Cerebral Cortex

Early-life painful events can influence brain development and behaviour later in life, yet the neural mechanisms underlying these long-term effects remain poorly understood. In particular, exposure to pain or tissue injury during early postnatal life has been associated with altered sensory processing, emotional regulation and behavioural responses later in life. Here we investigated whether early-life surgical pain alters adult behavioural and cortical network responses to injury. Using a rat model of neonatal hindpaw incision followed by repeat adult surgical incision, we combined behavioural analysis with continuous electrophysiological recordings from the medial prefrontal cortex (mPFC) and primary somatosensory cortex (S1) in freely moving animals. Early-life incision did not produce an overt alteration in adult social behaviour under baseline conditions. However, following adult injury, rats with prior neonatal incision showed altered social behavioural responses compared with animals receiving an incision only in adulthood. At the network level, adult incision increased beta-gamma phase-amplitude coupling within the mPFC and S1-mPFC theta coherence in animals experiencing their first injury, but not in those incised neonatally. Our evidence indicates that the relationship between mPFC coupling and social interaction differed according to neonatal injury history, revealing a lasting reorganisation of cortical network recruitment and brain-behaviour coupling after repeat injury.

Higher order association cortices like the prefrontal cortex (PFC) mature over a longer developmental window than sensory cortices, but whether genetically defined interneuron populations follow this region-wide delayed trajectory remains unclear. We compared the postnatal development of somatostatin-expressing interneurons in a higher-order cortical region (prelimbic cortex; PLC) and a sensory cortical region (somatosensory barrel cortex; S1BF) across adolescence using complementary structural, electrophysiological, and circuit analyses. We found that the maturation of SST neurons within these two cortical regions differs across time. S1BF SST neurons exhibited relatively linear maturation, whereas PLC SST neurons underwent continued dendritic remodeling, nonlinear intrinsic maturation, and age-dependent refinement of inhibitory output onto pyramidal neurons. Multivariate analyses likewise supported a more linear developmental trajectory in S1BF and a more prolonged, heterogeneous trajectory in PLC. This suggests divergent maturation of the PLC and S1BF and supports a broader, longer window of critical cellular plasticity in the PLC than in sensory cortices. Together, this reflects an extended developmental program at the level of a genetically defined inhibitory cell type. Because SST neurons are positioned to regulate pyramidal neuron output via control of dendritic integration, their delayed maturation is a crucial reflection of overall circuit function. These findings provide a cellular framework for the prolonged plasticity and developmental vulnerability known to be characteristic of adolescent prelimbic cortex. Significance statementWithin the brain, higher order association cortex remains plastic long after sensory cortex has matured, but the cellular basis for this prolonged developmental window has remained unknown. We find that developmental timing is encoded within genetically defined microcircuits. Prelimbic somatostatin circuits continue to remodel after sensory somatostatin circuits have largely stabilized through changes in cell shape, action potential firing dynamics, and inhibitory signaling. This work points to a specific prelimbic inhibitory cell type that matures more slowly, and less linearly, than its counterparts in other brain regions, and may help explain why prelimbic circuits remain vulnerable during adolescence, representing a biological substrate for extended adolescent remodeling in prelimbic cortex, and potentially the overall extensive flexibility, but also cognitive susceptibility, seen during adolescence.

Some participants are consistently easier to decode than others. We asked whether this difference belongs to the person or to the conditions under which the brain is measured. We compared visual decoding in EEG, MEG, intracranial EEG, and fMRI, testing classifiers on runs and stimulus identities excluded from training. Within-instrument decoding was reproducible. Attention, behavior, and peripheral signals affected recording quality but did not explain most of the stable differences between participants. Anatomy provided one explanation. Source-to-sensor distance strongly predicted modeled signal gain, and its effect was steepest in planar gradiometers. Intracranial recordings provided another: participants with sharper local category selectivity were easier to decode. This association chiefly reflected a smaller response to the nonpreferred category relative to overall visual responsivity. Cross-site prediction was uneven. EEG and MEG expressed the preferred and nonpreferred responses differently. MEG category separation and task-aligned variance described the information available to the decoder. Simultaneous EEG-MEG recordings contained a shared participant component, but external paired cohorts did not yield a common ordering across instruments. Correspondence depended on the measure, the instrument pair and, in one cohort, participant-linked stimulus sets. Repeated observations improved performance in participants with weak single-observation decoding. Stable decoding differences therefore reflect the relation between the individual, the represented distinction, and the instrument. They chiefly determine how much information a recording supplies per observation.

