BrainStat: A toolbox for brain-wide statistics and multimodal feature associations

Transcriptional substrates of cortical thickness alterations in anhedonia of major depressive disorder

BACKGROUND

Anhedonia is a core symptom of major depressive disorder (MDD), which has been shown to be associated with abnormalities in cortical morphology. However, the correlation between cortical thickness (CT) changes with anhedonia in MDD and gene expression remains unclear.

METHODS

We investigated the link between brain-wide gene expression and CT correlates of anhedonia in individuals with MDD, using 7 Tesla neuroimaging and a publicly available transcriptomic dataset. The interest-activity score was used to evaluation MDD with high anhedonia (HA) and low anhedonia (LA). Nineteen patients with HA, nineteen patients with LA, and twenty healthy controls (HC) were enrolled. We investigated CT alterations of anhedonia subgroups relative to HC and related cortical gene expression, enrichment and specific cell types. We further used Neurosynth and von Economo-Koskinas atlas to assess the meta-analytic cognitive functions and cytoarchitectural variation associated with anhedonia-related cortical changes.

RESULTS

Both patient subgroups exhibited widespread CT reduction, with HA manifesting more pronounced changes. Gene expression related to anhedonia had significant spatial correlations with CT differences. Transcriptional signatures related to anhedonia-associated cortical thinning were connected to mitochondrial dysfunction and enriched in adipogenesis, oxidative phosphorylation, mTORC1 signaling pathways, involving neurons, astrocytes, and oligodendrocytes. These CT alterations were significantly correlated with meta-analytic terms involving somatosensory processing and pain perception. HA had reduced CT within the somatomotor and ventral attention networks, and in agranular cortical regions.

LIMITATIONS

These include measuring anhedonia using interest-activity score and employing a cross-sectional design.

CONCLUSIONS

This study sheds light on the molecular basis underlying gene expression associated with anhedonia in MDD, suggesting directions for targeted therapeutic interventions.

Association of APOC1 with cortical atrophy during conversion to Alzheimer's disease

Alzheimer's disease (AD) is a prevalent neurodegenerative disorder, with its progression influenced by aberrant gene expression and alterations in the brain network topology. Although APOE has been extensively studied in relation to AD, the role of APOC1 remains relatively underexplored. This study investigated the impact of APOC1 on changes in cortical thickness (CTh) during conversion to AD in a longitudinal setting. Using a normative modeling approach, we examined changes in CTh in patients with mild cognitive impairment (MCI). The spatial patterns of CTh changes were then correlated with APOC1 mRNA expression levels. We estimated the time to conversion to AD and compared progression rates between the low and high APOC1 expression groups. Finally, mediation analysis was performed to assess the indirect effects of APOC1 expression on memory function via CTh changes. In patients with MCI and AD, reduced CTh was observed in the limbic and default mode regions, with a notable impact on the entorhinal cortex, parahippocampus, and fusiform gyrus when comparing baseline and follow-up measurements. The degree of change in CTh was significantly associated with APOC1 expression, with the paralimbic regions identified as particularly vulnerable. Furthermore, the high APOC1 expression group demonstrated more rapid conversion to AD than that observed in the low expression group. Mediation analysis indicated a trend suggesting that APOC1 expression indirectly affected memory and cognitive function through its influence on CTh. These results highlight the potential of APOC1 as an additional focus of AD research, offering insights into the genetic influences on AD pathology.

Disrupted Hierarchical Functional Brain Organization in Affective and Psychotic Disorders: Insights from Functional Brain Gradients

Patients with psychosis and depression show widespread alterations in brain resting-state functional connectivity (rs-FC), affecting both sensory and higher-order brain regions. In this study, we investigate disruptions in the hierarchical organization of brain functional networks in patients with psychotic and affective disorders. We derived functional brain gradients, low dimensional representations of rs-FC that capture cortical hierarchy, in a large patient sample including clinical high-risk for psychosis (CHR-P) patients, recent-onset psychosis (ROP) patients, recent-onset depression (ROD) patients, and healthy controls (HC). We examined regional alterations, network-level alterations and functional differentiation and their relationship to clinical symptoms. In addition, we linked case-control differences to receptor expression maps to explore underlying neurobiological mechanisms. All patient groups exhibited alterations in the visual-to-sensorimotor gradient, while only ROP patients showed alterations in the association-to-sensory gradient. CHR-P and ROP patients exhibited lower values in the ventral attention network. Additionally, patients combined showed higher values in the somatomotor network, a reduced gradient range and altered between-network dispersion. ROD showed reduced within-network dispersion in the attentional networks and a reduced range. Correlational analysis revealed weak associations of gradient measures with functioning, visual dysfunctions and cognition. Furthermore case-control differences showed associations to receptor expression maps, suggesting the involvement of neurotransmitter systems in these disruptions. Our findings reveal transdiagnostic and disease-specific alterations of hierarchical brain organization. These alterations indicate deficits in functional integration across psychiatric diseases, highlighting the role of attentional and sensory networks in disease processes.

Atypical maturation of the functional connectome hierarchy in autism

BACKGROUND

Autism spectrum disorder (ASD) is marked by disruptions in low-level sensory processing and higher-order sociocognitive functions, suggesting a complex interplay between different brain regions across the cortical hierarchy. However, the developmental trajectory of this hierarchical organization in ASD remains underexplored. Herein, we investigated the maturational abnormalities in the cortical hierarchy among individuals with ASD.

METHODS

Resting-state functional magnetic resonance imaging data from three large-scale datasets were analyzed: Autism Brain Imaging Data Exchange I and II and Lifespan Human Connectome Project Development (aged 5-22 years). The principal functional connectivity gradient representing cortical hierarchy was estimated using diffusion map embedding. By applying normative modeling with the generalized additive model for location, scale, and shape (GAMLSS), we captured the nonlinear trajectories of the developing functional gradient, as well as the individual-level deviations in ASD from typical development based on centile scores measured as deviations from the normative curves. A whole-brain summary metric, the functional hierarchy score, was derived to measure the extent of abnormal maturation in individuals with ASD. Finally, through a series of mediation analyses, we examined the potential role of network-level connectomic disruptions between the diagnoses and deviations in the cortical hierarchy.

RESULTS

The maturation of cortical hierarchy in individuals with ASD followed a non-linear trajectory, showing delayed maturation during childhood compared to that of typically developing individuals, followed by an accelerated "catch-up" phase during adolescence and a subsequent decline in young adulthood. The nature of these deviations varied across networks, with sensory and attention networks displaying the most pronounced abnormalities in childhood, while higher-order networks, particularly the default mode network (DMN), remaining impaired from childhood to adolescence. Mediation analyses revealed that the persistent reduction in DMN segregation throughout development was a key contributor to the atypical development of cortical hierarchy in ASD.

LIMITATIONS

The uneven distribution of samples across age groups, particularly in the later stages of development, limited our ability to fully capture developmental trajectories among older individuals.

CONCLUSIONS

These findings highlight the importance of understanding the developmental trajectories of cortical organization in ASD, collectively suggesting that early interventions aimed at promoting the normative development of higher-order networks may be critical for improving outcomes in individuals with ASD.

Disruption of structural connectome hierarchy in age-related hearing loss

Introduction

Age-related hearing loss (ARHL) is a common sensory disability among older adults and is considered a risk factor for the development of dementia. Previous work has shown altered brain connectome topology in ARHL, including abnormal nodal strength and clustering coefficient. However, whether ARHL affects the hierarchical organization of structural connectome and how these alterations relate to transcriptomic signatures remain unknown.

Methods

Here, we apply a gradient mapping framework to the structural connectome derived from diffusion magnetic resonance imaging. We focus on the first three structural gradients that reflect distinct hierarchical organization of structural connectome, and assess ARHL-related changes.

Results

We find that, compared to controls, ARHL patients exhibit widespread disruptions of structural connectome organization, spanning from primary sensory areas (e.g., somatomotor network) to high-order association areas (e.g., default mode network). Subsequently, by employing subcortical-weighted gradients derived from weighting cortical gradients by subcortical-cortical connectivity, we observe that ARHL patients show significantly altered subcortical-cortical connectivity in the left caudate, left nucleus accumbens, right hippocampus, and right amygdala. Finally, we investigate the relationship between gene expression and alterations in structural gradients. We observe that these alterations in structural gradients are associated with weighted gene expression profiles, with relevant genes preferentially enriched for inorganic ion transmembrane transport and terms related to regulating biological processes.

Discussion

Taken together, these findings highlight that ARHL is associated with abnormal structural connectome hierarchy and reveal the transcriptomic relevance of these abnormalities, contributing to a richer understanding of the neurobiological substrates in ARHL.

Temporal Lobe Epilepsy Perturbs the Brain-Wide Excitation-Inhibition Balance: Associations with Microcircuit Organization, Clinical Parameters, and Cognitive Dysfunction

Excitation-inhibition (E/I) imbalance is theorized as a key mechanism in the pathophysiology of epilepsy, with ample research focusing on elucidating its cellular manifestations. However, few studies investigate E/I imbalance at the macroscale, whole-brain level, and its microcircuit-level mechanisms and clinical significance remain incompletely understood. Here, the Hurst exponent, an index of the E/I ratio, is computed from resting-state fMRI time series, and microcircuit parameters are simulated using biophysical models. A broad decrease in the Hurst exponent is observed in pharmaco-resistant temporal lobe epilepsy (TLE), suggesting more excitable network dynamics. Connectome decoders point to temporolimbic and frontocentral cortices as plausible network epicenters of E/I imbalance. Furthermore, computational simulations reveal that enhancing cortical excitability in TLE reflects atypical increases in recurrent connection strength of local neuronal ensembles. Mixed cross-sectional and longitudinal analyses show stronger E/I ratio elevation in patients with longer disease duration, more frequent electroclinical seizures as well as interictal epileptic spikes, and worse cognitive functioning. Hurst exponent-informed classifiers discriminate patients from healthy controls with high accuracy (72.4% [57.5%-82.5%]). Replicated in an independent dataset, this work provides in vivo evidence of a macroscale shift in E/I balance in TLE patients and points to progressive functional imbalances that relate to cognitive decline.

