/9781119184096.ch6CrossRefGoogle Scholar
Just, M. A., & Carpenter, P. A. (1980). A theory of reading: From eye fixations to comprehension. Psychological Review, 87, 329354.10.1037/0033-295X.87.4.329CrossRefGoogle ScholarPubMed
Kamide, Y., Altmann, G. T., & Haywood, S. L. (2003). The time-course of prediction in incremental sentence processing: Evidence from anticipatory eye movements. Journal of Memory and Language, 49, 133156.10.1016/S0749-596X(03)00023-8CrossRefGoogle Scholar
Kintsch, W. (1988). The role of knowledge in discourse comprehension: A construction-integration model. Psychological Review, 95, 163.10.1037/0033-295X.95.2.163CrossRefGoogle ScholarPubMed
Kintsch, W., & Van Dijk, T. A. (1978). Toward a model of text comprehension and production. Psychological Review, 85, 363.10.1037/0033-295X.85.5.363CrossRefGoogle Scholar
Kinzler, K. D., Corriveau, K. H., & Harris, P. L. (2011). Children’s selective trust in native‐accented speakers. Developmental Science, 14(1), 106111.10.1111/j.1467-7687.2010.00965.xCrossRefGoogle ScholarPubMed
Kinzler, K. D., Dupoux, E., & Spelke, E. S. (2007). The native language of social cognition. Proceedings of the National Academy of Sciences, 104(30), 1257712580.10.1073/pnas.0705345104CrossRefGoogle ScholarPubMed
Koenig, M. A., & Harris, P. L. (2005). Preschoolers mistrust ignorant and inaccurate speakers. Child Development, 76, 12611277.10.1111/j.1467-8624.2005.00849.xCrossRefGoogle ScholarPubMed
Koenig, M. A., & Woodward, A. L. (2010). Sensitivity of 24-month-olds to the prior inaccuracy of the source: Possible mechanisms. Developmental Psychology, 46(4), 815.10.1037/a0019664CrossRefGoogle Scholar
Koenig, M. A., Clément, F., & Harris, P. L. (2004). Trust in testimony: Children’s use of true and false statements. Psychological Science, 15(10), 694698.10.1111/j.0956-7976.2004.00742.xCrossRefGoogle ScholarPubMed
Kroczek, L. O., & Gunter, T. C. (2021). The time course of speaker-specific language processing. Cortex, 141, 311321.10.1016/j.cortex.2021.04.017CrossRefGoogle ScholarPubMed
Kuperberg, G. R. (2021). Tea with milk? A hierarchical generative framework of sequential event comprehension. Topics in Cognitive Science, 13, 256298.10.1111/tops.12518CrossRefGoogle ScholarPubMed
Kuperberg, G. R., & Jaeger, T. F. (2016). What do we mean by prediction in language comprehension? Language, Cognition and Neuroscience, 31, 3259.10.1080/23273798.2015.1102299CrossRefGoogle ScholarPubMed
Kutas, M., DeLong, K. A., & Smith, N. J. (2011). A look around at what lies ahead: Prediction and predictability in language processing. Predictions in the Brain: Using Our Past to Generate a Future, 190207(10.1093).10.1093/acprof:oso/9780195395518.003.0065CrossRefGoogle Scholar
Kutas, M., & Hillyard, S. A. (1980). Reading senseless sentences: Brain potentials reflect semantic incongruity. Science, 207(4427), 203205. https://doi.org/10.1126/science.7350657CrossRefGoogle ScholarPubMed
Kutas, M., & Iragui, V. (1998). The N400 in a semantic categorization task across 6 decades. Electroencephalography and Clinical Neurophysiology/Evoked Potentials Section, 108(5), 456471.10.1016/S0168-5597(98)00023-9CrossRefGoogle Scholar
Kutas, M., Van Petten, C. K., & Kluender, R. (2006). Psycholinguistics electrified II (1994–2005). In Handbook of Psycholinguistics (pp. 659724). Academic Press.10.1016/B978-012369374-7/50018-3CrossRefGoogle Scholar
Lau, E., Stroud, C., Plesch, S., & Phillips, C. (2006). The role of structural prediction in rapid syntactic analysis. Brain and Language, 98(1), 7488.10.1016/j.bandl.2006.02.003CrossRefGoogle ScholarPubMed
Landauer, T. K., & Dumais, S. T. (1997). A solution to Plato’s problem: The latent semantic analysis theory of acquisition, induction, and representation of knowledge. Psychological Review, 104(2), 211.10.1037/0033-295X.104.2.211CrossRefGoogle Scholar