Music and language share many similarities, yet music does not elicit a response in the language brain areas in adults with typical amounts of music experience, and patients with aphasia show preserved music ability. However, this dissociation might not generalize across development or expertise: it may not yet be present in children, who have limited experience with language and music, or it may be diminished in musicians with extensive music training. To evaluate these possibilities, we here used a precision fMRI approach to examine the responses in the language areas of children (aged 4-16 years, n=80) and adult musicians (n=10) to music. We found that the results obtained previously for non-musician adults replicate in two new control samples and, critically, generalize to both of the newly tested populations: the language areas are already selective for language relative to music in young children, showing no age-related change from early to late childhood, and remain selective despite extensive music training in highly experienced musicians. Thus, it appears that the amount of music exposure and practice have little effect on how the language brain areas respond to music.

The neural substrates of tactile long-term memory (LTM) in humans remain poorly understood, as relatively few neuroimaging studies have addressed this question. Here, we asked whether retrieval of tactile stimulation engages modality-specific representations in the primary and secondary somatosensory cortices (S1 and S2), alongside domain-general retrieval networks. Participants learned 16 tactile trajectories, each presented for 1.2 s on the left thumb through sequential activation of 10 vibrating dots on a Braille-like display. Three learning sessions within one week were followed by a recognition test during functional magnetic resonance imaging (fMRI). In the final sample (n = 26), we contrasted BOLD responses during successful recognition of learned stimuli with those during correct rejection of novel stimuli. Successful recognition was associated with increased activity in contralateral S1 and S2, alongside activation in the hippocampus as well as frontal and parietal regions implicated in memory retrieval. A psychophysiological interaction analysis (PPI) further revealed increased task-dependent connectivity between the hippocampus and contralateral S1 and S2 during successful recognition. Together, these findings suggest that tactile long-term memory retrieval relies on coordinated hippocampal-somatosensory interactions and may engage long-term memory representations in somatosensory cortex.

The cerebellum has long been considered a late-maturing structure subordinate to neocortical development, therefore its potential role as an early driver of cortical organization remains largely unexplored. Using two large longitudinal neuroimaging cohorts of developing children together with lesion experiments in mice, we show that early cerebellar morphology may drive neocortical maturation in a regionally specific manner. These cross-species findings implicate the cerebellum as a possible regulator of neocortical organization.

For more than a century we have pictured the dendritic spine as the postsynaptic point where a single presynaptic bouton delivers its message. That picture is correct but incomplete, since it overlooks other neuronal elements surrounding each spine. Here we characterize that neighborhood for the first time by counting and measuring the proximity of the elements encircling each postsynaptic spine. We call this neighborhood the vicinome: the full set of neuronal and glial elements surrounding a dendritic spine. We used ground-truth three-dimensional meshes from the H01 petavoxel dataset, a reconstruction of the human cerebral cortex. We analyzed 4550 neighboring elements across 322 spines from 17 pyramidal neurons in cortical layers 2 through 5, with each spine classified as apical or basal. Neighbor number followed a depth gradient, falling from 17.2 {+/-} 4.2 elements per spine in layer 2 apical spines to 12.5 {+/-} 3.1 in layer 5 basal spines. A linear mixed model with a random intercept per neuron confirmed a strong effect of layer (p = 4.3 x 10-5) with large effect sizes (Cohen's d up to 1.45) and no effect of polarity. The minimum spine-to-neighbor distance stayed uniform, near 30 nm in every group, and although some depth-related contrasts were significant, all effect sizes were negligible (Cohen's d below 0.21). We conclude that cortical depth, and not pyramidal neuron polarity, was related to the number of neuronal elements neighboring the spine. We suggest that vicinome crowding could offer a measurable observable for comparison across regions, ages, species, and disease.