Identifying influential nodes in brain networks via self-supervised graph-transformer

BACKGROUND

Studying influential nodes (I-nodes) in brain networks is of great significance in the field of brain imaging. Most existing studies consider brain connectivity hubs as I-nodes such as the regions of high centrality or rich-club organization. However, this approach relies heavily on prior knowledge from graph theory, which may overlook the intrinsic characteristics of the brain network, especially when its architecture is not fully understood. In contrast, self-supervised deep learning dispenses with manual features, allowing it to learn meaningful representations directly from the data. This approach enables the exploration of I-nodes for brain networks, which is also lacking in current studies.

METHOD

This paper proposes a Self-Supervised Graph Reconstruction framework based on Graph-Transformer (SSGR-GT) to identify I-nodes, which has three main characteristics. First, as a self-supervised model, SSGR-GT extracts the importance of brain nodes to the reconstruction. Second, SSGR-GT uses Graph-Transformer, which is well-suited for extracting features from brain graphs, combining both local and global characteristics. Third, multimodal analysis of I-nodes uses graph-based fusion technology, combining functional and structural brain information.

RESULTS

The I-nodes we obtained are distributed in critical areas such as the superior frontal lobe, lateral parietal lobe, and lateral occipital lobe, with a total of 56 identified across different experiments. These I-nodes are involved in more brain networks than other regions, have longer fiber connections, and occupy more central positions in structural connectivity. They also exhibit strong connectivity and high node efficiency in both functional and structural networks. Furthermore, there is a significant overlap between the I-nodes and both the structural and functional rich-club.

CONCLUSIONS

Experimental results verify the effectiveness of the proposed method, and I-nodes are obtained and discussed. These findings enhance our understanding of the I-nodes within the brain network, and provide new insights for future research in further understanding the brain working mechanisms.

ChatGPT-estimated occupational complexity predicts cognitive outcomes and cortical thickness above and beyond socioeconomic status among older adults

Many aging cohort studies have collected data on participants' job titles, yet these job titles were seldom analyzed within the cognitive aging context despite their relevance to neurocognition, due to difficulties in analyzing these job titles quantitatively. While it is possible to rate these jobs' occupational complexity (OC) using job classification systems, this can be somewhat labor-intensive and prone to human errors. To this end, we demonstrate a novel and simple method to extract OC ratings from job titles using ChatGPT. Then, we showcased the utility of these ratings in predicting cognitive and structural brain outcomes, especially compared to other socioeconomic status (SES) indicators. Community-dwelling older adults (N = 238, agemean = 70) completed cognitive assessments and underwent MRI scans. Regression models were fitted to predict 14 different cognitive outcomes, vertex-wise cortical thickness (CT), and subcortical gray matter volumes, using OC scores and/or SES predictors (e.g., education, housing type, and income levels), controlling for demographical covariates. OC scores outperformed SES indicators in predicting clusters of CT increases and most cognitive outcomes, including diagnoses of mild cognitive impairment. Furthermore, OC scores significantly predicted clusters of CT increases and various cognitive outcomes, even after controlling for SES. Meta-analytic decoding suggests these clusters of CT increases occurred in regions typically associated with sensorimotor and memory processing. These results highlight the significant and unique contribution of ChatGPT-derived OC scores in predicting cognitive and brain aging outcomes. These scores are easy to derive and can be helpful in fine-tuning predictions of cognitive and brain aging outcomes.

From histology to macroscale function in the human amygdala

The amygdala is a subcortical region in the mesiotemporal lobe that plays a key role in emotional and sensory functions. Conventional neuroimaging experiments treat this structure as a single, uniform entity, but there is ample histological evidence for subregional heterogeneity in microstructure and function. The current study characterized subregional structure-function coupling in the human amygdala, integrating post-mortem histology and in vivo MRI at ultra-high fields. Core to our work was a novel neuroinformatics approach that leveraged multiscale texture analysis as well as non-linear dimensionality reduction techniques to identify salient dimensions of microstructural variation in a 3D post-mortem histological reconstruction of the human amygdala. We observed two axes of subregional variation in this region, describing inferior-superior as well as mediolateral trends in microstructural differentiation that in part recapitulated established atlases of amygdala subnuclei. Translating our approach to in vivo MRI data acquired at 7 Tesla, we could demonstrate the generalizability of these spatial trends across 10 healthy adults. We then cross-referenced microstructural axes with functional blood-oxygen-level dependent (BOLD) signal analysis obtained during task-free conditions, and revealed a close association of structural axes with macroscale functional network embedding, notably the temporo-limbic, default mode, and sensory-motor networks. Our novel multiscale approach consolidates descriptions of amygdala anatomy and function obtained from histological and in vivo imaging techniques.

Brain connectivity and transcriptomic similarity inform abnormal morphometric similarity patterns in first-episode, treatment-naïve major depressive disorder

BACKGROUND

Major depressive disorder (MDD) is associated with disrupted brain structural integration. Morphometric similarity offers a means to capture the coordinated patterns of various structural features. However, it remains unknown whether MDD-related changes can be detected in cortical morphometric similarity through the Morphometric Inverse Divergence (MIND) network. Additionally, the role of brain connectivity in shaping these alterations, and their links to neuroreceptors and gene expression, have yet to be investigated.

METHODS

Using the T1-weighted MRI data from 71 patients with first-episode, treatment-naïve MDD and 69 healthy controls, we constructed the MIND network for all participants. We then performed between-group comparisons to investigate abnormalities in the network and spatial relationships between the observed patterns of MIND disruption and the patterns of neuroreceptors were estimated. Network-based spreading was utilized to explore the abnormalities constrained by brain connectivity based on structural, functional, and transcriptional connectome architecture and to further identify potential epicenters of MDD. In addition, partial least squares regression was conducted to examine the associations of gene expression profiles with MIND changes in MDD.

RESULTS

Patients with MDD showed significantly increased MIND in regions associated with sensation and cognition compared with healthy controls, with this altered pattern being influenced by a combination of transcriptional and structural connectivity, and potential epicenters of MDD were identified in the frontal, parietal, and paracentral cortices. Furthermore, the cortical map of case-control differences in MIND was spatially correlated with the cannabinoid CB1 receptor and the brain-wide expression of a weighted combination of genes. These genes were enriched for neurobiologically relevant pathways and preferentially expressed in different cell classes and cortical layers.

CONCLUSION

These results highlight the abnormal pattern of morphometric similarity observed in MDD, shedding light on the complex interplay between disrupted macroscale coordinated morphology and microscale molecular organization in MDD.

ASSOCIATIONS BETWEEN EPILEPSY-RELATED POLYGENIC RISK AND BRAIN MORPHOLOGY IN CHILDHOOD

Temporal lobe epilepsy with hippocampal sclerosis (TLE-HS) is associated with a complex genetic architecture, but the translation from genetic risk factors to brain vulnerability remains unclear. Here, we examined associations between epilepsy-related polygenic risk scores for HS (PRS-HS) and brain structure in a large sample of neurotypical children, and correlated these signatures with case-control findings in in multicentric cohorts of patients with TLE-HS. Imaging-genetic analyses revealed PRS-related cortical thinning in temporo-parietal and fronto-central regions, strongly anchored to distinct functional and structural network epicentres. Compared to disease-related effects derived from epilepsy case-control cohorts, structural correlates of PRS-HS mirrored atrophy and epicentre patterns in patients with TLE-HS. By identifying a potential pathway between genetic vulnerability and disease mechanisms, our findings provide new insights into the genetic underpinnings of structural alterations in TLE-HS and highlight potential imaging-genetic biomarkers for early risk stratification and personalized interventions.

Late-onset temporal lobe epilepsy: insights from brain atrophy and Alzheimer's disease biomarkers

Considering the growing age of the world population, the incidence of epilepsy in older adults is expected to increase significantly. It has been suggested that late-onset temporal lobe epilepsy (LO-TLE) may be neurodegenerative in origin and overlap with Alzheimer's disease (AD). Herein, we aimed to characterize the pattern of cortical atrophy and CSF biomarkers of AD (total and phosphorylated tau and amyloid-β) in a selected population of LO-TLE of unknown origin. We prospectively enrolled individuals with temporal lobe epilepsy onset after the age of 50 and no cognitive impairment. They underwent a structural MRI scan and CSF biomarkers measurement. Imaging and biomarkers data were compared to three retrospectively collected groups: (i) age-sex-matched healthy controls; (ii) patients with mild cognitive impairment (MCI) and abnormal CSF AD biomarkers (MCI-AD); and (iii) patients with MCI and normal CSF AD biomarkers (MCI-noAD). From a pool of 52 patients, 20 consecutive eligible LO-TLE patients with a mean disease duration of 1.8 years were recruited. As control populations, 25 patients with MCI-AD, 25 patients with MCI-noAD and 25 healthy controls were enrolled. CSF biomarkers returned normal values in LO-TLE, significantly different from patients with MCI due to AD. There were no differences in cortico-subcortical atrophy between epilepsy patients and healthy controls, while patients with MCI demonstrated widespread injuries of cortico-subcortical structures. Individuals with LO-TLE, characterized by short disease duration and normal CSF amyloid-β and tau protein levels, showed patterns of cortical thickness and subcortical volumes not significantly different from healthy controls, but highly different from patients with MCI, either due to AD or not.

