Biology subjects

Valk, S. L.

Publications and source records attributed to Valk, S. L..

At least 19 recordsLinked to original sources

bioRxiv2026

EigenBrain maps cortical molecular architecture from functional, geometric, and structural eigenmodes

Neurotransmitter receptor and transporter distributions shape neural communication across the cortex and underpin mechanistic interpretations of brain function. Magnetic resonance imaging (MRI)-derived eigenmodes, low-dimensional spatial patterns that capture the principal axes of cortical organization, are increasingly used to reconstruct brain maps and offer a potential route to approximating molecular topographies in large cohorts where direct measurements are unavailable. Yet whether the type of MRI data used to derive these eigenmodes determines which receptor and transporter distributions can be approximated, and which molecular systems are accessible through this approach at all, remains unknown. Using a spatial reconstruction framework applied to 23 molecular systems spanning neurotransmitter, metabolic, and pathological markers, we show that eight receptor and transporter maps, spanning serotonin, dopamine, histamine, cholinergic, and opioid markers, can be selectively approximated from functional eigenmodes but not structural or geometric ones. This selectivity also reveals that functional brain organization encodes a specific subset of neuromodulatory topographies that structural and geometric organization does not. To illustrate translational potential in clinical cohorts where molecular imaging is unavailable, we applied individual-level eigenmode decompositions of MRI data projected onto the eight validated molecular systems and detected cross-sectional differences in autism and longitudinal changes in schizophrenia. Together, these findings reveal a difference in how geometric, structural, and functional brain organization relate to molecular architecture, offering a method for approximating validated molecular profiles in population neuroimaging cohorts that lack direct molecular imaging.

neuroscience↗

bioRxiv2026

Structural Brain Co-Maturation In The Neonatal Period

Background. The neonatal period is characterized by neurodevelopmental processes coinciding with rapid physiological transitions, however, spatial patterns of brain expansion in early life remain incompletely characterized. Here, we leverage grey matter structural covariance in term- and preterm-born neonates to study the interregional synchrony of neonatal brain maturation along principal brain organizational axes. Methods. We used structural MRI data from the developing Human Connectome Project (n=525; 435 term-born) scanned at 37-44 weeks postmenstrual age (PMA)), stratifying the sample by term status and PMA. Based on cortical thickness (CT) and surface area (SA) metrics, we computed age group- (CVg) and individual-level (CVi) structural covariance matrices. Applying surface-based linear models, we identified changes in interregional covariance with postmenstrual age (PMA) and gestational age at birth (GAB), and contextualized alterations to neonatal functional networks. Using gradient decomposition, we identified major trajectories of cortical expansion on individual and group levels, and determined their correlation to archetypal geometric, evolutionary, and functional axes. Results. We found age-related changes reflecting cortical expansion and an increased structural differentiation with age. Gradient decomposition of group-level covariance revealed that primary components followed both an posterior-anterior distribution, anchored in the visual cortex, and a sensorimotor-association gradient. Individual-level covariance gradients adhered most to geometric axes, and diverged from a sensorimotor-association pattern with increasing PMA. Term-born neonates exhibited a higher spatial correlation to functional and geometric axes than preterm-born neonates, overall pointing to different expansion patterns in neonates of the same PMA. Conclusion. We found trajectories of structural maturation in the neonatal period that appear coordinated along geometric and functional axes. On an age group level, term-born neonates appear to follow archetypal axes more than preterm-borns at term-equivalent age, underlining differential expansion patterns in preterm-born neonates.

neuroscience↗

bioRxiv2026

Distinct spatial associations of adversity with hippocampal macro- and microstructure in early adolescence