The Component Process Model of Emotion conceptualizes any emotional episode (e.g., the discrete emotions of sadness, anger, fear, or interest) as being driven by the multiple appraisal components. However, both the specificity of the neural mechanisms underlying appraisal processes and the way these appraisal networks relate to the neural circuits underlying discrete emotions remain unclear. Here we investigated the neural correlates of appraisal processes and compared them with those of discrete emotions. Participants (n = 97) were scanned with functional magnetic resonance imaging (fMRI) while watching short movie clips with varying emotional contents. Intensity for 12 appraisals and 12 basic and epistemic emotions evoked by the movie clips were rated by independent participants (n = 444). The neural responses were modelled with convolved ratings of appraisals and discrete emotions. The results indicated that appraisals and discrete emotions are supported by a shared set of distributed brain regions that extend beyond typically reported emotion-related areas, encompassing perceptual, action-related, and higher-order cognitive systems. Activations were more consistent for and better explained by appraisals versus discrete emotions. Within this network, epistemic emotions elicited less consistent activations than basic emotions, particularly in limbic regions. Our results highlight the functional organization of appraisals and discrete emotions under dynamic and complex conditions and indicate that appraisal theories better explain neural responses than discrete emotion models.

Human social perception relies on multiple visual signals, including object-directed actions and emotional facial expressions. It remains unclear whether responses to these signals converge within action-observation regions and whether apparent convergence depends on the spatial scale of analysis. We scanned 39 healthy human adults during two block-design fMRI tasks, hand action observations contrasted with paper-tube controls, and emotional expression observations contrasted with neutral faces. Using independently defined meta-analytic action observation network (AON) ROIs in the inferior frontal gyrus (IFG), inferior parietal lobule (IPL), and posterior superior temporal sulcus (pSTS), we analysed responses at whole-brain, ROI-average, and AON-constrained voxelwise scales. Whole-brain overlap between the two contrasts was localised primarily to the left lateral occipitotemporal extrastriate cortex, outside the AON. At the regional ROI-average scale, the IFG showed positive responses to both contrasts, whereas the IPL and pSTS showed opposing task preferences. Crucially, regional IFG co-engagement did not imply that the same voxels responded to both contrasts. Suprathreshold voxelwise overlap within the AON was virtually absent, and individual-level analysis revealed a small but reliable posterior displacement of hand action relative to emotional face within IFG. These findings show that spatial convergence between hand and emotion observation responses depends on the scale of analysis. The same IFG region can be engaged by both stimulus domains while retaining distinct local response topographies.

High-level visual cortex supports the perception and recognition of visual categories. What is the role of experience in shaping this region and the time course over which it stays malleable? We tested whether experience with a sign language, where information is conveyed via the hands and face, shapes category representations in high-level visual cortex. We acquired functional MRI data from 20 hearing signers and 20 non-signers while they viewed images from ten categories, including faces and hands. We compared the neural distinctiveness and size of category-selective regions between groups in ventral temporal and lateral occipito-temporal cortex. Signers showed higher distinctiveness for hands and larger hand-selective regions than non-signers in the left hemisphere, and sign language experience predicted neural hand representations. Critically, ventral hand representations were also enhanced in signers who learned sign language in adulthood. These findings indicate that visual cortex retains experience-dependent plasticity into adulthood, with implications for visual learning and cortical development.

Working memory (WM) and decision-making (DM) are closely linked cognitive processes that rely on frontoparietal regions, yet their distinct and shared neural dynamics remain unclear. Using intracranial EEG recordings from 24 human subjects performing a delayed match-to-sample task, we examined high-frequency broadband (HFB) activity to dissociate WM- and DM-related processes with high spatiotemporal resolution. Principal component analysis of frontoparietal HFB activity revealed multiple temporally distinct patterns spanning stimulus presentation and delay phases. The most dominant component reflected sustained WM-related activity across task phases, consistent with persistent maintenance of internal representations. Additional components captured transient WM encoding across trial phases, as well as both stimulus-linked and ramping DM-related activity suggesting dual early and late stages of evaluative processing. These processes were distributed across frontoparietal regions but showed systematic differences in anatomical focus, with WM-related activity concentrated in dorsolateral prefrontal cortex (PFC) and DM-related activity concentrated in ventrolateral PFC, while inferior parietal cortex preferentially tracked the behavioral significance of incoming stimuli and superior parietal cortex tracked the appearance of new information that may require updating ongoing processing. Together, these findings demonstrate that WM and DM processes are separable yet interleaved over time within distributed cortical networks, revealing coordinated but functionally distinct contributions to goal-directed behavior.