Sodium valproate is associated with cortical thinning of disease-specific areas in juvenile myoclonic epilepsy

BACKGROUND

Juvenile myoclonic epilepsy (JME) is associated with cortical thinning of the motor areas. The relative contribution of antiseizure medication to cortical thickness is unknown. We aimed to investigate how valproate influences the cortical morphology of JME.

METHODS

In this cross-sectional study, individuals with JME with and without valproate, with temporal lobe epilepsy (TLE) with valproate and controls were selected through propensity score matching. Participants underwent T1-weighted brain imaging and vertex-wise calculation of cortical thickness.

RESULTS

We matched 36 individuals with JME on valproate with 36 individuals with JME without valproate, 36 controls and 19 individuals with TLE on valproate. JME on valproate showed thinning of the precentral gyri (left and right, p<0.001) compared with controls and thinning of the left precentral gyrus when compared with JME not on valproate (p<0.01) or to TLE on valproate (p<0.001). Valproate dose correlated negatively with the thickness of the precentral gyri, postcentral gyri and superior frontal gyrus in JME (left and right p<0.0001), but not in TLE.

CONCLUSIONS

Valproate was associated with JME-specific and dose-dependent thinning of the cortical motor regions. This suggests that valproate is a key modulator of cortical morphology in JME, an effect that may underlie its high efficacy in this syndrome.

Sex differences in autism spectrum disorder using class imbalance adjusted functional connectivity

Autism spectrum disorder (ASD) is an atypical neurodevelopmental condition with a diagnostic ratio largely differing between male and female participants. Due to the sex imbalance in participants with ASD, we lack an understanding of the differences in connectome organization of the brain between male and female participants with ASD. In this study, we matched the sex ratio using a Gaussian mixture model-based oversampling technique and investigated the differences in functional connectivity between male and female participants with ASD using low-dimensional principal gradients. Between-group comparisons of the gradient values revealed significant interaction effects of sex in the sensorimotor, attention, and default mode networks. The sex-related differences in the gradients were highly associated with higher-order cognitive control processes. Transcriptomic association analysis provided potential biological underpinnings, specifying gene enrichment in the cortex, thalamus, and striatum during development. Finally, the principal gradients were differentially associated with symptom severity of ASD between sexes, highlighting significant effects in female participants with ASD. Our work proposed an oversampling method to mitigate sex imbalance in ASD and observed significant sex-related differences in functional connectome organization. The findings may advance our knowledge about the sex heterogeneity in large-scale brain networks in ASD.

Comparison of different group-level templates in gradient-based multimodal connectivity analysis

The study of large-scale brain connectivity is increasingly adopting unsupervised approaches that derive low-dimensional spatial representations from high-dimensional connectomes, referred to as gradient analysis. When translating this approach to study interindividual variations in connectivity, one technical issue pertains to the selection of an appropriate group-level template to which individual gradients are aligned. Here, we compared different group-level template construction strategies using functional and structural connectome data from neurotypical controls and individuals with autism spectrum disorder (ASD) to identify between-group differences. We studied multimodal magnetic resonance imaging data obtained from the Autism Brain Imaging Data Exchange (ABIDE) Initiative II and the Human Connectome Project (HCP). We designed six template construction strategies that varied in whether (1) they included typical controls in addition to ASD; or (2) they mapped from one dataset onto another. We found that aligning a combined subject template of the ASD and control subjects from the ABIDE Initiative onto the HCP template exhibited the most pronounced effect size. This strategy showed robust identification of ASD-related brain regions for both functional and structural gradients across different study settings. Replicating the findings on focal epilepsy demonstrated the generalizability of our approach. Our findings will contribute to improving gradient-based connectivity research.

Cortical Surface Area Profile Mediates Effects of Childhood Disadvantage on Later-Life General Cognitive Ability

OBJECTIVES

Childhood disadvantage is associated with lower general cognitive ability (GCA) and brain structural differences in midlife and older adulthood. However, the neuroanatomical mechanisms underlying childhood disadvantage effects on later-life GCA remain poorly understood. Although total surface area (SA) has been linked to lifespan GCA differences, total SA does not capture the nonuniform nature of childhood disadvantage effects on neuroanatomy, which varies across unimodal and transmodal cortices. Here, we examined whether cortical SA profile-the extent to which the spatial patterning of SA deviates from the normative unimodal-transmodal cortical organization-is a mediator of childhood disadvantage effects on later-life GCA.

METHODS

In 477 community-dwelling men aged 56-72 years old, childhood disadvantage index was derived from four indicators of disadvantages and GCA was assessed using a standardized test. Cortical SA was obtained from structural magnetic resonance imaging. For cortical SA profile, we calculated the spatial similarity between maps of individual cortical SA and MRI-derived principal gradient (i.e., unimodal-transmodal organization). Mediation analyses were conducted to examine the indirect effects of childhood disadvantage index through cortical SA profile on GCA.

RESULTS

Around 1.31% of childhood disadvantage index effects on later-life GCA were mediated by cortical SA profile, whereas total SA did not. Higher childhood disadvantage index was associated with more deviation of the cortical SA spatial patterning from the principal gradient, which in turn related to lower later-life GCA.

DISCUSSION

Childhood disadvantage may contribute to later-life GCA differences partly by influencing the spatial patterning of cortical SA in a way that deviates from the normative cortical organizational principle.

Microstructural asymmetry in the human cortex

The human cerebral cortex shows hemispheric asymmetry, yet the microstructural basis of this asymmetry remains incompletely understood. Here, we probe layer-specific microstructural asymmetry using one post-mortem male brain. Overall, anterior and posterior regions show leftward and rightward asymmetry respectively, but this pattern varies across cortical layers. A similar anterior-posterior pattern is observed using in vivo Human Connectome Project (N = 1101) T1w/T2w microstructural data, with average cortical asymmetry showing the strongest similarity with post-mortem-based asymmetry of layer III. Moreover, microstructural asymmetry is found to be heritable, varies as a function of age and sex, and corresponds to intrinsic functional asymmetry. We also observe a differential association of language and markers of mental health with microstructural asymmetry patterns at the individual level, illustrating a functional divergence between inferior-superior and anterior-posterior microstructural axes, possibly anchored in development. Last, we could show concordant evidence with alternative in vivo microstructural measures: magnetization transfer (N = 286) and quantitative T1 (N = 50). Together, our study highlights microstructural asymmetry in the human cortex and its functional and behavioral relevance.

Differential reorganization of episodic and semantic memory systems in epilepsy-related mesiotemporal pathology

Declarative memory encompasses episodic and semantic divisions. Episodic memory captures singular events with specific spatiotemporal relationships, whereas semantic memory houses context-independent knowledge. Behavioural and functional neuroimaging studies have revealed common and distinct neural substrates of both memory systems, implicating mesiotemporal lobe (MTL) regions such as the hippocampus and distributed neocortices. Here, we explored declarative memory system reorganization in patients with unilateral temporal lobe epilepsy (TLE) as a human disease model to test the impact of variable degrees of MTL pathology on memory function. Our cohort included 31 patients with TLE and 60 age- and sex-matched healthy controls, and all participants underwent episodic and semantic retrieval tasks during a multimodal MRI session. The functional MRI tasks were closely matched in terms of stimuli and trial design. Capitalizing on non-linear connectome gradient-mapping techniques, we derived task-based functional topographies during episodic and semantic memory states, in both the MTL and neocortical networks. Comparing neocortical and hippocampal functional gradients between TLE patients and healthy controls, we observed a marked topographic reorganization of both neocortical and MTL systems during episodic memory states. Neocortical alterations were characterized by reduced functional differentiation in TLE across lateral temporal and midline parietal cortices in both hemispheres. In the MTL, in contrast, patients presented with a more marked functional differentiation of posterior and anterior hippocampal segments ipsilateral to the seizure focus and pathological core, indicating perturbed intrahippocampal connectivity. Semantic memory reorganization was also found in bilateral lateral temporal and ipsilateral angular regions, whereas hippocampal functional topographies were unaffected. Furthermore, leveraging MRI proxies of MTL pathology, we observed alterations in hippocampal microstructure and morphology that were associated with TLE-related functional reorganization during episodic memory. Moreover, correlation analysis and statistical mediation models revealed that these functional alterations contributed to behavioural deficits in episodic memory, but again not in semantic memory in patients. Altogether, our findings suggest that semantic processes rely on distributed neocortical networks, whereas episodic processes are supported by a network involving both the hippocampus and the neocortex. Alterations of such networks can provide a compact signature of state-dependent reorganization in conditions associated with MTL damage, such as TLE.

Depression and metabolic connectivity: insights into the locus coeruleus, HF-rTMS, and anxiety

The use of repetitive Transcranial Magnetic Stimulation (rTMS) in treating major depressive disorder (MDD) is increasingly being explored in precision medicine. However, there's a notable lack of understanding of the underlying neurobiological effects, which limits our ability to correlate specific imaging features with treatment efficacy. As one possible neurobiological mechanism, clinical research has already shown that in MDD, lower norepinephrine release in the locus coeruleus (LC) triggers depressive symptoms, and pharmacological approaches that block norepinephrine reuptake boost its levels, easing depression. Surprisingly, the LC has not received a more pronounced focus in contemporary rTMS research. This study investigates the role of the LC in MDD and its response to high-frequency (HF)-rTMS using 18FDG-PET imaging. We compared LC metabolic connectivity between MDD patients (n = 43) and healthy controls (n = 32). Additionally, we evaluated the predictive value of LC connectivity for HF-rTMS treatment outcomes and examined post-treatment changes in LC metabolic connectivity. Our findings revealed significant differences in LC metabolic connectivity between MDD patients and controls. Baseline LC metabolic connectivity did not predict HF-rTMS treatment outcomes. However, post-treatment analyses showed a significant correlation between improved clinical outcomes and attenuation of LC metabolic connectivity in regions associated with cognitive control and the default mode network. Notably, a reduction in state anxiety moderated this relationship, highlighting the role of anxiety in HF-rTMS efficacy for MDD treatment. Our findings suggest that LC metabolic connectivity, influenced by state anxiety levels, may be crucial in HF-rTMS efficacy, offering further insights for personalized MDD treatment strategies.

