Biology subjects

Ngo, A.

Publications and source records attributed to Ngo, A..

At least 19 recordsLinked to original sources

bioRxiv2026

Differential subcortical-cortical circuit reorganization in autism and ADHD

Autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) often co-occur and share symptoms as well as genetic risk factors. While subcortical-cortical networks have been implicated in both conditions, particularly involving thalamic and striatal circuits, patterns of shared and diverging disruptions remain unclear. Here we integrated resting-state functional connectivity (FC) and regression dynamic causal modeling (rDCM) across a transdiagnostic multi-site cohort. We used statistical group comparisons and individualized normative deviation mapping to map network deviations in ASD and ADHD relative to neurotypical controls and against one another. Multivariate associative techniques examined associations to clinical and cognitive phenotypes. Our transdiagnostic analyses revealed significant differentiation of ASD and ADHD across subcortical-cortical circuits. While ASD was characterized by widespread thalamocortical hyperconnectivity and bidirectional elevated coupling across thalamic subdivisions, ADHD exhibited a focal pattern of striatocortical disruption, anchored predominantly within the caudate. Multivariate analyses identified shared and disorder-specific brain-behavior associations. Across both conditions, aberrant striatocortical signaling was associated with reduced overall intelligence measures. Clinically, ASD-related thalamocortical connectivity disruptions mapped onto generalized cognitive impairment, whereas ADHD-related subcortical alterations tracked hyperactive and inattentive symptom dimensions. Our findings differentiate ASD and ADHD through distinct patterns of functional and directional subcortical-cortical dysregulations.

neuroscience↗

bioRxiv2026

RADIAL AND TANGENTIAL FIBER COMPONENTS IN HUMAN SUPERFICIAL WHITE MATTER AND THEIR ASSOCIATIONS WITH MACROSCALE FUNCTION

The superficial white matter (SWM), a thin layer of white matter beneath the cortex, contains a complex arrangement of short- and long-range fiber systems that support communication between cortical regions. These fiber populations include subcortical U-shaped fibers (U-fibers) that predominantly follow a tangential trajectory along the gray matter-white matter interface and long-range fibers that extend more radially through the deeper white matter to connect distant cortical regions. Here, we developed a surface-based framework to dissociate radial and tangential fiber components within the human SWM and investigated their microstructural properties and functional relevance using in-vivo high-field MRI. These components were quantified using apparent fiber density (AFD), fractional anisotropy (FA), and mean diffusivity (MD). We further contextualized SWM fiber architecture by examining depth-dependent microstructural profiles and their relationship with normative patterns of cortical organization and hierarchical specialization. The anatomical assessment of the proposed fiber orientation separation was supported by tractography-based bundle analyses, while the anatomical accuracy of tractography reconstructions was confirmed through comparison with post-mortem white matter dissection data. To assess their functional relevance, the fiber predominance map derived from radial and tangential AFD was related to spatial patterns of functional variability across the cortex. Regions with greater radially oriented fiber contribution exhibited more gradual changes in functional similarity across geodesic distance, whereas tangentially oriented fiber-enriched regions showed more rapid local functional differentiation. These findings reveal distinct structural and functional signatures of radial and tangential SWM fiber components and provide a framework for investigating their contributions to cortical organization and functional specialization. SIGNIFICANCE STATEMENTThe human cerebral cortex is organized into specialized regions that support diverse functions, but the structural principles underlying this organization remain incompletely understood. The superficial white matter (SWM), a thin layer of white matter beneath the cortex, contains intermingled short- and long-range fiber systems that support communication between cortical regions. However, these fiber populations have remained difficult to characterize because they are closely intertwined within the SWM. By developing a reproducible framework for mapping and quantifying distinct SWM fiber systems, this work provides a foundation for systematic investigation of this complex compartment. Integration of multimodal datasets, together with open sharing of analytical tools and standardized features, promotes transparency, reproducibility, enabling future studies of how superficial connectivity supports brain organization.

neuroscience↗

bioRxiv2026

Assessing the Functional-Structural Reorganization of Connector Hubs in Temporal Lobe Epilepsy