Youth adversity has been associated with alterations in hippocampal structure; however, it remains unclear whether different forms of adversity relate distinctly to its organization across the anterior-posterior and proximal-distal axes. Here, we investigated the associations of different types of adversity with multiple structural properties of the hippocampus in 5,263 early adolescents from the ABCD Study. Hippocampal macrostructure was characterized using volume, thickness, and gyrification, whereas T1w/T2w ratio served as an in vivo proxy for microstructure. Adversity was assessed at the family level using questionnaires on family environment and parenting, and at the socioeconomic level using income-to-needs ratio and neighborhood disadvantage measured by the Area Deprivation Index. Associations were examined for each adversity type separately in multi-variate analyses and for cumulative adversity exposure in univariate models. Hippocampal features were obtained using HippUnfold, an advanced automatic segmentation approach that accounts for interindividual folding variability, and were analyzed globally as well as across the hippocampal anterior-posterior and proximal-distal axes. Socioeconomic measures showed widespread associations with hippocampal macrostructure across the whole hippocampus and both anatomical axes, whereas associations with T1w/T2w ratio were limited and observed only for neighborhood disadvantage along the anterior-posterior axis. Cumulative adversity exposure was consistently associated with alterations in CA1 and subiculum across volume, thickness, and gyrification, but not T1w/T2w ratio. Together, these findings suggest that different types of adversity exhibit distinct spatial associations across complementary hippocampal macro- and microstructural features, highlighting regional variation in the susceptibility of the developing hippocampus to environmental adversity.

neuroscience↗

bioRxiv2026

Selective convergence and graded divergence of hippocampal and amygdala subregions using functional connectivity

The hippocampus and amygdala are neighboring medial temporal lobe structures linked to memory and affect, yet how their subregions are jointly embedded within distributed isocortical systems remains unclear. Using resting-state fMRI from 722 Human Connectome Project Young Adult participants, we mapped hippocampal and amygdalar subregions within a unified cortex-wide framework, quantifying subregion-to-cortex connectivity via Pearson correlation (broad co-fluctuation) and GLASSO partial correlation (relatively more direct functional association). We introduced two count-based metrics: dominance (relative hippocampal vs. amygdalar representation) and sharedness (balanced co-representation). Direct associations showed both structures sharing coupling with paralimbic areas and, more modestly, default mode regions, while broader co-fluctuations extended into somatomotor and paralimbic networks. Divergence patterns depended on the estimator: hippocampal subregions preferentially coupled with default-mode and visual networks under direct association, while amygdalar nuclei favored ventral attention and limbic networks; broader co-fluctuations additionally implicated somatomotor cortex for amygdala and visual cortex for hippocampus. These principles held at the subfield/nucleus level, varying along the hippocampal long axis and identifying the paralaminar nucleus as the most hippocampus-like amygdalar subregion. Data-driven connectivity gradients confirmed both systems separation and fine-scale interdigitation. Hippocampal and amygdalar subregions are thus embedded in cortex not as discrete systems, but through structured, spatially organized co-representation.

neuroscience↗

bioRxiv2026

Nucleus-level thalamic organization anchors multimodal signatures of thalamocortical maturation

The human thalamus is composed of multiple nuclei that differ in structure and function. From early development onwards, these nuclei form reciprocal, nucleus-specific connections with the cerebral cortex, contributing to sensory and cognitive processing. In childhood and adolescence, a key period of neurocognitive development, these connections undergo widespread refinement, yet how developmental trajectories of thalamocortical connections vary across nuclei remains unknown. Here, we leveraged the Human Connectome Project in Development dataset (HCP-D, N = 604, age range 8-21) and segmented 10 thalamic nuclei using a segmentation approach optimized for intrathalamic contrast. Applying probabilistic tractography, we reconstructed nucleus-specific thalamocortical connections and charted their maturational profiles based on changes in fractional anisotropy (FA) using generalized additive models. We found FA to increase in thalamocortical connections, with nucleus-specific variation in temporal profiles and magnitude of age effects. Connections of core-cell-rich, sensory-projecting nuclei, such as the lateral geniculate nucleus, showed earlier maturational plateaus, whereas matrix-cell-rich, association-projecting nuclei, such as ventral anterior nucleus, showed more sustained maturation. This links maturational heterochronicity to thalamic organization of cell distribution and connectivity embedding. In parallel, functional thalamocortical connectivity decreased with age, with FA and functional connectivity age effects coupled in nucleus-connections showing prolonged maturation. Finally, concordant age effects in connectivity and nucleus volumes suggest that intra-nucleus remodeling may support refinement of structural connections while reducing thalamocortical functional synchrony. Together, our work reveals that thalamocortical maturation is anchored in the developmental and organizational heterogeneity of thalamic nuclei, offering a framework for understanding how diverse thalamic nuclei contribute to neurocognitive development.