Face familiarity elicits reliable neural signatures during perception, yet how it is represented when faces are recalled from memory by using visual imagery and how these signals relate to perceptual representations, remains unclear. We combined perceptual and imagery conditions with electroencephalography and multivariate pattern analysis. In a perceptual session we presented of four famous individuals, while in the imagery session we used a cued recall paradigm and presented abstract symbols, associated to them. By using time-resolved multivariate decoding we tested if familiarity information is shared across stimulus categories, and if perceptual face familiarity representations overlap with processing during cued recall, related to imagery. The face perception condition showed typical and robust familiarity information over occipito-temporal electrodes. The symbolic cues also carried similar familiarity information, demonstrating cross-category familiarity processing between symbols and faces. During cued recall, familiarity information emerged over posterior regions and evolved into a prolonged and late information component over right anterior electrodes. Importantly, cross-domain temporal generalization analysis revealed an overlap between perceptual face familiarity patterns and recall/imagery related processing: perceptual face familiarity information mapped onto later processing during cued recall, with a pronounced and prolonged right anterior dominance and a shorter overlap over left posterior channels. Together, these results suggest that familiarity processing, similarly to category representations, is supported by overlapping neural patterns across perception and recall/imagery, transitioning from dynamic posterior representations, consistent with perceptual analysis, to a stable and prolonged representation over right anterior sites, that is compatible with a sustained processing, related to recall and/or imagery.

Genome-wide association studies (GWAS) have identified hundreds of common genetic variants associated with regional brain volumes, enabling the construction of polygenic scores (PGS) that summarize genetic predisposition for variation in specific neuroanatomical traits. To investigate how these genetic influences are exerted spatially throughout the brain, we computed PGS for ten brain volume phenotypes, including nine major subcortical structures and intracranial volume. Each locus was weighted by its estimated GWAS effect size on regional volume in the original GWAS. In an independent, non-overlapping sample of 2,830 UK Biobank participants, we performed whole-brain voxel-based morphometry (VBM) analyses of 3D volumetric brain MRI to reveal voxel-wise associations between each PGS and modulated gray matter volume (GMV). To probe genetic effects across multiple spatial scales, analyses were repeated across Gaussian smoothing kernels ranging from 2-mm to 12-mm full-width at half-maximum (FWHM). Several PGS demonstrated highly significant associations with GMV, including localized effects in the hippocampus, amygdala, thalamus, and basal ganglia, whereas the brainstem PGS showed more widespread associations throughout the brain. For most of the PGS, the fraction of voxels surviving the false discovery rate (FDR) correction increased with increasing FWHM. Peak voxel-wise significance was often strongest at intermediate smoothing levels. Hippocampal significance maps showed progressively larger regions of significant signal at higher smoothing levels, and subsampling showed that detectable signal remained present even with substantial reductions in sample size. These findings suggest that genetic influences on brain morphology are expressed across multiple spatial scales, with consequences that may help to guide the design of deep learning methods to discover genomic loci associated with brain structure and brain diseases.

Social isolation and loneliness are major determinants of well-being in older adults. Shrinking social networks and age-related shifts in social behavior and decision-making may increase vulnerability to loneliness. These changes in social decision-making strategies can be conceptualized within an exploration-exploitation tradeoff framework, in which social options with known outcomes are prioritized over uncertain ones. Yet, no study has characterized how complementary decision-making strategies, undirected novelty seeking and goal-directed exploration, relate to social network constructs or are supported by distinct neural systems. These strategies capture distinct forms of decision-making: undirected novelty seeking is driven by the intrinsic salience of novel options independent of expected informational gain, whereas goal-directed exploration involves deliberately sampling uncertain options to reduce uncertainty and optimize future choices. Here, we used fMRI and a novel social bandit reinforcement task to identify dissociable social constructs and brain systems linked to undirected novelty seeking and goal-directed exploration in older adults. Undirected novelty seeking was associated with social network size and with activity of temporoparietal and mid-cingulate brain areas. Goal-directed exploration predicted subjective feelings of social connectedness and was associated with activity of anterior cingulate and prefrontal brain areas. Crucially, choice probabilities from a non-social version of the three-arm bandit task were not associated with social decision-making nor with social constructs. Our findings suggest that, in later life, dissociable social decision-making strategies, when faced with unknown options, rely on distinct neural systems supporting social network size as well as subjective feelings of social connectedness.