Temporal lobe epilepsy (TLE) is associated with altered functional connectivity, yet its effects on connector hubs, regions supporting long-range and inter-network communication, remain poorly understood. We used SParsity-based Analysis of Reliable k-hubness to characterize connector hub reorganization in unilateral TLE compared with healthy controls. Patients exhibited significant widespread reductions in k-hubness involving the occipital, cingulate, and precuneus regions, ipsilateral hippocampus, and the bilateral pallidum. Compared to the distribution of k-hubness in healthy controls, the hub disruption index revealed rapid loss of k-hubness alongside emergence of new hubs in contralateral homologous regions. To investigate microstructural substrates of these functional changes, apparent diffusion coefficient and fractional anisotropy from diffusion magnetic resonance imaging were examined. The strongest associations with k-hubness were observed in subcortical structures and the hippocampus. These findings demonstrate that TLE is characterized by widespread, asymmetric connector hub reorganization extending beyond the epileptogenic temporal lobe, revealing distinct patterns of network disruption and reorganization across the brain.

neuroscience↗

bioRxiv2026

Disrupted Brain Organoid Circuitry, Structural Organization, and Spine Morphology in 7q11.23 Copy Number Variant Syndromes

The 7q11.23 chromosomal region represents a model of gene dosage-dependence, where a hemizygous deletion causes Williams Syndrome (WS) and a duplication leads to 7q11.23 Duplication Syndrome (Dup7). It is not understood how these copy number variations (CNVs) disrupt development and functional cortical circuit assembly. Utilizing iPSC-derived cerebral organoids and longitudinal imaging from post-differentiation day 30 to 150, we characterized the aberrant neural rosette morphogenesis in WS and Dup7 during early stages, establishing an early structural divergence from control lines. We observed accelerated early cortical rosette morphogenesis in WS, characterized by a premature increase in both rosette number and layer thickness compared to controls. In contrast, Dup7 organoids consistently exhibit a significantly lower number and reduced thickness of rosettes from early stages onward. This early structural disruption progressively impacted synaptic-level architecture as the organoids matured. Dendritic spine characterization at later stages revealed Dup7 organoids exhibited a significantly higher dendritic spine density compared to WS. Pharmacological antagonism of CCR5 (C-C chemokine receptor type 5) with Maraviroc significantly enhanced dendritic spine density in control and WS organoids; however, this effect was absent in Dup7. To determine how these structural anomalies translate into circuit-level behavior, we performed longitudinal calcium imaging using GCaMP. Control organoids sustained synchronized activity and high spike correlations at all time points. This synchronization was delayed and highly transient in WS organoids, and completely abolished in Dup7 organoids, which exhibit significantly low spike correlations at all stages. Developmentally, GABA changes from acting as an excitatory signal in the immature brain to an inhibitory signal as the brain matures. As control lines matured gabazine-induced desynchronization progressively diminished, but persisted in WS organoids. Dup7 organoids failed to establish synchronization at any developmental time point, but displayed a negligible increased synchrony following gabazine treatment. These functional aberrations were paralleled by genotype-specific defects in structural organization, specifically in rosette morphogenesis and dendritic spine density. Collectively, our findings demonstrate that 7q11.23 CNVs trigger pathogenic neurodevelopmental defects by derailing the trajectories of structural organization, circuit assembly, and functional synchronization during cortical maturation.

neuroscience↗

bioRxiv2026

HippoGenes: A robust workflow for subregional transcriptomic profiling of the human hippocampus

The human hippocampus is a unique cortical structure central to brain function, plasticity, and disease. Unravelling its complex organization requires the integration of multiscale data, linking molecular features to mesoscale anatomy and macroscale functional patterns. Gene expression is a fundamental microscale phenotype, and its profiling can provide a reference description of how molecular features are distributed across the brain. Capitalizing on recent imaging-transcriptomic analyses, we introduce HippoGenes, a repository of fine-grained gene expression patterns across human hippocampal subregions. We leveraged spatial statistical models and hippocampal surface mapping to reconstruct dense transcriptomic maps from sparse post-mortem tissue samples of the Allen Human Brain Atlas, generating continuous expression estimates for thousands of genes aligned to a common surface-based coordinate system. We illustrate the utility of HippoGenes to (i) map medial-lateral and anterior-posterior transcriptomic gradients that align with subfield and tripartite subdivisions of the hippocampal formation, (ii) examine associations between gene expression and canonical microstructural and functional features of the hippocampus, and (iii) perform a molecular decoding of subregional alterations in neurological patients with hippocampal pathology. HippoGenes provides a framework for exploring the molecular organization of the hippocampus, opening avenues for multiscale integration in health and disease, and is openly available on https://hippogenes.readthedocs.io/.