Levelt, W. J. (1992). Accessing words in speech production: Stages, processes and representations. Cognition, 42, 122.10.1016/0010-0277(92)90038-JCrossRefGoogle ScholarPubMed
Levy, R. (2008). Expectation-based syntactic comprehension. Cognition, 106, 11261177.10.1016/j.cognition.2007.05.006CrossRefGoogle ScholarPubMed
Lund, K., & Burgess, C. (1996). Producing high-dimensional semantic spaces from lexical co-occurrence. Behavior Research Methods, Instruments, & Computers, 28(2), 203208.10.3758/BF03204766CrossRefGoogle Scholar
Lupyan, G., & Clark, A. (2015). Words and the World: Predictive Coding and the Language-Perception-Cognition Interface. Current Directions in Psychological Science, 24(4), 279284. https://doi.org/10.1177/0963721415570732CrossRefGoogle Scholar
MacDonald, M. C., Pearlmutter, N. J., & Seidenberg, M. S. (1994). The lexical nature of syntactic ambiguity resolution. Psychological Review, 101(4), 676.10.1037/0033-295X.101.4.676CrossRefGoogle ScholarPubMed
Marslen-Wilson, W. D. (1987). Functional parallelism in spoken word-recognition. Cognition, 25(1–2), 71102.10.1016/0010-0277(87)90005-9CrossRefGoogle ScholarPubMed
McClelland, J. L., & Rumelhart, D. E. (1981). An interactive activation model of context effects in letter perception: I. An account of basic findings. Psychological Review, 88, 375.10.1037/0033-295X.88.5.375CrossRefGoogle Scholar
Metusalem, R., Kutas, M., Urbach, T. P., Hare, M., McRae, K., & Elman, J. L. (2012). Generalized event knowledge activation during online sentence comprehension. Journal of Memory and Language, 66(4), 545567.10.1016/j.jml.2012.01.001CrossRefGoogle ScholarPubMed
Morales, L., Paolieri, D., Dussias, P. E., Kroff, J. R. V., Gerfen, C., & Bajo, M. T. (2016). The gender congruency effect during bilingual spoken-word recognition. Bilingualism: Language and Cognition, 19(2), 294310. https://doi.org/10.1017/S1366728915000176CrossRefGoogle ScholarPubMed
Morris, R. K. (1994). Lexical and message-level sentence context effects on fixation times in reading. Journal of Experimental Psychology: Learning, Memory, & Cognition, 20, 92103.Google ScholarPubMed
Morton, J. (1969). Interaction of information in word recognition. Psychological Review, 76, 165178.10.1037/h0027366CrossRefGoogle Scholar
Ness, T., & Meltzer‐Asscher, A. (2021a). From pre‐activation to pre‐updating: A threshold mechanism for commitment to strong predictions. Psychophysiology, 58(5), e13797.10.1111/psyp.13797CrossRefGoogle ScholarPubMed
Ness, T., & Meltzer-Asscher, A. (2021b). Rational adaptation in lexical prediction: The influence of prediction strength. Frontiers in Psychology, 12, 622873.10.3389/fpsyg.2021.622873CrossRefGoogle ScholarPubMed
Nieuwland, M. S., Arkhipova, Y., & Rodríguez-Gómez, P. (2020). Anticipating words during spoken discourse comprehension: A large-scale, pre-registered replication study using brain potentials. Cortex, 133, 136.10.1016/j.cortex.2020.09.007CrossRefGoogle ScholarPubMed
Nieuwland, M. S., Politzer-Ahles, S., Heyselaar, E., Segaert, K., Darley, E., Kazanina, N., Von Grebmer Zu Wolfsthurn, S., Bartolozzi, F., Kogan, V., & Ito, A. (2018). Large-scale replication study reveals a limit on probabilistic prediction in language comprehension. ELife, 7, e33468.10.7554/eLife.33468CrossRefGoogle ScholarPubMed
Perdomo, M., & Kaan, E. (2021). Prosodic cues in second-language speech processing: A visual world eye-tracking study. Second Language Research, 37, 349375.10.1177/0267658319879196CrossRefGoogle Scholar
Pickering, M. J., & Gambi, C. (2018). Predicting while comprehending language: A theory and review. Psychological Bulletin, 144(10), 1002. https://doi.org/10.1037/bul0000158CrossRefGoogle Scholar