Quantitative MRI Measures and Cognitive Function in People With Drug-Resistant Juvenile Myoclonic Epilepsy

BACKGROUND AND OBJECTIVES

Neuroimaging studies have so far identified structural changes in individuals with juvenile myoclonic epilepsy (JME) when compared with controls. However, the underlying mechanisms of drug-resistant JME remain unknown. In this study, we aimed at characterizing the structural underpinnings of drug-resistant JME using MRI-derived cortical morphologic markers.

METHODS

In this prospective cross-sectional 2-center study, T1-weighted MRI and neuropsychological measures of verbal memory and executive function were obtained in individuals with drug-resistant and drug-responsive JME recruited from epilepsy outpatient clinics and healthy controls. We performed vertexwise measurements of cortical thickness, surface area, and local gyrification index (LGI). Vertexwise group comparisons were corrected for multiple comparisons at a familywise error (FWE) of 0.05. The neuropsychological profile of disease subgroups was analyzed through principal component analysis.

RESULTS

We studied 42 individuals with drug-resistant JME (mean age 29 ± 11 years, 50% female), 37 with drug-responsive JME (mean age 34 ± 10, years, 59% female), and 71 healthy controls (mean age 21 ± 9 years, 61% female). Surface area was increased in participants with drug-resistant JME in the left temporal lobe (Cohen d = 0.82 [-0.52 to -1.12], pFWE < 0.05) when compared with the drug-responsive group. Although no cortical thickness changes were observed between disease subgroups, drug-resistant and drug-sensitive participants showed discrete cortical thinning against controls (Cohen d = -0.42 [-0.83 to -0.01], pFWE < 0.05; Cohen d = -0.57 [-1.03 to -0.11], pFWE < 0.05, respectively). LGI was increased in the left temporal and occipital lobes in drug-resistant participants (Cohen d = 0.60 [0.34-0.86], pFWE < 0.05) when contrasting against drug-sensitive participants, but not controls. The composite executive function score was reduced in drug-resistant individuals compared with controls and drug-sensitive individuals (-1.74 [-2.58 to -0.90], p < 0.001 and -1.29 [-2.25 to -0.33], p < 0.01, respectively). Significant correlations were observed between executive function impairment and increased surface area in the precuneus and medial prefrontal regions (r = -0.79, pFWE < 0.05) in participants with drug-resistant JME.

DISCUSSION

We identified a developmental phenotype in individuals with drug-resistant JME characterized by changes in cortical surface area and folding complexity, the extent of which correlates with executive dysfunction. No association was observed between cortical thickness and disease severity. Our findings support a neurodevelopmental basis for drug resistance and cognitive impairment in JME.

Changes in the structure of spontaneous speech predict the disruption of hierarchical brain organization in first-episode psychosis

Psychosis implicates changes across a broad range of cognitive functions. These functions are cortically organized in the form of a hierarchy ranging from primary sensorimotor (unimodal) to higher-order association cortices, which involve functions such as language (transmodal). Language has long been documented as undergoing structural changes in psychosis. We hypothesized that these changes as revealed in spontaneous speech patterns may act as readouts of alterations in the configuration of this unimodal-to-transmodal axis of cortical organization in psychosis. Results from 29 patients with first-episodic psychosis (FEP) and 29 controls scanned with 7 T resting-state fMRI confirmed a compression of the cortical hierarchy in FEP, which affected metrics of the hierarchical distance between the sensorimotor and default mode networks, and of the hierarchical organization within the semantic network. These organizational changes were predicted by graphs representing semantic and syntactic associations between meaningful units in speech produced during picture descriptions. These findings unite psychosis, language, and the cortical hierarchy in a single conceptual scheme, which helps to situate language within the neurocognition of psychosis and opens the clinical prospect for mental dysfunction to become computationally measurable in spontaneous speech.

Gradients of Brain Organization: Smooth Sailing from Methods Development to User Community

Multimodal neuroimaging grants a powerful in vivo window into the structure and function of the human brain. Recent methodological and conceptual advances have enabled investigations of the interplay between large-scale spatial trends - or gradients - in brain structure and function, offering a framework to unify principles of brain organization across multiple scales. Strong community enthusiasm for these techniques has been instrumental in their widespread adoption and implementation to answer key questions in neuroscience. Following a brief review of current literature on this framework, this perspective paper will highlight how pragmatic steps aiming to make gradient methods more accessible to the community propelled these techniques to the forefront of neuroscientific inquiry. More specifically, we will emphasize how interest for gradient methods was catalyzed by data sharing, open-source software development, as well as the organization of dedicated workshops led by a diverse team of early career researchers. To this end, we argue that the growing excitement for brain gradients is the result of coordinated and consistent efforts to build an inclusive community and can serve as a case in point for future innovations and conceptual advances in neuroinformatics. We close this perspective paper by discussing challenges for the continuous refinement of neuroscientific theory, methodological innovation, and real-world translation to maintain our collective progress towards integrated models of brain organization.

Early Cortical Microstructural Changes in Aging Are Linked to Vulnerability to Alzheimer's Disease Pathology

BACKGROUND

Early identification of Alzheimer's disease (AD) risk is critical for improving treatment success. Cortical thickness is a macrostructural measure used to assess neurodegeneration in AD. However, cortical microstructural changes appear to precede macrostructural atrophy and may improve early risk identification. Currently, whether cortical microstructural changes in aging are linked to vulnerability to AD pathophysiology remains unclear in nonclinical populations, who are precisely the target for early risk identification.

METHODS

In 194 adults, we calculated magnetic resonance imaging-derived maps of changes in cortical mean diffusivity (microstructure) and cortical thickness (macrostructure) over 5 to 6 years (mean age: time 1 = 61.82 years; time 2 = 67.48 years). Episodic memory was assessed using 3 well-established tests. We obtained positron emission tomography-derived maps of AD pathology deposition (amyloid-β, tau) and neurotransmitter receptors (cholinergic, glutamatergic) implicated in AD pathophysiology. Spatial correlational analyses were used to compare pattern similarity among maps.

RESULTS

Spatial patterns of cortical macrostructural changes resembled patterns of cortical organization sensitive to age-related processes (r = -0.31, p < .05), whereas microstructural changes resembled the patterns of tau deposition in AD (r = 0.39, p = .038). Individuals with patterns of microstructural changes that more closely resembled stereotypical tau deposition exhibited greater memory decline (β = 0.22, p = .029). Microstructural changes and AD pathology deposition were enriched in areas with greater densities of cholinergic and glutamatergic receptors (ps < .05).

CONCLUSIONS

Patterns of cortical microstructural changes were more AD-like than patterns of macrostructural changes, which appeared to reflect more general aging processes. Microstructural changes may better inform early risk prediction efforts as a sensitive measure of vulnerability to pathological processes prior to overt atrophy and cognitive decline.

Brain Networks for Cortical Atrophy and Responsive Neurostimulation in Temporal Lobe Epilepsy

Importance

Drug-resistant temporal lobe epilepsy (TLE) has been associated with hippocampal pathology. Most surgical treatment strategies, including resection and responsive neurostimulation (RNS), focus on this disease epicenter; however, imaging alterations distant from the hippocampus, as well as emerging data from responsive neurostimulation trials, suggest conceptualizing TLE as a network disorder.

Objective

To assess whether brain networks connected to areas of atrophy in the hippocampus align with the topography of distant neuroimaging alterations and RNS response.

Design, Setting, and Participants

This retrospective case-control study was conducted between July 2009 and June 2022. Data collection for this multicenter, population-based study took place across 4 tertiary referral centers in Montréal, Canada; Querétaro, México; Nanjing, China; and Salt Lake City, Utah. Eligible patients were diagnosed with TLE according to International League Against Epilepsy criteria and received either neuroimaging or neuroimaging and RNS to the hippocampus. Patients with encephalitis, traumatic brain injury, or bilateral TLE were excluded.

Main Outcomes and Measures

Spatial alignment between brain network topographies.

Results

Of the 110 eligible patients, 94 individuals diagnosed with TLE were analyzed (51 [54%] female; mean [SD] age, 31.3 [10.9] years). Hippocampal thickness maps in TLE were compared to 120 healthy control individuals (66 [55%] female; mean [SD] age, 29.8 [9.5] years), and areas of atrophy were identified. Using an atlas of normative connectivity (n = 1000), 2 brain networks were identified that were functionally connected to areas of hippocampal atrophy. The first network was defined by positive correlations to temporolimbic, medial prefrontal, and parietal regions, whereas the second network by negative correlations to frontoparietal regions. White matter changes colocalized to the positive network (t93 = -3.82; P = 2.44 × 10-4). In contrast, cortical atrophy localized to the negative network (t93 = 3.54; P = 6.29 × 10-3). In an additional 38 patients (20 [53%] female; mean [SD] age, 35.8 [11.3] years) treated with RNS, connectivity between the stimulation site and atrophied regions within the negative network was associated with seizure reduction (t212 = -2.74; P = .007).

