Stress and depression have a reciprocal relationship, but the neural underpinnings of this reciprocity are unclear. We investigated neuroimaging phenotypes that facilitate the reciprocity between stress and depressive symptoms.

In total, 22 195 participants (52.0% females) from the population-based UK Biobank study completed two visits (initial visit: 2006–2010, age = 55.0 ± 7.5 [40–70] years; second visit: 2014–2019; age = 62.7 ± 7.5 [44–80] years). Structural equation modeling was used to examine the longitudinal relationship between self-report stressful life events (SLEs) and depressive symptoms. Cross-sectional data were used to examine the overlap between neuroimaging correlates of SLEs and depressive symptoms on the second visit among 138 multimodal imaging phenotypes.

Longitudinal data were consistent with significant bidirectional causal relationship between SLEs and depressive symptoms. In cross-sectional analyses, SLEs were significantly associated with lower bilateral nucleus accumbal volume and lower fractional anisotropy of the forceps major. Depressive symptoms were significantly associated with extensive white matter hyperintensities, thinner cortex, lower subcortical volume, and white matter microstructural deficits, mainly in corticostriatal-limbic structures. Lower bilateral nucleus accumbal volume were the only imaging phenotypes with overlapping effects of depressive symptoms and SLEs (B = −0.032 to −0.023, p = 0.006–0.034). Depressive symptoms and SLEs significantly partially mediated the effects of each other on left and right nucleus accumbens volume (proportion of effects mediated = 12.7–14.3%, p < 0.001−p = 0.008). For the left nucleus accumbens, post-hoc seed-based analysis showed lower resting-state functional connectivity with the left orbitofrontal cortex (cluster size = 83 voxels, p = 5.4 × 10−5) in participants with high v. no SLEs.

The nucleus accumbens may play a key role in the reciprocity between stress and depressive symptoms.

Obsessive–compulsive disorder (OCD) is a classic disorder on the compulsivity spectrum, with diverse comorbidities. In the current study, we sought to understand OCD from a dimensional perspective by identifying multimodal neuroimaging patterns correlated with multiple phenotypic characteristics within the striatum-based circuits known to be affected by OCD.

Neuroimaging measurements of local functional and structural features and clinical information were collected from 110 subjects, including 51 patients with OCD and 59 healthy control subjects. Linked independent component analysis (LICA) and correlation analysis were applied to identify associations between local neuroimaging patterns across modalities (including gray matter volume, white matter integrity, and spontaneous functional activity) and clinical factors.

LICA identified eight multimodal neuroimaging patterns related to phenotypic variations, including three related to symptoms and diagnosis. One imaging pattern (IC9) that included both the amplitude of low-frequency fluctuation measure of spontaneous functional activity and white matter integrity measures correlated negatively with OCD diagnosis and diagnostic scales. Two imaging patterns (IC10 and IC27) correlated with compulsion symptoms: IC10 included primarily anatomical measures and IC27 included primarily functional measures. In addition, we identified imaging patterns associated with age, gender, and emotional expression across subjects.

We established that data fusion techniques can identify local multimodal neuroimaging patterns associated with OCD phenotypes. The results inform our understanding of the neurobiological underpinnings of compulsive behaviors and OCD diagnosis.

Impaired self-awareness of cognitive deficits (ISAcog) has rarely been investigated in Parkinson's disease (PD). ISAcog is associated with poorer long-term outcome in other diseases. This study examines ISAcog in PD with and without mild cognitive impairment (PD-MCI), compared to healthy controls, and its clinical-behavioral and neuroimaging correlates.

We examined 63 PD patients and 30 age- and education-matched healthy controls. Cognitive state was examined following the Movement Disorder Society Level II criteria. ISAcog was determined by subtracting z-scores (based on controls' scores) of objective tests and subjective questionnaires. Neural correlates were assessed by structural magnetic resonance imaging (MRI) and 2-[fluorine-18]fluoro-2-deoxy-d-glucose-positron emission tomography (FDG-PET) in 47 patients (43 with MRI) and 11 controls. We analyzed whole-brain glucose metabolism and cortical thickness in regions where FDG-uptake correlated with ISAcog.

PD-MCI patients (N = 23) showed significantly more ISAcog than controls and patients without MCI (N = 40). When all patients who underwent FDG-PET were examined, metabolism in the bilateral superior medial frontal gyrus, anterior and midcingulate cortex negatively correlated with ISAcog (FWE-corrected p < 0.001). In PD-MCI, ISAcog was related to decreased metabolism in the right superior temporal lobe and insula (N = 13; FWE-corrected p = 0.023) as well as the midcingulate cortex (FWE-corrected p = 0.002). Cortical thickness was not associated with ISAcog in these regions. No significant correlations were found between ISAcog and glucose metabolism in controls and patients without MCI.

Similar to Alzheimer's disease, the cingulate cortex seems to be relevant in ISAcog in PD. In PD-MCI patients, ISAcog might result from a disrupted network that regulates awareness of cognition and error processes.