Pickering, M. J., & Garrod, S. (2007). Do people use language production to make predictions during comprehension?Trends in Cognitive Sciences, 11, 105110.10.1016/j.tics.2006.12.002CrossRefGoogle ScholarPubMed
Pickering, M. J., & Garrod, S. (2013). An integrated theory of language production and comprehension. Behavioral and Brain Sciences, 36(4), 329392. https://doi.org/10.1017/S0140525X12003238CrossRefGoogle ScholarPubMed
Pickering, M. J., & Traxler, M. J. (1998). Plausibility and recovery from garden paths: An eye-tracking study. Journal of Experimental Psychology: Learning, Memory, and Cognition, 24, 940961.Google Scholar
Poulton, V. R., & Nieuwland, M. S. (2022). Can you hear what’s coming? Failure to replicate ERP evidence for phonological prediction. Neurobiology of Language, 3, 556574.10.1162/nol_a_00078CrossRefGoogle ScholarPubMed
Rao, R. P. N., & Ballard, D. H. (1999). Predictive coding in the visual cortex: A functional interpretation of some extra-classical receptive-field effects. Nature Neuroscience, 2(1), Article 1. https://doi.org/10.1038/4580CrossRefGoogle ScholarPubMed
Rescorla, R. A., & Wagner, A. R. (1972). A theory of Pavlovian conditioning: Variations in the effectiveness of reinforcement and nonreinforcement. In Black, A. H. & Prokasy, W. F. (Eds.), Classical Conditioning II: Current Research and Theory (Vol. 2, pp. 6499). Appleton-Century-Crofts.Google Scholar
Ryskin, R., Levy, R. P., & Fedorenko, E. (2020). Do domain-general executive resources play a role in linguistic prediction? Re-evaluation of the evidence and a path forward. Neuropsychologia, 136, 107258.10.1016/j.neuropsychologia.2019.107258CrossRefGoogle Scholar
Ryskin, R., & Nieuwland, M. S. (2023). Prediction during language comprehension: What is next?Trends in Cognitive Sciences, 27(11). https://doi.org/10.1016/j.tics.2023.08.003CrossRefGoogle ScholarPubMed
Sabbagh, M. A., & Baldwin, D. A. (2001). Learning words from knowledgeable versus ignorant speakers: Links between preschoolers’ theory of mind and semantic development. Child Development, 72(4), 10541070.10.1111/1467-8624.00334CrossRefGoogle ScholarPubMed
Schwanenflugel, P. J. (1991). Contextual constraint and lexical processing. In Advances in Psychology (Vol. 77, pp. 2345). North-Holland.Google Scholar
Schwanenflugel, P. J., & LaCount, K. L. (1988). Semantic relatedness and the scope of facilitation for upcoming words in sentences. Journal of Experimental Psychology: Learning, Memory, and Cognition, 14, 344354.Google Scholar
Schwanenflugel, P. J., & Shoben, E. J. (1985). The influence of sentence constraint on the scope of facilitation for upcoming words. Journal of Memory and Language, 24, 232252.10.1016/0749-596X(85)90026-9CrossRefGoogle Scholar
Scofield, J., & Behrend, D. A. (2008). Learning words from reliable and unreliable speakers. Cognitive Development, 23(2), 278290.10.1016/j.cogdev.2008.01.003CrossRefGoogle Scholar
Singleton, J. L., & Newport, E. L. (2004). When learners surpass their models: The acquisition of American Sign Language from inconsistent input. Cognitive Psychology, 49(4), 370407.10.1016/j.cogpsych.2004.05.001CrossRefGoogle ScholarPubMed
Steedman, M., & Altmann, G. (1989). Ambiguity in context: A reply. Language and Cognitive Processes, 4(3–4), SI105SI122. https://doi.org/10.1080/01690968908406365CrossRefGoogle Scholar
Stoet, G., (2017). PsyToolkit: A novel web-based method for running online questionnaires and reaction-time experiments. Teaching of Psychology, 44, 2431.10.1177/0098628316677643CrossRefGoogle Scholar
Stroop, J. R., (1935). Studies of interference in serial verbal reactions. Journal of Experimental Psychology, 18, 643.10.1037/h0054651CrossRefGoogle Scholar