neuroscience↗

bioRxiv2026

A surface-intrinsic framework for topology-preserving hippocampal alignment and precision morphometry

Accurate alignment of hippocampal anatomy across individuals remains challenging due to complex and highly variable folding patterns that are not well captured by conventional volumetric approaches. HippUnfold introduced a surface-based representation of the hippocampus, but key components--including coordinate estimation and inter-subject correspondence--were defined in the volumetric domain, making them susceptible to topological errors and interpolation artifacts. Here, we introduce a surface-intrinsic formulation of hippocampal unfolding in which geometry, intrinsic coordinates, and correspondence are defined directly on subject-specific surface manifolds. Intrinsic anterior-posterior and proximal-distal coordinates are computed by solving Laplace equations on the surface, and correspondence is established through surface-based resampling in unfolded space, replacing inverse volumetric warping. Relative to the original HippUnfold approach, this formulation improves test-retest consistency, subject identifiability, and mesh quality, while better preserving subject-specific gyral and sulcal morphology. Surface representations show reduced distortion between folded and unfolded spaces and eliminate misplaced or outlier vertices associated with volumetric warping. These improvements translate to enhanced sensitivity in a clinical application, improving lateralization of temporal lobe epilepsy. These results demonstrate that a surface-intrinsic formulation provides a principled and robust foundation for hippocampal unfolding, enabling topology-preserving alignment and more accurate characterization of inter-individual variability in health and disease.

neuroscience↗

bioRxiv2026

Bacteriophage treatment of Pseudomonas aeruginosa PA14 infection does not alter the native microbiome of Caenorhabditis elegans

Bacteriophage therapeutics are alternatives to antibiotics for treating multi-drug-resistant (MDR) bacterial infections. Bacteriophages kill host bacteria species with targeted precision, unlike the broad-spectrum nature of antibiotics. While the precision and the natural occurrence of phages in the environment have drawn attention to phages as new "drugs" in the time of accelerated antibiotic resistance, it remains poorly understood how phage treatment impacts the community of organisms composing the microbiome. Before phage therapies can be more widespread in practice, this understanding is required. Caenorhabditis elegans lends itself as an excellent model organism to address this question, as worm populations are raised under sterile conditions and the gut microbiome can be populated experimentally by the worms natural bacterivore diet. Here we have established a C. elegans infection and phage treatment model using fluorescent Pseudomonas aeruginosa PA14 to quantify infection. We isolated and whole genome sequenced PA14-specific lytic phage from wastewater samples near West Point, New York. To characterize the impact of treatment on the microbiome, we populated the C. elegans gut microbiome with 11 strains of the native C. elegans microbiome (CeMbio) and used PacBio sequencing of the full length 16S rRNA gene to characterize the microbiome during PA14 infection in the presence and absence of phage treatment (n = 100 worms per sample, 4 replicates per condition). Taxonomic classification, phylogenetic analysis, and diversity analysis performed using a HiFi 16S bioinformatics pipeline revealed that phage treatment and infection level did not change the overall composition of the C. elegans gut microbiome. ImportanceMultidrug resistant infections are emerging faster than new antibiotic compounds can be synthesized. Bacteriophages are natural viruses of bacteria that seek out and kill only their host bacteria species. Bacteriophage therapeutics are a promising solution for drug resistant infections in patients where no other treatment exists. However, while phage treatment is effective, there is little understanding about what happens within the complex community of the microbiome when a phage treatment is employed. Here we establish a new model utilizing C. elegans to integrate a multidrug resistant infection, phage treatment, and the native microbiome of the C. elegans worm to address how the microbiome changes in response to phage treatment. We find that the microbiome remains unchanged after bacteriophage treatment, highlighting the targeted specificity of phage therapy and suggests fewer side effects for phage therapy than antibiotic treatment for the same infection.

