Lateralization and localization of language in the brain is a critical component of surgical planning for patients with epilepsy or brain tumors who require neurosurgical intervention. Accurate language mapping allows the surgeon to conduct the most aggressive surgery possible, enhancing the chance for cure, while avoiding regions critical for language function; striking this balance is critical for maximizing the patient’s quality of life. A range of invasive and non-invasive language mapping techniques are available. This chapter provides a comparative analysis of these techniques and offers a detailed discussion on a newer, non-invasive method called transcranial magnetic stimulation (TMS). Using a superficial coil placed on the scalp, TMS generates a magnetic field that creates a temporary “virtual lesion” in the brain, thereby delineating eloquent cortex. TMS is a safe and well-tolerated procedure for both pediatric and adult populations which closely mimics the “gold-standard” invasive mapping techniques. TMS is becoming an integral component of neurosurgical planning and also shows promise as a research tool for studying typical language development and function in healthy populations.

Variability in ultimate learning outcomes is a conspicuous trait of second language (L2) acquisition. After enumerating well-studied conditioning factors in L2 attainment, the present chapter identifies five for particular attention: working memory, attitudes, music background, genetic makeup, and age of acquisition. Along with detailing the factors’ individual roles in L2 attainment, we demonstrate inter-relationships between them. For example, the aptitude factor of working memory ability is subject to genetic variation and may decline over age of L2 learning. We examine variable outcomes from two distinct perspectives: magnitude (i.e., how the identified factors contribute to higher or lower levels of L2 attainment) and dispersion (i.e., how the factors contribute to greater or lesser variability of L2 attainment). Notably, later ages of L2 learning are associated with both lower L2 attainment levels and greater L2 attainment variability. In this vein, we consider the possibility that magnitudes and variability of L2 outcomes over age of learning may be isomorphic with working memory levels and dispersion over the lifespan. In addition, we underscore the transitory nature of individual-level L2 outcomes, which are subject to destabilization following shifts of dominance between the L1 (first language) and the L2.

It is a privilege to present the introduction to this new volume of The Cambridge Handbook of Language and Brain. The chapters in this volume represent important trends, methods, and central questions in research on brain and language that encompasses perspectives that include a spectrum of studies in methodology that range from healthy subjects that use one or multiple languages to neurodiversity and neurological disorders. A reader looking to come up to speed on a particular topic in language and the brain need look no further than thorough the list of contributions in this book.

Music & spoken language share many features by combining smaller units (e.g., words, notes) into larger structures (e.g., sentences, musical phrases). This hierarchical organization of sound is culturally contingent & communicates meaning to listeners. Comparisons of music & language from a cognitive neuroscience perspective provide several insights into commonalities & differences between these systems, how they are represented in the brain. The cognitive neuroscience research of music & language, emphasizes the pitfalls & promises identified, including (1) the apparent acoustic & structural similarities between these systems, (2) how both systems convey meaning to listeners, (3) how these systems are learned over the course of development, & (4) the ways in which experience in one domain influences processing in the other domain. We conclude that searching for similarities in how these complex systems are structured (e.g., comparing musical syntax to linguistic syntax) represents a pitfall that researchers should approach with caution. A promising approach in this area of research is to examine how general cognitive mechanisms underlie the learning & maintenance of both systems

Anticipatory processes can influence how quickly comprehenders can process novel linguistic input and how they learn from linguistic surprises. This chapter outlines experimental evidence establishing the psychological reality of anticipatory processes and sketches some contemporary accounts that explain how comprehenders generate predictions from linguistic input. Accounts like Pickering & Gambi’s (2018) formulation suggest that comprehenders covertly engage language production mechanisms to generate predictions about future input and to know when it is time to stop processing current input. Kuperberg and colleagues’ (2021, 2023) formulation lays out a multi-layered network that produces predictions for several different types of linguistic and semantic information (phonological/orthographic, syntactic, lexical, event). N-gram accounts (Brennan, 2020; Hale, 2003, 2016) focus on word predictions and include formal metrics of entropy and surprisal derived from information-theoretic frameworks like Shallice’s. On this account, comprehenders store in long-term memory strings of words (N-grams) and these stored patterns serve as the basis for calculating entropy (how many different continuations are possible at a given point) and surprisal (how likely is a specific word in a specific context). We present a variety of evidence indicating that n-grams may not be the sole or main basis for predictions.