neuroscience↗

bioRxiv2026

Structural brain networks shape individual-level progression of brain atrophy after stroke

Stroke starts as a focal vascular lesion, but its structural consequences often extend beyond the lesion site, resulting in distributed brain atrophy whose organizing principles remain unclear. Here, using longitudinal MRI data from two stroke cohorts spanning the hyperacute to chronic stages, we tested whether and how post-stroke grey matter volume (GMV) change over time is constrained by large-scale brain networks across individuals. Coordinated deformation modelling showed that longitudinal GMV atrophy patterns were more strongly shaped by structural than by functional connectivity, with structural constraints already detectable in the acute phase. Network diffusion modelling further showed that atrophy patterns at 3 and 12 months were consistent with lesion-initiated propagation on the structural connectome, whereas model performance was weak in the early acute stage. The model-derived propagation stage did not increase monotonically with chronological time, indicating that it reflects the degree to which observed atrophy conforms to a network-consistent diffusion-like pattern rather than elapsed biological time. Inter-individual variation in propagation stage was associated with lesion size and with the topological and molecular properties of lesioned regions. Finally, lesion information combined with network diffusion modelling supported individualized prediction of later GMV atrophy patterns. These findings provide a network-based account of secondary degeneration after stroke and may inform individualized characterization of post-stroke structural reorganization.

neuroscience↗

bioRxiv2026

Individual differences reveal distinct age and pubertal contributions to the refinement of the functional cortical hierarchy during adolescence

The development of the functional cortical hierarchy, spanning sensorimotor to association systems, is exclusively studied as a function of age. During adolescence, this overlooks puberty as a major neurodevelopmental driver and source of variability. We studied sensorimotor-association axis refinement longitudinally (6323 observations across 4919 subjects), leveraging individual differences to disentangle chronological age from pubertal effects. We derived low dimensional features of sensorimotor-association axis development from resting-state functional connectomes, revealing substantial inter-individual heterogeneity in maturational trajectories that challenge group-level developmental trends and milestones. Then, we demonstrate independent effects of age and pubertal stage on sensorimotor-association axis refinement through the polarization of the cortical hierarchy. We further show that coordinated system-level shifts in network topology reflect an ongoing specialization of functional connectivity profiles across all major functional networks. Our findings frame adolescent hierarchical functional cortical maturation as an individualized, multifactorial phenomenon shaped by distinct chronological age and pubertal processes.

neuroscience↗

bioRxiv2026

Pharmacodynamic profiles inform systematization, efficacy and whole-brain drug distribution profiles in 18 antidepressants

Although empirical evidence shows that antidepressants are effective and superior to placebo in treating depressive disorders, their mechanisms of action are still unclear. In this study, we examine the multidimensional molecular affinities of 18 commonly used antidepressants. Clustering analyses consistently generate three distinct clusters, providing a broader taxonomy that groups SSRIs and SNRIs together. Correlational analyses cautiously indicate a relationship between the affinity to metabotropic serotonin receptors and antidepressant efficacy. Next, we generate anatomical distribution profiles of drug action strengths by combining positron emission tomography-derived maps of cerebral neurotransmitter receptor and transporter densities from an open-access repository of healthy participants with the drugs affinity profiles. We then relate these profiles to functional and structural neuroanatomical measures in health and disease. Our results reveal distinct, mechanistically interpretable differences between antidepressants with high 5-HTT affinity and atypical antidepressants. These differences could inform personalized drug selection and development.