microbiology↗

bioRxiv2026

FUNCTIONAL FRAGMENTATION AND STRUCTURAL DRIVERS OF THALAMO-CORTICAL CIRCUITS IN TEMPORAL LOBE EPILEPSY

AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSObjectiveC_ST_ABSIn temporal lobe epilepsy (TLE), the thalamus acts as a nexus in a pathophysiological network that implicates mesiotemporal, subcortical, and neocortical regions. Studying a large multimodal and multicentre dataset, we profiled thalamic, hippocampal, and neocortical functional connectivity (FC), assessed structural mediators, and examined clinical associations. MethodsWe studied resting-state FC alongside structural and diffusion MRI data in 250 unilateral TLE patients and 259 healthy controls, with measures aggregated across four independent datasets. Data were processed using open-access neuroinformatics workflows and analyzed at a subregional level to maximize anatomical precision. Statistical analysis and mediation models assessed between-group FC changes, structural contributors, and clinical correlations. ResultsCompared to controls, TLE patients presented with reduced thalamo-cortical FC, which was most marked in mesiotemporal, fronto-central, and occipital regions. Thalamo-hippocampal FC was also reduced, with effects seen in all CA subfields. In the thalamus, FC reductions peaked in the ventral posterior nucleus when considering neocortical target regions and in the mediodorsal nucleus when considering hippocampal target regions. While ipsilateral hippocampal volume and diffusion changes mediated thalamo-hippocampal FC, thalamo-cortical FC appeared decoupled from structural alterations. Findings were consistent in left and right TLE patients, in patients with short and long disease duration, and across imaging sites, suggesting that thalamo-cortical FC imbalances are a consistent signature of TLE. Conversely, thalamo-hippocampal FC was elevated in patients with focal-to-bilateral-tonic-clonic seizures and FC alterations were more marked in the subgroup of operated patients that became seizure-free after surgery. ConclusionOur multi-site findings demonstrate marked thalamic circuit fragmentation in TLE. Ipsilateral findings robustly showed subdivision-specific effects, which point to both mesiotemporal co-lateralization as well as broader system-level involvement. Mediation analyses furthermore confirmed a key role of hippocampal pathology in disrupted thalamo-hippocampal connectivity in TLE, while broader thalamo-cortical fragmentation becomes increasingly independent of mesiotemporal compromise. Critically, thalamic FC represents a network substrate for seizure generalization and can serve as a prognostic indicator for surgical outcome. These results underscore the contribution of the thalamus as a hub in macroscale dysfunction in TLE.

neuroscience↗

bioRxiv2026

Sex-related structural alterations across common epilepsies: a worldwide ENIGMA study

Epilepsy is characterized by widespread structural brain alterations extending beyond the epileptic zone, involving both cortical and subcortical regions. Importantly, the clinical manifestation of epilepsy, including seizure types, psychiatric comorbidities, and treatment responses, has been shown to differ between sexes. However, sex differences in structural alterations in epilepsy have been seldomly reported in neuroimaging studies, partly due to limited sample sizes and single-center designs. Here, we systematically investigated sex differences in common epilepsies and their related clinical variables using structural neuroimaging biomarkers in an international multi-center cohort of 1,253 epilepsy patients and 1,077 healthy controls. We studied cortical thickness and subcortical volume in two types of epilepsy: temporal lobe epilepsy (TLE) and genetic generalized epilepsy (GGE). Both male and female patients with TLE showed widespread cortical and subcortical thinning compared with controls. In GGE, when compared separately to controls, male patients showed only subtle structural alterations, whereas female patients exhibited more widespread structural alterations. Sex-stratified analyses revealed some variation in the extent and distribution of cortical thickness and subcortical volume alterations between male and female patients in both epilepsy cohorts. Yet, we did not find significant sex-by-diagnosis interaction effects in TLE and GGE. Similarly, no significant interaction effects were observed between sex and age of onset or disease duration in either patient group. Overall, although we observed some differences in regional cortical thickness and subcortical volume between male and female patients with epilepsy, we did not find significant sex-by-diagnosis interactions. Our findings indicate that sex differences in behavioral and clinical outcomes of epilepsy may involve biological or functional processes that require further investigation.