Conclusions and Relevance

The findings in this study indicate that distributed pathology in TLE may occur in brain networks connected to the hippocampal epicenter. Connectivity to these same networks was associated with improvement following RNS. A network approach to TLE may reveal therapeutic targets outside the traditional target in the hippocampus.

Contracted functional connectivity profiles in autism

OBJECTIVE

Autism spectrum disorder (ASD) is a neurodevelopmental condition that is associated with atypical brain network organization, with prior work suggesting differential connectivity alterations with respect to functional connection length. Here, we tested whether functional connectopathy in ASD specifically relates to disruptions in long- relative to short-range functional connections. Our approach combined functional connectomics with geodesic distance mapping, and we studied associations to macroscale networks, microarchitectural patterns, as well as socio-demographic and clinical phenotypes.

METHODS

We studied 211 males from three sites of the ABIDE-I dataset comprising 103 participants with an ASD diagnosis (mean ± SD age = 20.8 ± 8.1 years) and 108 neurotypical controls (NT, 19.2 ± 7.2 years). For each participant, we computed cortex-wide connectivity distance (CD) measures by combining geodesic distance mapping with resting-state functional connectivity profiling. We compared CD between ASD and NT participants using surface-based linear models, and studied associations with age, symptom severity, and intelligence scores. We contextualized CD alterations relative to canonical networks and explored spatial associations with functional and microstructural cortical gradients as well as cytoarchitectonic cortical types.

RESULTS

Compared to NT, ASD participants presented with widespread reductions in CD, generally indicating shorter average connection length and thus suggesting reduced long-range connectivity but increased short-range connections. Peak reductions were localized in transmodal systems (i.e., heteromodal and paralimbic regions in the prefrontal, temporal, and parietal and temporo-parieto-occipital cortex), and effect sizes correlated with the sensory-transmodal gradient of brain function. ASD-related CD reductions appeared consistent across inter-individual differences in age and symptom severity, and we observed a positive correlation of CD to IQ scores.

LIMITATIONS

Despite rigorous harmonization across the three different acquisition sites, heterogeneity in autism poses a potential limitation to the generalizability of our results. Additionally, we focussed male participants, warranting future studies in more balanced cohorts.

CONCLUSIONS

Our study showed reductions in CD as a relatively stable imaging phenotype of ASD that preferentially impacted paralimbic and heteromodal association systems. CD reductions in ASD corroborate previous reports of ASD-related imbalance between short-range overconnectivity and long-range underconnectivity.

The macroscale routing mechanism of structural brain connectivity related to body mass index

Understanding the brain's mechanisms in individuals with obesity is important for managing body weight. Prior neuroimaging studies extensively investigated alterations in brain structure and function related to body mass index (BMI). However, how the network communication among the large-scale brain networks differs across BMI is underinvestigated. This study used diffusion magnetic resonance imaging of 290 young adults to identify links between BMI and brain network mechanisms. Navigation efficiency, a measure of network routing, was calculated from the structural connectivity computed using diffusion tractography. The sensory and frontoparietal networks indicated positive associations between navigation efficiency and BMI. The neurotransmitter association analysis identified that serotonergic and dopaminergic receptors, as well as opioid and norepinephrine systems, were related to BMI-related alterations in navigation efficiency. The transcriptomic analysis found that genes associated with network routing across BMI overlapped with genes enriched in excitatory and inhibitory neurons, specifically, gene enrichments related to synaptic transmission and neuron projection. Our findings suggest a valuable insight into understanding BMI-related alterations in brain network routing mechanisms and the potential underlying cellular biology, which might be used as a foundation for BMI-based weight management.

Shared and distinct cortical morphometric alterations in five neuropsychiatric symptoms of Parkinson's disease

Neuropsychiatric symptoms (including anxiety, depression, apathy, impulse-compulsive behaviors and hallucinations) are among the most common non-motor features of Parkinson's disease. Whether these symptoms should be considered as a direct consequence of the pathophysiologic mechanisms of Parkinson's disease is controversial. Morphometric similarity network analysis and epicenter mapping approach were performed on T1-weighted images of 505 patients with Parkinson's disease and 167 age- and sex-matched healthy participants from Parkinson's Progression Markers Initiative database to reveal the commonalities and specificities of distinct neuropsychiatric symptoms. Abnormal cortical co-alteration pattern in patients with neuropsychiatric symptoms was in somatomotor, vision and frontoparietal regions, with epicenters in somatomotor regions. Apathy, impulse-compulsive behaviors and hallucinations shares structural abnormalities in somatomotor and vision regions, with epicenters in somatomotor regions. In contrast, the cortical abnormalities and epicenters of anxiety and depression were prominent in the default mode network regions. By embedding each symptom within their co-alteration space, we observed a cluster composed of apathy, impulse-compulsive behaviors and hallucinations, while anxiety and depression remained separate. Our findings indicate different structural mechanisms underlie the occurrence and progression of different neuropsychiatric symptoms. Based upon these results, we propose that apathy, impulse-compulsive behaviors and hallucinations are directly related to damage of motor circuit, while anxiety and depression may be the combination effects of primary pathophysiology of Parkinson's disease and psychosocial causes.

Brain Charts for the Rhesus Macaque Lifespan

Recent efforts to chart human brain growth across the lifespan using large-scale MRI data have provided reference standards for human brain development. However, similar models for nonhuman primate (NHP) growth are lacking. The rhesus macaque, a widely used NHP in translational neuroscience due to its similarities in brain anatomy, phylogenetics, cognitive, and social behaviors to humans, serves as an ideal NHP model. This study aimed to create normative growth charts for brain structure across the macaque lifespan, enhancing our understanding of neurodevelopment and aging, and facilitating cross-species translational research. Leveraging data from the PRIMatE Data Exchange (PRIME-DE) and other sources, we aggregated 1,522 MRI scans from 1,024 rhesus macaques. We mapped non-linear developmental trajectories for global and regional brain structural changes in volume, cortical thickness, and surface area over the lifespan. Our findings provided normative charts with centile scores for macaque brain structures and revealed key developmental milestones from prenatal stages to aging, highlighting both species-specific and comparable brain maturation patterns between macaques and humans. The charts offer a valuable resource for future NHP studies, particularly those with small sample sizes. Furthermore, the interactive open resource (https://interspeciesmap.childmind.org) supports cross-species comparisons to advance translational neuroscience research.

Differential increase of hippocampal subfield volume after socio-affective mental training relates to reductions in diurnal cortisol

The hippocampus is a central modulator of the HPA-axis, impacting the regulation of stress on brain structure, function, and behavior. The current study assessed whether three different types of 3 months mental Training Modules geared towards nurturing (a) attention-based mindfulness, (b) socio-affective, or (c) socio-cognitive skills may impact hippocampal organization by reducing stress. We evaluated mental training-induced changes in hippocampal subfield volume and intrinsic functional connectivity, by combining longitudinal structural and resting-state fMRI connectivity analysis in 332 healthy adults. We related these changes to changes in diurnal and chronic cortisol levels. We observed increases in bilateral cornu ammonis volume (CA1-3) following the 3 months compassion-based module targeting socio-affective skills (Affect module), as compared to socio-cognitive skills (Perspective module) or a waitlist cohort with no training intervention. Structural changes were paralleled by relative increases in functional connectivity of CA1-3 when fostering socio-affective as compared to socio-cognitive skills. Furthermore, training-induced changes in CA1-3 structure and function consistently correlated with reductions in cortisol output. Notably, using a multivariate approach, we found that other subfields that did not show group-level changes also contributed to changes in cortisol levels. Overall, we provide a link between a socio-emotional behavioural intervention, changes in hippocampal subfield structure and function, and reductions in cortisol in healthy adults.

Associations of Cerebral Blood Flow Patterns With Gray and White Matter Structure in Patients With Temporal Lobe Epilepsy

BACKGROUND AND OBJECTIVES

Neuroimaging studies in patients with temporal lobe epilepsy (TLE) show widespread brain network alterations beyond the mesiotemporal lobe. Despite the critical role of the cerebrovascular system in maintaining whole-brain structure and function, changes in cerebral blood flow (CBF) remain incompletely understood in the disease. Here, we studied whole-brain perfusion and vascular network alterations in TLE and assessed its associations with gray and white matter compromises and various clinical variables.

METHODS

We included individuals with and without pharmaco-resistant TLE who underwent multimodal 3T MRI, including arterial spin labelling, structural, and diffusion-weighted imaging. Using surface-based MRI mapping, we generated individualized cortico-subcortical profiles of perfusion, morphology, and microstructure. Linear models compared regional CBF in patients with controls and related alterations to morphological and microstructural metrics. We further probed interregional vascular networks in TLE, using graph theoretical CBF covariance analysis. The effects of disease duration were explored to better understand the progressive changes in perfusion. We assessed the utility of perfusion in separating patients with TLE from controls using supervised machine learning.

RESULTS

Compared with control participants (n = 38; mean ± SD age 34.8 ± 9.3 years; 20 females), patients with TLE (n = 24; mean ± SD age 35.8 ± 10.6 years; 12 females) showed widespread CBF reductions predominantly in fronto-temporal regions (Cohen d -0.69, 95% CI -1.21 to -0.16), consistent in a subgroup of patients who remained seizure-free after surgical resection of the seizure focus. Parallel structural profiling and network-based models showed that cerebral hypoperfusion may be partially constrained by gray and white matter changes (8.11% reduction in Cohen d) and topologically segregated from whole-brain perfusion networks (area under the curve -0.17, p < 0.05). Negative effects of progressive disease duration further targeted regional CBF profiles in patients (r = -0.54, 95% CI -0.77 to -0.16). Perfusion-derived classifiers discriminated patients from controls with high accuracy (71% [70%-82%]). Findings were robust when controlling for several methodological confounds.