Swanson, L. R. (2016). The predictive processing paradigm has roots in Kant. Frontiers in Systems Neuroscience, 10. www.frontiersin.org/articles/10.3389/fnsys.2016.0007910.3389/fnsys.2016.00079CrossRefGoogle ScholarPubMed
Szewczyk, J. M., & Schriefers, H. (2013). Prediction in language comprehension beyond specific words: An ERP study on sentence comprehension in Polish. Journal of Memory and Language, 68(4), 297314.10.1016/j.jml.2012.12.002CrossRefGoogle Scholar
Tanenhaus, M. K., Spivey-Knowlton, M. J., Eberhard, K. M., & Sedivy, J. C. (1995). Integration of visual and linguistic information in spoken language comprehension. Science, 268(5217), 16321634.10.1126/science.7777863CrossRefGoogle ScholarPubMed
Trammel, T., Khodayari, N., Luck, S. J., Traxler, M. J., & Swaab, T. Y. (2023). Decoding semantic relatedness and prediction from EEG: A classification method comparison. NeuroImage, 277, 120268.10.1016/j.neuroimage.2023.120268CrossRefGoogle Scholar
Traxler, M. J. (2014). Trends in syntactic parsing: Anticipation, Bayesian estimation, and good-enough parsing. Trends in Cognitive Sciences, 18, 605611. https://doi.org/10.1016/j.tics.2014.08.001CrossRefGoogle ScholarPubMed
Traxler, M. J. (2023). Introduction to Psycholinguistics: Understanding Language Science (2nd ed.). Wiley-Blackwell.Google Scholar
Traxler, M. J., Foss, D. J., Seely, R. E., Kaup, B., & Morris, R. K. (2000). Priming in sentence processing: Intralexical spreading activation, schemas, and situation models. Journal of Psycholinguistic Research, 29, 581595.10.1023/A:1026416225168CrossRefGoogle ScholarPubMed
Van Berkum, J. J., Brown, C. M., Zwitserlood, P., Kooijman, V., & Hagoort, P. (2005). Anticipating upcoming words in discourse: Evidence from ERPs and reading times. Journal of Experimental Psychology: Learning, Memory, and Cognition, 31(3), 443.Google ScholarPubMed
Van Wonderen, E., & Nieuwland, M. S. (2023). Lexical prediction does not rationally adapt to prediction error: ERP evidence from pre-nominal articles. Journal of Memory and Language, 132, 104435.10.1016/j.jml.2023.104435CrossRefGoogle Scholar
Wang, L., Schoot, L., Brothers, T., Alexander, E., Warnke, L., Kim, M., … & Kuperberg, G. R. (2023). Predictive coding across the left fronto-temporal hierarchy during language comprehension. Cerebral Cortex, 33, 44784497.10.1093/cercor/bhac356CrossRefGoogle ScholarPubMed
Wang, L., Wlotko, E., Alexander, E., Schoot, L., Kim, M., Warnke, L., & Kuperberg, G. R. (2020). Neural evidence for the prediction of animacy features during language comprehension: Evidence from MEG and EEG representational similarity analysis. Journal of Neuroscience, 40(16), 32783291. https://doi.org/10.1523/JNEUROSCI.1733-19.2020CrossRefGoogle ScholarPubMed
Wicha, N. Y., Moreno, E. M., & Kutas, M. (2004). Anticipating words and their gender: An event-related brain potential study of semantic integration, gender expectancy, and gender agreement in Spanish sentence reading. Journal of Cognitive Neuroscience, 16(7), 12721288.10.1162/0898929041920487CrossRefGoogle ScholarPubMed
Wlotko, E. W., & Federmeier, K. D. (2012). So that’s what you meant! Event-related potentials reveal multiple aspects of context use during construction of message-level meaning. NeuroImage, 62(1), 356366.10.1016/j.neuroimage.2012.04.054CrossRefGoogle ScholarPubMed
Zipf, G. K. (1935). (reprinted 1965). The Psycho-Biology of Language. MIT Press.Google Scholar

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Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

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Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

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Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

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