Since the late 1990s, thousands of fMRI studies have been conducted on different aspects of language processing in the human brain. The earlier studies were generally devoted to first language or monolingual processing, but the field has continued to expand to include both studies of a single first language, and bi/multilingual language processing in the brain. A modest number of fMRI longitudinal studies of second language acquisition began to emerge over the past 13 years. The following analysis uses the findings of these BOLD fMRI longitudinal studies of second language acquisition, including comparison with cross-sectional studies of L2 acquisition, to make recommendations for enhancing the research design and empirical measurements to facilitate new methodologies and approaches. Conclusions include a discussion of the utility of longitudinal studies, elucidation of the theoretical foundation of dynamic modeling underlying individual user variation in L1/L2 language processing, inclusion of a broader array of imaging techniques (structural DTI, resting state fMRI and functional connectivity), and the importance of proficiency measurements and proficiency testing as a part of research design.

The emergence of robust accessibility to functional neuroimaging in the late 1990s and early 2000s provided a new way to study language processing in the human brain, the most common techniques being PET and fMRI studies. Prior to this moment, neural language mappings were tied to invasive procedures in surgery and pathology, where CSM (cortical stimulation mapping) was one of the primary sources of data. Reframing approaches to understanding language processing in the brain allowed for closer ties between the cognitive neurosciences and linguistic theory, as well as new perspectives of multimodalities, resting state functional connectivity, and embodied cognition. Here we explore the range of outcomes in functional and structural neuroimaging studies focusing on language processing in the brain, including studies of bi- and multilingualism. The chapter concludes with a discussion of some of the central challenges in neuroimaging studies of language(s), including software and inter-method discrepancies, protocol design, proficiency measurements, and ecological validity.

Language and other cognitive abilities interact with each other in a complex fashion. This interaction affects how we understand and develop models of cognitive function, interpret data reflecting neural activation and connectivity, and diagnose and treat language and cognitive conditions. The goal of this chapter is to provide a cohesive narrative introduction to major cognitive processes and some of the ways in which they interact with language processing. The chapter addresses four key non-linguistic cognitive processes: attention, memory, working memory, and executive function. Each process is discussed in terms of current thinking and prominent models regarding how it functions, its neural substrates, and how it affects and is affected by language function. While the cognitive processes discussed are presented separately, they share underlying relationships, and some models of cognition conceptualize the divisions between constructs differently. This chapter offers a clear but somewhat simplified overview in the interest of providing a basis for conceptualizing the interactive nature of language and other cognitive skills.

This chapter explores the role of functional connectivity (FC), as measured by FMRI, in the neural processes involved in the recovery from aphasia following left hemisphere strokes. It distinguishes between normalization (restoration of typical connectivity patterns) and compensation (reorganization and recruitment of new regions and connections). The chapter organization is based on two methodological dimensions. One is the type of connectivity measured: resting-state vs. task-based FC. The second is the study design: a single time-point scan, examining the correlation between connectivity and language performance across individuals; or a pre/post-treatment design, examining changes in connectivity within participants. While the results of many studies show that normalization of left hemisphere connectivity contributes to language performance, there is also evidence for compensatory processes in both hemispheres and in interhemispheric connectivity, as involved in language recovery. The chapter also highlights the role of connectivity with domain general networks in aphasia studies, beyond the language network. Studies measuring large scale networks show mixed evidence regarding the contribution of integration across networks vs. segregation and specialization of networks to language recovery. The chapter emphasizes the importance of considering factors like patient heterogeneity, lesion characteristics, and the type of FC analysis when interpreting results.

This chapter reviews the current state of knowledge with regards to language control in bilingual aphasia. First, an overview of bilingual language processing and language control in healthy bilinguals is provided. Then, language impairment and recovery patterns in bilingual aphasia are discussed and the influence of language control and linguistic similarity are highlighted. Next, the relationship between bilingual language control and cognitive control is reviewed with attention given to the potential overlap between linguistic and nonlinguistic control mechanisms. Then, case studies and experiments that specifically examine linguistic and nonlinguistic control processes in bilingual aphasia are discussed, focusing on a variety of tasks and methodologies used to examine these processes. Finally, the chapter is concluded by discussing the role of language control in treatment and, specifically, its role in cross-language generalization.

In this chapter, we review what is known about the neural bases of language in, autism spectrum disorder (ASD), focusing on structural and functional investigations in studies of infants, children, and adults. While language impairment is not a core symptom of ASD, most children show significant delays and many continue to experience significant deficits. First, we summarize the range of methods used to investigate brain structure and function in ASD and the challenges in conducting neuroimaging research with this population. Then we survey the research on children and adults to highlight some of the major findings that characterize the neural underpinnings of language in ASD. Since ASD is a neurodevelopmental disorder, there is growing interest in understanding the developmental origins of heterogeneous language profiles. Thus, we then provide a detailed review of this literature, which highlights the very early emergence of atypical neural structure and function in ASD. We end by drawing some tentative conclusions and identifying gaps in the literature that point to future directions for research on language in ASD.