Cerebral cortex最新文献

Neuroimaging research has identified focal differences in the cerebral cortex of individuals with autism spectrum disorder (ASD), particularly in the folds (sulci) within higher-level association cortices. This study examined sulcal patterning and morphology of the anterior cingulate cortex (ACC) in individuals with ASD compared to neurotypical (NT) individuals. We used neuroimaging data from 100 NT and 100 ASD male participants (ages 5 to 18), split into equal discovery and replication samples. Using established criteria, we manually identified the variably present paracingulate sulcus (PCGS), a defining sulcal feature of ACC, in each participant. Quantitative morphological features (length, depth, and cortical thickness mean and standard deviation) were extracted from the PCGS using FreeSurfer. Analyses revealed that, in both samples, NT participants were more likely to have asymmetrical PCGS patterns than ASD participants (controlling for age, IQ, and scanner site). No quantitative morphological features differed between groups. These findings suggest the presence of a variation in the prenatal neurodevelopment of ACC in young males with ASD; however, further research is necessary to uncover the role of this observed difference in the pathogenesis of ASD. The present study also adds to the growing literature implicating variations in PCGS patterning as a trait marker across multiple disorders.

Corticothalamic layer 6 modulates information flow between cortical and thalamic circuits. Previous research reported contrasting inhibitory or excitatory effects of corticothalamic layer 6 on cortical dynamics, potentially reflecting technological discrepancies or physiological differences in corticothalamic layer 6 function. To resolve these discrepancies, we combined translaminar, multi-channel in vivo electrophysiology in the primary somatosensory cortex of anesthetized mice with optogenetic stimulation across a range of stimulation regimes to manipulate firing rate and spiking statistics of corticothalamic layer 6. Increasing corticothalamic layer 6 firing rates exerted a transition from inhibition to excitation across cortical layers. Furthermore, corticothalamic layer 6 activity imparted population synchrony onto distinct cortical subpopulations, independent of changes in overall corticothalamic layer 6 activity. In the thalamus, corticothalamic layer 6 modulated thalamic bursting in a bidirectional manner, dependent on optogenetic stimulation frequency. These results demonstrate that corticothalamic layer 6 in primary somatosensory cortex can bidirectionally modulate both cortical firing and thalamic firing mode, elucidating a more nuanced function of somatosensory corticothalamic layer 6 in thalamic and cortical signaling than previously recognized.

Understanding how differences in brain structure relate to differences in cognition across the lifespan is essential for addressing age-related cognitive decline. Since age is strongly associated with both brain structure and cognition, predictive models often risk simply capturing age effects. To mitigate this risk, deconfounding is typically applied to remove the effects of age. Here, beyond treating age as a confound, we treat it as a moderator by estimating brain-cognition associations separately across age groups. This captures age-stratified changes in how brain structure and cognitive performance are statistically connected. For this view to hold, variations in brain structure linked to differences in cognitive performance in older subjects (eg related to disease) would differ from those in younger subjects. Using structural brain imaging data from the UK Biobank we found an asymmetry in generalisability: models trained on younger subjects successfully predicted cognition in older subjects, but models trained on older subjects failed to generalize to younger individuals. These findings reveal a trade-off between model specificity and generalisability, suggesting the optimal approach-whether age-specific or pooled-depends on the research or clinical goal for the target population.

Human social nature has shaped auditory perception, as hearing is essential for navigating social interactions, especially when listening to others' conversations. While much research has examined how the brain processes isolated words or sentences, far less is known about how broader social and semantic contexts influence speech comprehension. We used 7 T fMRI to examine neural responses while participants listened to two-speaker dialogues versus single-speaker monologues, presented either in intact or sentence-scrambled order. Twenty-four healthy young adults listened to AI-generated five-sentence conversations designed to independently manipulate social (dialogue vs. monologue) and semantic (intact vs. sentence-scrambled) contexts. Whole-brain univariate analyses revealed increased activity for scrambled compared to intact conversations in the left superior temporal sulcus (STS), consistent with predictive-coding models. Although social context alone showed no main effect, an interaction emerged: semantic disruption elicited stronger responses in dialogues than monologues within the STS. Multivariate pattern analyses further revealed higher classification accuracy of individual sentences within dialogues vs. monologues, particularly in the left anterior STS and inferior frontal gyrus, suggesting that social context enhances linguistic encoding. Together, these findings indicate that the left STS integrates both semantic and social information, supporting predictive and context-sensitive mechanisms crucial for real-world verbal communication.

Motor adaptation involves recalibration of well-learned movements in response to sensory or mechanical perturbations. This is believed to rely on internal models-neural representations that predict motor command outcomes-enabling computation of sensory prediction errors. These models support learning generalization, ie application of newly learned movements to new situations, effectors, or state space regions not directly encountered during practice. Prior studies show that focal left posterior parietal cortex lesions impair visuomotor adaptation in both arms, implicating posterior parietal cortex in sensorimotor recalibration. Here, we investigated the posterior parietal cortex's role in visuomotor adaptation and interlimb generalization using anodal high-definition transcranial direct current stimulation (HD-tDCS). Sixty adults performed dominant (right) arm reaches while adapting to a 2D 30° cursor rotation, concurrent with HD-tDCS targeting the left posterior parietal cortex, right posterior parietal cortex, or under sham conditions. Stimulation was then discontinued, and participants repeated the task with their non-dominant (left) arm to assess interlimb generalization. HD-tDCS over left or right posterior parietal cortex had no effect on initial adaptation (P = 0.77). However, left posterior parietal cortex stimulation was associated with enhanced interlimb generalization (P = 0.003) whereas right posterior parietal cortex stimulation was not (P = 0.77). This suggests that anodal transcranial direct current stimulation to contralateral posterior parietal cortex may contribute to interlimb generalization of visuomotor adaptation, rather than adaptation itself.