DISCUSSION

Our multimodal findings provide insights into vascular contributions to TLE pathophysiology affecting and extending beyond mesiotemporal structures and highlight their clinical potential in epilepsy diagnosis. As our work was cross-sectional and based on a single site, it motivates future longitudinal studies to confirm progressive effects, ideally in a multicentric setting.

A shifting role of thalamocortical connectivity in the emergence of cortical functional organization

The cortical patterning principle has been a long-standing question in neuroscience, yet how this translates to macroscale functional specialization in the human brain remains largely unknown. Here we examine age-dependent differences in resting-state thalamocortical connectivity to investigate its role in the emergence of large-scale functional networks during early life, using a primarily cross-sectional but also longitudinal approach. We show that thalamocortical connectivity during infancy reflects an early differentiation of sensorimotor networks and genetically influenced axonal projection. This pattern changes in childhood, when connectivity is established with the salience network, while decoupling externally and internally oriented functional systems. A developmental simulation using generative network models corroborated these findings, demonstrating that thalamic connectivity contributes to developing key features of the mature brain, such as functional segregation and the sensory-association axis, especially across 12-18 years of age. Our study suggests that the thalamus plays an important role in functional specialization during development, with potential implications for studying conditions with compromised internal and external processing.

Connectome reorganization associated with temporal lobe pathology and its surgical resection

Network neuroscience offers a unique framework to understand the organizational principles of the human brain. Despite recent progress, our understanding of how the brain is modulated by focal lesions remains incomplete. Resection of the temporal lobe is the most effective treatment to control seizures in pharmaco-resistant temporal lobe epilepsy (TLE), making this syndrome a powerful model to study lesional effects on network organization in young and middle-aged adults. Here, we assessed the downstream consequences of a focal lesion and its surgical resection on the brain's structural connectome, and explored how this reorganization relates to clinical variables at the individual patient level. We included adults with pharmaco-resistant TLE (n = 37) who underwent anterior temporal lobectomy between two imaging time points, as well as age- and sex-matched healthy controls who underwent comparable imaging (n = 31). Core to our analysis was the projection of high-dimensional structural connectome data-derived from diffusion MRI tractography from each subject-into lower-dimensional gradients. We then compared connectome gradients in patients relative to controls before surgery, tracked surgically-induced connectome reconfiguration from pre- to postoperative time points, and examined associations to patient-specific clinical and imaging phenotypes. Before surgery, individuals with TLE presented with marked connectome changes in bilateral temporo-parietal regions, reflecting an increased segregation of the ipsilateral anterior temporal lobe from the rest of the brain. Surgery-induced connectome reorganization was localized to this temporo-parietal subnetwork, but primarily involved postoperative integration of contralateral regions with the rest of the brain. Using a partial least-squares analysis, we uncovered a latent clinical imaging signature underlying this pre- to postoperative connectome reorganization, showing that patients who displayed postoperative integration in bilateral fronto-occipital cortices also had greater preoperative ipsilateral hippocampal atrophy, lower seizure frequency and secondarily generalized seizures. Our results bridge the effects of focal brain lesions and their surgical resections with large-scale network reorganization and interindividual clinical variability, thus offering new avenues to examine the fundamental malleability of the human brain.

A neurofunctional signature of subjective disgust generalizes to oral distaste and socio-moral contexts

While disgust originates in the hard-wired mammalian distaste response, the conscious experience of disgust in humans strongly depends on subjective appraisal and may even extend to socio-moral contexts. Here, in a series of studies, we combined functional magnetic resonance imaging with machine-learning-based predictive modelling to establish a comprehensive neurobiological model of subjective disgust. The developed neurofunctional signature accurately predicted momentary self-reported subjective disgust across discovery (n = 78) and pre-registered validation (n = 30) cohorts and generalized across core disgust (n = 34 and n = 26), gustatory distaste (n = 30) and socio-moral (unfair offers; n = 43) contexts. Disgust experience was encoded in distributed cortical and subcortical systems, and exhibited distinct and shared neural representations with subjective fear or negative affect in interoceptive-emotional awareness and conscious appraisal systems, while the signatures most accurately predicted the respective target experience. We provide an accurate functional magnetic resonance imaging signature for disgust with a high potential to resolve ongoing evolutionary debates.

Differences in cortical microstructure according to body mass index in neurologically healthy populations using structural magnetic resonance imaging

Associations between brain structure and body mass index (BMI) are increasingly gaining attention. Although BMI-related regional alterations in brain morphology have been previously reported, the effect of BMI on the microstructural profiles, which provide information on the proxy of neuronal density within the cortex, is unexplored. In this study, we investigated the links between cortical layer-specific microstructural profiles and BMI in 302 neurologically healthy young adults. Using the microstructure-sensitive proxy based on the T1-and T2-weighted ratio, we estimated microstructural profile covariance (MPC) by calculating linear correlations of cortical depth-wise intensity profiles between different brain regions. Then, low-dimensional gradients of the MPC matrix were estimated using dimensionality reduction techniques, and the gradients were associated with BMI. Significant effects in the heteromodal association areas were observed. The BMI-gradient association map was related to the geodesic distance along the cortical surface, curvature, and sulcal depth, suggesting that the microstructural alterations occurred along the cortical topology. The BMI-gradient association map was further linked to cognitive states related to negative emotions. Our findings may provide insights into understanding the atypical cortical microstructure associated with BMI.

Adolescent maturation of cortical excitation-inhibition balance based on individualized biophysical network modeling

The balance of excitation and inhibition is a key functional property of cortical microcircuits which changes through the lifespan. Adolescence is considered a crucial period for the maturation of excitation-inhibition balance. This has been primarily observed in animal studies, yet human in vivo evidence on adolescent maturation of the excitation-inhibition balance at the individual level is limited. Here, we developed an individualized in vivo marker of regional excitation-inhibition balance in human adolescents, estimated using large-scale simulations of biophysical network models fitted to resting-state functional magnetic resonance imaging data from two independent cross-sectional (N = 752) and longitudinal (N = 149) cohorts. We found a widespread relative increase of inhibition in association cortices paralleled by a relative age-related increase of excitation, or lack of change, in sensorimotor areas across both datasets. This developmental pattern co-aligned with multiscale markers of sensorimotor-association differentiation. The spatial pattern of excitation-inhibition development in adolescence was robust to inter-individual variability of structural connectomes and modeling configurations. Notably, we found that alternative simulation-based markers of excitation-inhibition balance show a variable sensitivity to maturational change. Taken together, our study highlights an increase of inhibition during adolescence in association areas using cross sectional and longitudinal data, and provides a robust computational framework to estimate microcircuit maturation in vivo at the individual level.

Connectome architecture shapes large-scale cortical alterations in schizophrenia: a worldwide ENIGMA study

Schizophrenia is a prototypical network disorder with widespread brain-morphological alterations, yet it remains unclear whether these distributed alterations robustly reflect the underlying network layout. We tested whether large-scale structural alterations in schizophrenia relate to normative structural and functional connectome architecture, and systematically evaluated robustness and generalizability of these network-level alterations. Leveraging anatomical MRI scans from 2439 adults with schizophrenia and 2867 healthy controls from 26 ENIGMA sites and normative data from the Human Connectome Project (n = 207), we evaluated structural alterations of schizophrenia against two network susceptibility models: (i) hub vulnerability, which examines associations between regional network centrality and magnitude of disease-related alterations; (ii) epicenter mapping, which identifies regions whose typical connectivity profile most closely resembles the disease-related morphological alterations. To assess generalizability and specificity, we contextualized the influence of site, disease stages, and individual clinical factors and compared network associations of schizophrenia with that found in affective disorders. Our findings show schizophrenia-related cortical thinning is spatially associated with functional and structural hubs, suggesting that highly interconnected regions are more vulnerable to morphological alterations. Predominantly temporo-paralimbic and frontal regions emerged as epicenters with connectivity profiles linked to schizophrenia's alteration patterns. Findings were robust across sites, disease stages, and related to individual symptoms. Moreover, transdiagnostic comparisons revealed overlapping epicenters in schizophrenia and bipolar, but not major depressive disorder, suggestive of a pathophysiological continuity within the schizophrenia-bipolar-spectrum. In sum, cortical alterations over the course of schizophrenia robustly follow brain network architecture, emphasizing marked hub susceptibility and temporo-frontal epicenters at both the level of the group and the individual. Subtle variations of epicenters across disease stages suggest interacting pathological processes, while associations with patient-specific symptoms support additional inter-individual variability of hub vulnerability and epicenters in schizophrenia. Our work outlines potential pathways to better understand macroscale structural alterations, and inter- individual variability in schizophrenia.

LFC study: Protocol for a longitudinal follow-up cohort study on ageing and mental health in community-dwelling older adults in Singapore

The rapid pace of population ageing worldwide has prompted the need to better understand the ageing process. The current study, titled the Longitudinal Follow-up of the CHI (LFC) study, was a 3-year follow-up study of an earlier study titled the Community Health and Intergenerational (CHI) study. The LFC study looked to examine longitudinal changes in their cognitive functioning and psychosocial outcomes across the 3-year period. Additionally, the current study built upon the earlier CHI study by collecting neuroimaging data and exploring the long-term effects of non-pharmacological interventions, which were not examined in the prior study. A total of 653 community-dwelling participants from the baseline CHI study cohort were invited to take part in the LFC study, where they underwent a battery of neuropsychological assessments, psychosocial questionnaires, a Magnetic Resonance Imaging scan and a voice recording segment. The current study would holistically track longitudinal changes in cognitive functioning and psychosocial outcomes in the ageing population in Singapore. Unique associations between linguistics and neuroimaging data alongside cognitive and psychosocial outcomes would be explored. This study also serves to guide the development of new interventions for older adults and assist in improving the well-being of the local and global ageing population.