Irony and sarcasm are complex forms of non-literal language that hinge on a misalignment between surface meaning and speaker intent, requiring listeners to integrate contextual, semantic, and prosodic cues. While prior neuroimaging studies have implicated a broad network--including the temporal cortex, the inferior frontal gyrus, and the medial prefrontal cortex--in the comprehension of ironic and sarcastic speech, the precise neural mechanisms underlying the integration of semantic and prosodic information remain unclear. In the present study, we addressed this gap by employing voxel-wise encoding models to systematically identify brain regions specifically involved in combining prosodic and semantic cues during non-literal language comprehension. Participants listened to naturalistic auditory dialogues in which both discourse context and target utterance semantics and prosody were systematically manipulated. We derived custom text embeddings using transformer-based models to capture context-sensitive semantic representations of ironic statements, alongside acoustic features characterizing affective prosody. Ridge regression models were fitted to predict BOLD responses at the voxel level using semantic, prosodic, and combined features, and we identified integration as voxels in which each modality contributed predictive information beyond the other, using a permutation-based conjunction test. The regions integrating prosody and semantics depended on whether discourse context was modeled: integration was confined to the bilateral temporal speech cortex when statements were encoded in isolation, but additionally engaged the left inferior frontal gyrus pars orbitalis (IFGorb) when each statement was weighted by its relevance to the preceding context. These findings indicate that the left IFGorb integrates prosody with context-dependent meaning, engaging beyond the temporal speech cortex specifically when comprehension requires combining semantic, prosodic, and contextual cues--as in irony and sarcasm.

Decades of developmental memory research has mainly reported linear and protracted changes in both human hippocampal function and connectivity between the hippocampus and cortex. While foundational, very few studies have interrogated the reliability of hippocampal signals across age, and how this coincides with (or diverges from) age-related changes in connectivity to broader cortical networks supporting multiple memory systems. Here, utilizing movie-watching fMRI data in children 3 to 12 years and adults, we assessed hippocampal response stability using an inter-subject functional correlation (ISFC) approach, and then measured functional connectivity between the hippocampus and the Posterior Medial (PM) - Anterior Temporal (AT) cortical memory networks proposed to support episodic-like (PM) and semantic-like (AT) memory respectively. Results showed that hippocampal responses are stable in the youngest children, but bifurcate in 7 year olds, with half the subjects correlating most highly with younger and half with older age groups. Likewise, we found that while functional connectivity within the AT network is stable across development, connections between the anterior hippocampus and this network did not reach adult levels until around 7 years. Thus, while brain networks supporting semantic memory may be in place early, interactions with the hippocampus may not develop until after middle childhood, with an inflection point around 7 years of age.

Episodic memory critically depends on the hippocampal-entorhinal system. Despite a rapid developmental change in human episodic memory during the first two years of life, little is known about the developmental trajectory of the hippocampal-entorhinal circuitry during this critical time period. In the current study, we collected high-quality precision fMRI data from five typically developing infants over the time period between 1 and 2 years of life and examined the cortical networks associated with subregions of the hippocampal-entorhinal system. We show that already at around 1 year of age, subdivisions of the canonical default network (DN) are dissociated at the neocortex but are differently associated with the hippocampal-entorhinal system, with tentatively differential developmental trajectories. While the DN-A, associated with episodic simulation, coupled with the anterior hippocampus and the medial part of the entorhinal cortex, the DN-B, associated with social cognition, showed weaker connectivity with the hippocampal-entorhinal system. The parietal memory network, in turn, coupled with the posterior hippocampus and the lateral part of the entorhinal cortex. Exploratory longitudinal results suggest that associations of the DN-B with the hippocampus and the intermediate part of the entorhinal cortex increase towards the end of the second postnatal year, and the associations of the parietal memory network become more topographically restricted to the posterior hippocampus. These networks and their differential maturation may provide the basis for important developments in episodic memory and social cognition in the second postnatal year and suggest that potentially unique properties of human hippocampal-entorhinal circuitry may emerge latest in development.