The coronavirus disease 2019 (COVID-19) pandemic has not only challenged global public health but also generated interest in its neurological basis. A growing number of neuroimaging studies have used quantitative magnetic resonance imaging (MRI) to quantify brain alterations in COVID-19 patients. We conducted a comprehensive review to synthesize brain regions with abnormal MRI metrics of microstructure and function in COVID-19 patients compared to healthy controls. Drawing upon 49 studies sourced from PubMed, Embase, and Web of Science databases, our review showcases structural and functional brain abnormalities across many brain regions in COVID-19. Across multimodal MRI studies, alterations were predominantly in frontal regions, temporal regions, parietal regions, limbic system, and subcortical nuclei. Our findings may help understanding of the neurophysiological basis of acute neurological symptoms and long-term neurological sequelae associated with COVID-19.

Covert visuospatial attention in anticipation of a stimulus is known to topographically modulate alpha-band (8 to 14 Hz) brain activity. However, the specific cortical regions involved remain unclear. Here, we conducted a whole-cortex analysis of alpha-band changes by examining source-level electroencephalographic (EEG) signals during a cued visuospatial attention task via a novel approach integrating conventional alpha power analysis with a deep learning technique based on an interpretable convolutional neural network (CNN). Conventional metrics contrasting alpha power between leftward and rightward attention suggested a robust, selective involvement of the left parietal lobe (superior and inferior parietal cortices) and a broader involvement of right hemisphere regions with less parietal contribution. The CNN-based approach, which discriminated the attention direction from the source-level EEG signals and identified the most discriminative regions in alpha band, refined these findings, corroborating the dominant role of the left parietal lobe and limited involvement of the right parietal lobe restricted to the supramarginal gyrus. The obtained findings are interpreted in terms of a more tonic engagement (disinhibition) of right parietal lobe, leaving less dynamic range for condition-dependent alpha modulation. This study not only improves the characterization of alpha-band attention-related changes but also presents a novel combined approach to investigate brain oscillations.

Neighborhood disadvantage is associated with worse health outcomes and rates of neurodevelopmental disorders. In childhood, experience of greater neighborhood disadvantage is associated with atypical structural and functional brain development, especially within the limbic system. Although these differences are observed throughout the lifespan, there is a profound gap in our understanding of how early neighborhood disadvantage impacts brain development. Using a prospective cohort of 199 healthy pregnancies from around Washington, DC, we performed serial fetal brain MRIs during pregnancy. Using nested linear mixed-effects models, we assess the impact of neighborhood disadvantage on brain volumes throughout fetal development. We found that greater neighborhood disadvantage was associated with significant differences in brain volumes, especially limbic areas. Increases in neighborhood disadvantage were linearly associated with larger volumes earlier in gestation and smaller volumes approaching term age. Importantly, these relationships vary depending on fetal sex, with different regions exhibiting sex-dependent vulnerabilities. These results suggest that even prior to birth, neighborhood disadvantage is associated with altered structural brain development. While the cause of this relationship is unclear, it may stem from the impact of maternal stress and adverse environmental exposures. Our findings provide an important lens to understand the impacts of how socioeconomic inequalities can influence development beginnings prenatally.

Recent models of self-development highlight different rates of development in brain networks underlying emotion and cognition, which may contribute to increased vulnerability to depression and social anxiety disorder during adolescence. Functional magnetic resonance imaging (fMRI) studies suggest age- and affective disorder-related differences in neural activation during self-referential processing (SRP)-a cognitive process central to typical and atypical development. However, findings are mixed, with high methodological variability. We conducted the first activation likelihood estimation meta-analysis of SRP, synthesizing findings from 33 task-based fMRI studies in healthy controls, community samples, and socially anxious or depressed samples to (i) confirm the SRP-related brain network, (ii) examine age- and disorder-related SRP neural correlates, and (iii) explore moderating effects of task features on SRP-related brain activation. Results confirm robust SRP-related activation in core hubs of the default mode network. Nonclinical children, adolescents, and emerging adults showed stronger anterior cingulate cortex activation compared to adults, while adults displayed stronger dorsolateral prefrontal cortex activity across all samples. Clinical samples showed no significant convergence. Findings revealed differential neural convergence depending on task design factors such as comparator choice and stimuli valence. Our findings support developmental maturation of self-representational processes and highlight methodological considerations for future research.

The initial therapeutic exposure to Deep Brain Stimulation (DBS) during implantation surgery has reproducible acute behavioral effects that carry over without further stimulation. We analyzed local field potential (LFP) data from the first month following brief therapeutic intraoperative DBS. Data were recorded from the subcallosal cingulate cortex. During this month, no further stimulation was applied. Recent studies have identified beta power fluctuations in LFP data as an acute putative depression biomarker of this exposure. However, a detailed description of neural dynamics underlying brain power fluctuations is missing. Here, we consider how these fluctuations are related to brain itinerancy, that is, neural activity changes between stable and unstable states. We also provide a proof of principle study that these dynamics can be described using 2 new dynamical systems measures: instability frequency and relative wandering time. These capture interactions between neural activity and the mesoscale oscillatory electric fields generated by it. The 2 measures seem to split low vs. high Hamilton Depression Rating Scale scores within a small patient cohort. They are motivated by the cytoelectric coupling hypothesis, which suggests that efficient information processing results from mesoscale electric fields and that the re-emergence of depression symptoms might result from altered electric fields. Whether the new measures reflect general mechanisms of rapid antidepressant action remains to be tested.