neuroscience↗

bioRxiv2026

Whole-brain drug distribution profiles of psychedelic drugs provide insights into rapid antidepressant action

Recent studies pioneered the use of classic hallucinogens as rapid-acting antidepressants (RAAD). To further understand the link between their neuromodulatory and antidepressant effects, we combine pharmacodynamic profiles of four classic hallucinogens and the anaesthetic Ketamine with receptor density distributions from both Positron Emission Tomography (PET) and layer-resoluted autoradiography studies to develop anatomical distribution profiles of drug action strengths giving a comparative measure how strong a drug would act in a region of interest. PET-based, we find high action strengths in association cortices for classic hallucinogens, which we contextualise anatomically using functional and cytoarchitectural measures. Autoradiography-based, we observe high action strengths in the supragranular layer and multimodal temporal areas. Finally, we show how Ketamines affinity to high-affinity subtypes of 5-HT2a and D2 receptors produce classic hallucinogen-like neuroanatomical trends. Through highlighting high RAAD action strengths in regions with emotion processing functionality, our results contribute to a mechanistic understanding of rapid antidepressant action.

neuroscience↗

bioRxiv2025

cuBNM: GPU-Accelerated Brain Network Modeling

Brain network modeling uses computer simulations to infer about latent neural properties at micro- and mesoscales by fitting brain dynamic models to empirical data of individual subjects or groups. However, computational costs of (individualized) model fitting is a major bottleneck, limiting the practical feasibility of this approach to larger cohorts and more complex models, and highlighting the need for scalable simulation implementations. Here, we introduce cuBNM, a Python package which leverages parallel processing of graphics processing units to massively accelerate simulations of brain network models. We show running simulations on graphics processing units is several hundred times faster compared to central processing units. We demonstrate the usage of cuBNM by running optimization of group-level and individualized low- and high-dimensional models. As examples of the utility of individualized models, we investigated test-retest reliability and heritability of simulated and empirical measures in the Human Connectome Project dataset. We found simulated features were fairly reliable and significantly heritable, suggesting their biological plausibility. Overall, cuBNM enables large-scale simulations of brain network models, opening new avenues for studying latent neural processes across diverse populations, dense networks, and high-dimensional models, which was previously impractical due to computational constraints.

neuroscience↗

bioRxiv2025

Cerebellar growth is associated with domain-specific cerebral maturation and socio-linguistic behavioral outcomes

The cerebellums involvement in cognitive functions is increasingly recognized, yet its developmental contribution to cognition remains poorly understood. The cerebellum undergoes rapid development in early life, paralleling major cognitive and behavioral changes. Although clinical studies have linked early cerebellar disruptions to profound developmental deficits, it remains largely unclear how typical cerebellar maturation supports the development of cognitive functions and how it interacts with broader brain development. Here, we apply a normative modeling framework to map cerebellar volumetric growth from infancy to young adulthood (N = 751; ages 1-21 years). Using lobular and functional cerebellar parcellations, we comprehensively characterize typical cerebellar development and examine how it aligns with cerebral development and behavioral outcomes. Across parcellations, posterior higher association areas consistently show steeper growth trajectories than anterior sensorimotor areas. Cerebellar and cerebral areas with similar functional roles demonstrate coordinated maturation, and volumetric growth in the posterior cerebellum relates to individual differences in socio-linguistic behaviors. These findings establish a comprehensive reference for typical cerebellar development, highlight cerebellar co-maturation with the cerebral cortex, and underscore the cerebellums role in supporting emerging higher cognitive functions.

neuroscience↗

bioRxiv2024

Bias-accounting meta-analyses overcome cerebellar neglect to refine the cerebellar behavioral topography