Atypical connectome topography and signal flow in temporal lobe epilepsy

Temporal lobe epilepsy (TLE) is the most common pharmaco-resistant epilepsy in adults. While primarily associated with mesiotemporal pathology, recent evidence suggests that brain alterations in TLE extend beyond the paralimbic epicenter and impact macroscale function and cognitive functions, particularly memory. Using connectome-wide manifold learning and generative models of effective connectivity, we examined functional topography and directional signal flow patterns between large-scale neural circuits in TLE at rest. Studying a multisite cohort of 95 patients with TLE and 95 healthy controls, we observed atypical functional topographies in the former group, characterized by reduced differentiation between sensory and transmodal association cortices, with most marked effects in bilateral temporo-limbic and ventromedial prefrontal cortices. These findings were consistent across all study sites, present in left and right lateralized patients, and validated in a subgroup of patients with histopathological validation of mesiotemporal sclerosis and post-surgical seizure freedom. Moreover, they were replicated in an independent cohort of 30 TLE patients and 40 healthy controls. Further analyses demonstrated that reduced differentiation related to decreased functional signal flow into and out of temporolimbic cortical systems and other brain networks. Parallel analyses of structural and diffusion-weighted MRI data revealed that topographic alterations were independent of TLE-related cortical thinning but partially mediated by white matter microstructural changes that radiated away from paralimbic circuits. Finally, we found a strong association between the degree of functional alterations and behavioral markers of memory dysfunction. Our work illustrates the complex landscape of macroscale functional imbalances in TLE, which can serve as intermediate markers bridging microstructural changes and cognitive impairment.

Atypical cortical hierarchy in Aβ-positive older adults and its reflection in spontaneous speech

Abnormal deposition of Aβ amyloid is an early neuropathological marker of Alzheimer's disease (AD), arising long ahead of clinical symptoms. Non-invasive measures of associated early neurofunctional changes, together with easily accessible behavioral readouts of these changes, could be of great clinical benefit. We pursued this aim by investigating large-scale cortical gradients of functional connectivity with functional MRI, which capture the hierarchical integration of cortical functions, together with acoustic-prosodic features from spontaneous speech, in cognitively unimpaired older adults with and without Aβ positivity (total N = 188). We predicted distortions of the cortical hierarchy associated with prosodic changes in the Aβ + group. Results confirmed substantially altered cortical hierarchies and less variability in these in the Aβ + group, together with an increase in quantitative prosodic measures, which correlated with gradient variability as well as digit span test scores. Overall, these findings confirm that long before the clinical stage and objective cognitive impairment, increased risk of cognitive decline as indexed by Aβ accumulation is marked by neurofunctional changes in the cortical hierarchy, which are related to automatically extractable speech patterns and alterations in working memory functions.

Diffusion time-related structure-function coupling reveals differential association with inter-individual variations in body mass index

Body mass index (BMI) is an indicator of obesity, and recent neuroimaging studies have demonstrated that inter-individual variations in BMI are associated with altered brain structure and function. However, the mechanism underlying the alteration of structure-function correspondence according to BMI is under-investigated. In this study, we studied structural and functional connectivity derived from diffusion MRI tractography and inter-regional correlations of functional MRI time series, respectively. We combined the structural and functional connectivity information using the Riemannian optimization approach. First, the low-dimensional principal eigenvectors (i.e., gradients) of the structural connectivity were generated by applying diffusion map embedding with varying diffusion times. A transformation was identified so that the structural and functional embeddings share the same coordinate system, and subsequently, the functional connectivity matrix was simulated. Then, we generated gradients from the simulated functional connectivity matrix. We found the most apparent cortical hierarchical organization differentiating between low-level sensory and higher-order transmodal regions in the middle of the diffusion time, indicating that the hierarchical organization of the brain may reflect the intermediate mechanisms of mono- and polysynaptic communications. Associations between the functional gradients and BMI were strongest when the hierarchical structure was the most evident. Moreover, the gradient-BMI association map was related to the microstructural features, and the findings indicated that the BMI-related structure-function coupling was significantly associated with brain microstructure, particularly in higher-order transmodal areas. Finally, transcriptomic association analysis revealed the potential biological underpinnings specifying gene enrichment in the striatum, hypothalamus, and cortical cells. Our findings provide evidence that structure-function correspondence is strongly coupled with BMI when hierarchical organization is the most apparent and that the associations are related to the multiscale properties of the brain, leading to an advanced understanding of the neural mechanisms related to BMI.

Altered asymmetry of functional connectome gradients in major depressive disorder

Introduction

Major depressive disorder (MDD) is a debilitating disease involving sensory and higher-order cognitive dysfunction. Previous work has shown altered asymmetry in MDD, including abnormal lateralized activation and disrupted hemispheric connectivity. However, it remains unclear whether and how MDD affects functional asymmetries in the context of intrinsic hierarchical organization.

Methods

Here, we evaluate intra- and inter-hemispheric asymmetries of the first three functional gradients, characterizing unimodal-transmodal, visual-somatosensory, and somatomotor/default mode-multiple demand hierarchies, to study MDD-related alterations in overarching system-level architecture.

Results

We find that, relative to the healthy controls, MDD patients exhibit alterations in both primary sensory regions (e.g., visual areas) and transmodal association regions (e.g., default mode areas). We further find these abnormalities are woven in heterogeneous alterations along multiple functional gradients, associated with cognitive terms involving mind, memory, and visual processing. Moreover, through an elastic net model, we observe that both intra- and inter-asymmetric features are predictive of depressive traits measured by BDI-II scores.

Discussion

Altogether, these findings highlight a broad and mixed effect of MDD on functional gradient asymmetry, contributing to a richer understanding of the neurobiological underpinnings in MDD.

Functional gradients reveal cortical hierarchy changes in multiple sclerosis

Functional gradient (FG) analysis represents an increasingly popular methodological perspective for investigating brain hierarchical organization but whether and how network hierarchy changes concomitant with functional connectivity alterations in multiple sclerosis (MS) has remained elusive. Here, we analyzed FG components to uncover possible alterations in cortical hierarchy using resting-state functional MRI (rs-fMRI) data acquired in 122 MS patients and 97 healthy control (HC) subjects. Cortical hierarchy was assessed by deriving regional FG scores from rs-fMRI connectivity matrices using a functional parcellation of the cerebral cortex. The FG analysis identified a primary (visual-to-sensorimotor) and a secondary (sensory-to-transmodal) component. Results showed a significant alteration in cortical hierarchy as indexed by regional changes in FG scores in MS patients within the sensorimotor network and a compression (i.e., a reduced standard deviation across all cortical parcels) of the sensory-transmodal gradient axis, suggesting disrupted segregation between sensory and cognitive processing. Moreover, FG scores within limbic and default mode networks were significantly correlated (ρ = 0.30 $$ \rho =0.30 $$ , p < .005 after Bonferroni correction for both) with the symbol digit modality test (SDMT) score, a measure of information processing speed commonly used in MS neuropsychological assessments. Finally, leveraging supervised machine learning, we tested the predictive value of network-level FG features, highlighting the prominent role of the FG scores within the default mode network in the accurate prediction of SDMT scores in MS patients (average mean absolute error of 1.22 ± 0.07 points on a hold-out set of 24 patients). Our work provides a comprehensive evaluation of FG alterations in MS, shedding light on the hierarchical organization of the MS brain and suggesting that FG connectivity analysis can be regarded as a valuable approach in rs-fMRI studies across different MS populations.

The clinical, imaging, pathological and genetic landscape of bottom-of-sulcus dysplasia

Bottom-of-sulcus dysplasia (BOSD) is increasingly recognized as a cause of drug-resistant, surgically-remediable, focal epilepsy, often in seemingly MRI-negative patients. We describe the clinical manifestations, morphological features, localization patterns and genetics of BOSD, with the aims of improving management and understanding pathogenesis. We studied 85 patients with BOSD diagnosed between 2005-2022. Presenting seizure and EEG characteristics, clinical course, genetic findings and treatment response were obtained from medical records. MRI (3 T) and 18F-FDG-PET scans were reviewed systematically for BOSD morphology and metabolism. Histopathological analysis and tissue genetic testing were performed in 64 operated patients. BOSD locations were transposed to common imaging space to study anatomical location, functional network localization and relationship to normal MTOR gene expression. All patients presented with stereotyped focal seizures with rapidly escalating frequency, prompting hospitalization in 48%. Despite 42% patients having seizure remissions, usually with sodium channel blocking medications, most eventually became drug-resistant and underwent surgery (86% seizure-free). Prior developmental delay was uncommon but intellectual, language and executive dysfunction were present in 24%, 48% and 29% when assessed preoperatively, low intellect being associated with greater epilepsy duration. BOSDs were missed on initial MRI in 68%, being ultimately recognized following repeat MRI, 18F-FDG-PET or image postprocessing. MRI features were grey-white junction blurring (100%), cortical thickening (91%), transmantle band (62%), increased cortical T1 signal (46%) and increased subcortical FLAIR signal (26%). BOSD hypometabolism was present on 18F-FDG-PET in 99%. Additional areas of cortical malformation or grey matter heterotopia were present in eight patients. BOSDs predominated in frontal and pericentral cortex and related functional networks, mostly sparing temporal and occipital cortex, and limbic and visual networks. Genetic testing yielded pathogenic mTOR pathway variants in 63% patients, including somatic MTOR variants in 47% operated patients and germline DEPDC5 or NPRL3 variants in 73% patients with familial focal epilepsy. BOSDs tended to occur in regions where the healthy brain normally shows lower MTOR expression, suggesting these regions may be more vulnerable to upregulation of MTOR activity. Consistent with the existing literature, these results highlight (i) clinical features raising suspicion of BOSD; (ii) the role of somatic and germline mTOR pathway variants in patients with sporadic and familial focal epilepsy associated with BOSD; and (iii) the role of 18F-FDG-PET alongside high-field MRI in detecting subtle BOSD. The anatomical and functional distribution of BOSDs likely explain their seizure, EEG and cognitive manifestations and may relate to relative MTOR expression.