The coordination of sensory processing and working memory (WM) is fundamental to cognition. Spatial organization of sensory processing and WM is known to be broadly distributed across the cortex, but finer-scale organization at the interfaces between these functions remains understudied. Although the notion of sharp parcellations of cortex into distinct functional modules dominates the field, a growing body of works support graded changes in function and anatomy in some cortical zones. Based on this and potential advantages of gradient organizational structure in frontal cortex, we hypothesized that sensory-WM interfaces in the frontal cortex are gradient-like, not boundary-like. We examined twenty bilateral cortical regions that participate in visual/auditory WM tasks. In five frontal cortical regions, group-level WM activation overlapped with sensory drive, but was spatially shifted. We compared subject-level (N=20) boundary and gradient models of change in function. Strong individual-level evidence for sensory-WM gradients was observed in pre-supplementary motor area, ventral premotor cortex, and anterior insula in both modalities and in dorsal premotor cortex for visual WM. Conversely, dorsolateral pre-frontal cortex yielded mixed results, favored distinct WM and sensory regions in the left hemisphere, and gave some evidence for gradients in the right hemisphere. These results provide evidence that sensory and WM regions in frontal cortex are largely not distinct with sharp boundaries at their interfaces but instead bleed into each other to form local rostral-caudal sensory-WM gradients. We speculate these gradients may allow efficient interfacing between sensory and WM representations, and/or fine-grained, task-dependent shifting between bottom-up sensory and top-down influences.

Neural encoding of acoustic and linguistic features of continuous speech is sensitive to cognitive factors, such as attention and comprehension. We investigated whether neural tracking is also sensitive to the predictability of speech. Participants were repeatedly exposed to intelligible or unintelligible versions of the same audiobook segment while EEG was recorded. First, we fit encoding models to predict EEG responses from acoustic, sublexical, and lexical features of the presented speech. Model comparisons revealed no reliable improvement in model fit when lexical features were included; subsequent analyses were performed on models including only acoustic and sublexical predictors. Second, we compared prediction accuracy for models trained and tested on the same exposures with models trained and tested across different exposures. While we observed no overall change in prediction performance across exposures, we found that models were exposure-specific: prediction performance was highest within the same exposure and decreased with increasing temporal distance between the training and test exposure. This effect was observed for intelligible but not for unintelligible speech, suggesting that the effect depends on properties unique to intelligible speech, such as the ability to form increasingly specific predictions about upcoming linguistic input, rather than general, non-linguistic factors related to repeated exposure. This distance effect was associated with increased model weights from -90 ms to 130 ms, indicating an enhancement of familiar input during an early cortical processing stage. In summary, these findings indicate that cortical tracking of sublexical speech features is modulated by repeated exposure to intelligible speech, consistent with a role for linguistic predictability.

The human brain must rapidly construct hierarchical structures to organize complex sequential behavior, yet the neural dynamics supporting this process during natural behavior remain poorly understood. Spoken language provides a powerful model system for investigating this computation, requiring rapid transformation of conceptual intent into structured sequential output. Using rare intracranial stereo-electroencephalography (SEEG) recordings from patients producing extended spontaneous speech, we examined how syntactic planning unfolds over time using measures of constituency, dependency structure, and probabilistic syntactic categories. We identified a hierarchical planning architecture in which global sentence structure and core syntactic categories (nouns and verbs) were specified before more local planning operations. Neural representations of these categories emerged up to 1 s before articulation and persisted throughout the planning period, whereas optional modifiers, including adjectives and adverbs, were recruited only closer to speech onset. These observations support a model of hierarchical incremental planning in which abstract sentence structure precedes the incremental specification of individual sentence elements. While core syntactic categories engaged a broader fronto-temporo-parietal network than other word classes, syntactic-depth-related activity emerged in parallel across cortical regions and the hippocampus, suggesting that hippocampal relational representations contribute to sentence structure building. Together, these findings support a cortico-hippocampal model of speech production in which hierarchical sentence structure and core syntactic categories are planned before secondary syntactic elements are incrementally incorporated into the evolving sentence plan. These results provide a neural account of how abstract linguistic structure is transformed into fluent speech.