The cerebellum plays important roles in motor, cognitive, and emotional behaviors. Previous cerebellar coordinate-based meta-analyses (CBMAs) have complemented precision-mapping and parcellation approaches by finding generalizable cerebellar activations across the largest possible set of behaviors. However, cerebellar CBMAs face challenges due to inherent methodological limitations exacerbated by historical cerebellar neglect in neuroimaging. Here, we show overrepresentation of superior activations, rendering the null hypothesis of standard activation likelihood estimation (ALE) unsuitable. Our new method, cerebellum-specific ALE (C-SALE), finds behavioral convergence beyond baseline activation rates. It does this by testing experimental activations versus null models sampled from a data-driven probability distribution of finding activations at any cerebellar location. Task-specific mappings in the BrainMap meta-analytic database illustrated improved specificity of the new method. Multiple (sub)domains reached convergence in specific cerebellar subregions, supporting dual motor representations and placing cognition in posterior-lateral regions. We show our method and findings were replicable within NeuroSynth. Across both databases, 54/138 task domains or behavioral terms, including sustained attention, somesthesis, inference, anticipation and rhythm, reached convergence in specific cerebellar subgregions. Maps largely corresponded with cerebellar atlases but also showed many complementary mappings. Repeated subsampling showed that motor behaviors, and to a lesser extent language and working memory, mapped to especially consistent cerebellar subregions. Lastly, we found that cerebellar clusters were parts of brain-wide coactivation networks with cortical and subcortical regions implied in these behaviors. Together, our method further complements and expands understanding of cerebellar involvement in human behavior, highlighting regions for future investigation in both basic and clinical applications. Highlights[bullet] Biases in reported cerebellar activations strongly favors superior regions. [bullet]A new method of meta-analysis increases cerebellar mapping specificity and accuracy. [bullet]Large-scale meta-analyses support cerebellar roles in cognitive, affective, and motor behaviors. [bullet]54 task domains/ terms converged, including sustained attention, somesthesis, inference, anticipation and rhythm. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=100 SRC="FIGDIR/small/621398v3_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@716ea0org.highwire.dtl.DTLVardef@11601fforg.highwire.dtl.DTLVardef@1dd1208org.highwire.dtl.DTLVardef@caf535_HPS_FORMAT_FIGEXP M_FIG Graphical abstract C_FIG

neuroscience↗

bioRxiv2024

Bridging Glucose Metabolism and Intrinsic Functional Organization of the Human Cortex

The human brain requires a continuous supply of energy to function effectively. Here, we investigated how the low-dimensional organization of intrinsic functional connectivity patterns based on resting-state functional magnetic resonance imaging relates to brain energy expenditure measured by fluorodeoxyglucose positron emission tomography. By incrementally adding more dimensions of brain organization (via functional gradients), we were able to show that increasing amounts of variance in the map of brain energy expenditure could be accounted for. In particular, the brain organization dimensions that explained a large amount of the variance in intrinsic brain function also explained a large amount of the regional variance in the energy expenditure maps. This was particularly true for brain organization maps based on the strongest connections, suggesting that "weak" connections may not explain as much energy variance. Notably, our topological model was more effective than random brain organization configurations, suggesting that brain organization may be specifically associated with energy optimization. Finally, using brain asymmetry as a model for metabolic efficiency, we found that optimizing energy expenditure independently in each hemisphere outperformed non-independent optimization. This supports the concept of hemispheric competition rather than lateralization in energy allocation. Our results demonstrate how the spatial organization of functional connections is systematically linked to optimized energy expenditure in the human brain, providing new insights into the metabolic basis of brain function.

neuroscience↗

bioRxiv2024

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 ultrahigh 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 medio-lateral 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 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.

neuroscience↗

bioRxiv2024

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.

neuroscience↗

bioRxiv2024

Contracted anterior-posterior systematic covariance of cortical thickness in early-onset schizophrenia