A latent clinical-anatomical dimension relating metabolic syndrome to brain structure and cognition

The link between metabolic syndrome (MetS) and neurodegenerative as well as cerebrovascular conditions holds substantial implications for brain health in at-risk populations. This study elucidates the complex relationship between MetS and brain health by conducting a comprehensive examination of cardiometabolic risk factors, brain morphology, and cognitive function in 40,087 individuals. Multivariate, data-driven statistics identified a latent dimension linking more severe MetS to widespread brain morphological abnormalities, accounting for up to 71% of shared variance in the data. This dimension was replicable across sub-samples. In a mediation analysis, we could demonstrate that MetS-related brain morphological abnormalities mediated the link between MetS severity and cognitive performance in multiple domains. Employing imaging transcriptomics and connectomics, our results also suggest that MetS-related morphological abnormalities are linked to the regional cellular composition and macroscopic brain network organization. By leveraging extensive, multi-domain data combined with a dimensional stratification approach, our analysis provides profound insights into the association of MetS and brain health. These findings can inform effective therapeutic and risk mitigation strategies aimed at maintaining brain integrity.

A WORLDWIDE ENIGMA STUDY ON EPILEPSY-RELATED GRAY AND WHITE MATTER COMPROMISE ACROSS THE ADULT LIFESPAN

Objectives

Temporal lobe epilepsy (TLE) is commonly associated with mesiotemporal pathology and widespread alterations of grey and white matter structures. Evidence supports a progressive condition although the temporal evolution of TLE is poorly defined. This ENIGMA-Epilepsy study utilized multimodal magnetic resonance imaging (MRI) data to investigate structural alterations in TLE patients across the adult lifespan. We charted both grey and white matter changes and explored the covariance of age-related alterations in both compartments.

Methods

We studied 769 TLE patients and 885 healthy controls across an age range of 17-73 years, from multiple international sites. To assess potentially non-linear lifespan changes in TLE, we harmonized data and combined median split assessments with cross-sectional sliding window analyses of grey and white matter age-related changes. Covariance analyses examined the coupling of grey and white matter lifespan curves.

Results

In TLE, age was associated with a robust grey matter thickness/volume decline across a broad cortico-subcortical territory, extending beyond the mesiotemporal disease epicentre. White matter changes were also widespread across multiple tracts with peak effects in temporo-limbic fibers. While changes spanned the adult time window, changes accelerated in cortical thickness, subcortical volume, and fractional anisotropy (all decreased), and mean diffusivity (increased) after age 55 years. Covariance analyses revealed strong limbic associations between white matter tracts and subcortical structures with cortical regions.

Conclusions

This study highlights the profound impact of TLE on lifespan changes in grey and white matter structures, with an acceleration of aging-related processes in later decades of life. Our findings motivate future longitudinal studies across the lifespan and emphasize the importance of prompt diagnosis as well as intervention in patients.

Age-related decrease in inter-subject similarity of cortical morphology and task and resting-state functional connectivity

"All old people are the same" is an unfortunate characterization of the perceived homogeneity in the older age group. This study attempts to debunk this myth in the context of the structural and functional brain. Within older relative to younger age groups, individuals are hypothesized to be more dissimilar to their similar-aged peers-thus demonstrating an age-related divergence. This study analyzed functional connectivity (FC) during multiple fMRI paradigms (2 rest + 5 tasks) and cortical thickness (CT) data from two lifespan datasets (Ntotal = 1161). On average, between-subject FC/CT correlations became weaker in the older age groups. Further analyses ruled out the possibility that more rapid age-related changes in older brains have increased the dissimilarity in these older age groups. Brain-wide analyses revealed significant effects of age-related divergence across most of the brain. Finally, CT similarity between a dyad significantly predicted their FC similarity across multiple fMRI task paradigms-demonstrating a close relationship between brain structure and function even at the between-dyad level. Contrary to the myth that "all old people are the same," these findings suggest young people are more similar to each other. This study presents major implications in the study of neural fingerprinting and brain-behavior associations.

Connectome-wide structure-function coupling models implicate polysynaptic alterations in autism

Autism spectrum disorder (ASD) is one of the most common neurodevelopmental diagnoses. Although incompletely understood, structural and functional network alterations are increasingly recognized to be at the core of the condition. We utilized multimodal imaging and connectivity modeling to study structure-function coupling in ASD and probed mono- and polysynaptic mechanisms on structurally-governed network function. We examined multimodal magnetic resonance imaging data in 80 ASD and 61 neurotypical controls from the Autism Brain Imaging Data Exchange (ABIDE) II initiative. We predicted intrinsic functional connectivity from structural connectivity data in each participant using a Riemannian optimization procedure that varies the times that simulated signals can unfold along tractography-derived personalized connectomes. In both ASD and neurotypical controls, we observed improved structure-function prediction at longer diffusion time scales, indicating better modeling of brain function when polysynaptic mechanisms are accounted for. Prediction accuracy differences (∆prediction accuracy) were marked in transmodal association systems, such as the default mode network, in both neurotypical controls and ASD. Differences were, however, lower in ASD in a polysynaptic regime at higher simulated diffusion times. We compared regional differences in ∆prediction accuracy between both groups to assess the impact of polysynaptic communication on structure-function coupling. This analysis revealed that between-group differences in ∆prediction accuracy followed a sensory-to-transmodal cortical hierarchy, with an increased gap between controls and ASD in transmodal compared to sensory/motor systems. Multivariate associative techniques revealed that structure-function differences reflected inter-individual differences in autistic symptoms and verbal as well as non-verbal intelligence. Our network modeling approach sheds light on atypical structure-function coupling in autism, and suggests that polysynaptic network mechanisms are implicated in the condition and that these can help explain its wide range of associated symptoms.

A latent clinical-anatomical dimension relating metabolic syndrome to brain structure and cognition

The link between metabolic syndrome (MetS) and neurodegenerative as well cerebrovascular conditions holds substantial implications for brain health in at-risk populations. This study elucidates the complex relationship between MetS and brain health by conducting a comprehensive examination of cardiometabolic risk factors, cortical morphology, and cognitive function in 40,087 individuals. Multivariate, data-driven statistics identified a latent dimension linking more severe MetS to widespread brain morphological abnormalities, accounting for up to 71% of shared variance in the data. This dimension was replicable across sub-samples. In a mediation analysis we could demonstrate that MetS-related brain morphological abnormalities mediated the link between MetS severity and cognitive performance in multiple domains. Employing imaging transcriptomics and connectomics, our results also suggest that MetS-related morphological abnormalities are linked to the regional cellular composition and macroscopic brain network organization. By leveraging extensive, multi-domain data combined with a dimensional stratification approach, our analysis provides profound insights into the association of MetS and brain health. These findings can inform effective therapeutic and risk mitigation strategies aimed at maintaining brain integrity.

Whole human-brain mapping of single cortical neurons for profiling morphological diversity and stereotypy

Quantifying neuron morphology and distribution at the whole-brain scale is essential to understand the structure and diversity of cell types. It is exceedingly challenging to reuse recent technologies of single-cell labeling and whole-brain imaging to study human brains. We propose adaptive cell tomography (ACTomography), a low-cost, high-throughput, and high-efficacy tomography approach, based on adaptive targeting of individual cells. We established a platform to inject dyes into cortical neurons in surgical tissues of 18 patients with brain tumors or other conditions and one donated fresh postmortem brain. We collected three-dimensional images of 1746 cortical neurons, of which 852 neurons were reconstructed to quantify local dendritic morphology, and mapped to standard atlases. In our data, human neurons are more diverse across brain regions than by subject age or gender. The strong stereotypy within cohorts of brain regions allows generating a statistical tensor field of neuron morphology to characterize anatomical modularity of a human brain.

Diverging asymmetry of intrinsic functional organization in autism

Autism is a neurodevelopmental condition involving atypical sensory-perceptual functions together with language and socio-cognitive deficits. Previous work has reported subtle alterations in the asymmetry of brain structure and reduced laterality of functional activation in individuals with autism relative to non-autistic individuals (NAI). However, whether functional asymmetries show altered intrinsic systematic organization in autism remains unclear. Here, we examined inter- and intra-hemispheric asymmetry of intrinsic functional gradients capturing connectome organization along three axes, stretching between sensory-default, somatomotor-visual, and default-multiple demand networks, to study system-level hemispheric imbalances in autism. We observed decreased leftward functional asymmetry of language network organization in individuals with autism, relative to NAI. Whereas language network asymmetry varied across age groups in NAI, this was not the case in autism, suggesting atypical functional laterality in autism may result from altered developmental trajectories. Finally, we observed that intra- but not inter-hemispheric features were predictive of the severity of autistic traits. Our findings illustrate how regional and patterned functional lateralization is altered in autism at the system level. Such differences may be rooted in atypical developmental trajectories of functional organization asymmetry in autism.