Background and HypothesisSchizophrenia is a neurodevelopmental condition with alterations in both sensory and association cortical areas. These alterations have been reported to follow structural connectivity patterning, and to occur in a system-level fashion. Here, we investigated whether pathological alterations of schizophrenia originated from an early disruption of cortical organization by using 7-17-years-old individuals with early-onset schizophrenia (EOS). Study DesignWe estimated cortical thickness using T1-weighted structural MRI data from 95 patients with antipsychotic-naive first-episode EOS and 99 typically developing (TD) controls. We then computed structural covariance of cortical thickness and estimated system-level organizational axes by performing nonlinear dimensionality reduction techniques on covariance matrices for the EOS and TD groups. Finally, we tested for group differences between EOS and TD individuals in terms of both structural covariance and covariance distances along the systematic axis. Study ResultsThe first covariance gradient differentiated motor regions from other cortical areas. Similar to the macrostructural axis in adults, the second gradient axis in young TD discriminated anterior from posterior regions and was compressed in EOS patients relative to TD controls. In addition, patients showed increased structural covariance between two ends of the systematic axis, with increased geodesic distance of covarying regions between two ends. ConclusionOur findings revealed a contracted organizational axis of cortical thickness in EOS patients, which was attributed to excessive distally coordinated changes between anterior and posterior regions of the cortex. Taken together, our study suggests a possible early disruption of system-level neurodevelopment in schizophrenia.

pathology↗

bioRxiv2024

Exploring sex-specific neuroendocrine influences on the sensorimotor-association axis in single individuals

Human neuroimaging studies consistently show multimodal patterns of variability along a key principle of macroscale cortical organization - the sensorimotor-association (S-A) axis. However, little is known about day-to-day fluctuations in functional activity along this axis within an individual, including sex-specific neuroendocrine factors contributing to such transient changes. We leveraged data from two densely sampled healthy young adults, one female and one male, to investigate intra-individual daily variability along the S-A axis, which we computed as our measure of functional cortical organization by reducing the dimensionality of functional connectivity matrices. Daily variability was greatest in temporal limbic and ventral prefrontal regions in both participants, and was more strongly pronounced in the male subject. Next, we probed local and system-level effects of steroid hormones and self-reported perceived stress on functional organization. Our findings revealed modest effects that differed between participants, hinting at subtle -potentially sex-specific- associations between neuroendocrine fluctuations and intra-individual variability along the S-A axis. In sum, our study points to neuroendocrine factors as possible modulators of intra-individual variability in functional brain organization, highlighting the need for further research in larger samples.

neuroscience↗

bioRxiv2024

Pharmaco-resistant temporal lobe epilepsy gradually perturbs the cortex-wide excitation-inhibition balance

AO_SCPLOWBSTRACTC_SCPLOWExcitation-inhibition (E/I) imbalance is theorized as a key mechanism in the pathophysiology of epilepsy, with a mounting body of previous research focusing on elucidating its cellular manifestations. However, there are limited studies into E/I imbalance at macroscale and its microcircuit-level mechanisms and clinical associations. In our current work, we computed the Hurst exponent--a previously validated index of the E/I ratio--from resting-state fMRI time series, and simulated microcircuit parameters using biophysical computational models. We found a broad reduction in the Hurst exponent in pharmaco-resistant temporal lobe epilepsy (TLE), indicative of a shift towards more excitable network dynamics. Connectome decoders pointed to temporolimbic and frontocentral areas as plausible network epicenters of E/I imbalance. Computational simulations further revealed that enhancing cortical excitability in patients likely reflected atypical increases in recurrent connection strength of local neuronal ensembles. Moreover, mixed cross-sectional and longitudinal analyses revealed heightened E/I elevation in patients with longer disease duration, more frequent electroclinical seizures and inter-ictal epileptic spikes, and worse cognitive functioning. Replicated in an independent dataset, our work provides compelling in-vivo evidence of a macroscale shift in E/I balance in TLE patients that undergoes progressive changes and underpins cognitive impairments, potentially informing treatment strategies targeting E/I mechanisms.

neuroscience↗