neuroscience↗

bioRxiv2026

MICAFlow: Fast and Robust MRI Preprocessing Bridging Research Neuroimaging and Clinical Practice

MICAFlow is a fully automated MRI preprocessing pipeline designed to translate advanced neuroimaging workflows from research into routine clinical practice. The pipeline emphasizes speed, robustness, and ease of use, focusing on structural and diffusion MRI. Key innovations include a Label-Augmented Modality-Agnostic Registration (LAMAReg) technique driven by deep learning segmentations for reliable cross-modal alignment, integration of state-of-the-art distortion corrections, and adherence to reproducible standards (Snakemake workflow, BIDSApp specifications). We describe the design of MICAFlow and evaluate its performance across heterogeneous datasets. First, accessibility: MICAFlow processes a multimodal MRI exam in minutes with clinically accessible hardware and without requiring GPU access, making it feasible for same-day clinical use. Second, registration accuracy: LAMAReg achieves cutting-edge multi-modal registration accuracy, yielding accurate alignment of diffusion MRI, FLAIR, and intra-subject T1-weighted images while remaining generally robust to common artifacts. Third, data reliability: Using identifiability, we show MICAFlow maintains consistent performance across diverse datasets, including subjects with pathology, and is closely comparable to contemporary pipelines. In sum, MICAFlows combination of machine learning and efficient workflows produces research-grade data quality with clinical-grade speed. This work demonstrates that advanced MRI preprocessing can be done fast and robustly, helping close the gap between research neuroimaging and broad clinical application of quantitative MRI techniques. The source code for MICAFlow is available here: https://github.com/MICA-MNI/micaflow, and for LAMAReg here: https://github.com/MICA-MNI/LAMAReg.

bioinformatics↗

bioRxiv2026

MutaPhy: A clade-based framework to detect genotype-phenotype associations on phylogenetic trees

Understanding how genetic variation in pathogens influences clinical phenotypes observed in infected hosts is a fundamental challenge in evolutionary genomics and public health. Phenotypic traits such as infection severity are often non-randomly distributed within the pathogens phylogeny, suggesting the existence of evolutionary determinants but also violating the independence assumption underlying classical genome-wide association studies and potentially leading to inflated false positive rates. We present MutaPhy, a phylogeny-based method aimed at detecting correlations between a binary host phenotype and the corresponding pathogen genome by directly utilizing the hierarchical structure of phylogenetic trees. MutaPhy encompasses three different scales: (i) a subtree scale, on which relevant clades over-representing the phenotype of interest are detected using permutation-based tests; (ii) a tree scale, which agglomerates local signals into a global association statistics; and (iii) a site scale, whereby candidate mutational events on branches leading to significant clades are examined using ancestral sequence reconstruction. We evaluate the statistical behavior and detection performance of MutaPhy using simulations under diverse evolutionary scenarios. We also compare this tool to several existing phylogenetic association methods. As illustrative applications, we apply MutaPhy to dengue virus and hepatitis C virus datasets associated to clinical phenotypes in human hosts. Our results highlight the ability of the proposed approach to detect viral lineages associated to over-represented phenotypes while revealing limited evidence for robust mutation-level associations in these particular datasets. Altogether, MutaPhy provides a framework for guiding genotype-phenotype association analyses by leveraging phylogenetic structure, thereby reducing false positive findings and improving the interpretability of association signals.

evolutionary biology↗

bioRxiv2026

Increased Binding of Nifene, a PET Imaging Probe for α4β2* Nicotinic Acetylcholinergic Receptors in Hippocampus-Subiculum of Postmortem Human Parkinsons Disease Brain

Non-motor symptoms in Parkinsons disease (PD) may be influenced by the 4{beta}2* subtype of nicotinic acetylcholine receptors (nAChR) present in the hippocampus and subiculum. To continue efforts in PET diagnostics for PD, autoradiographic [18F]nifene binding to 4{beta}2* nAChR was quantitively assessed in the hippocampus-subiculum (HP-SUB) of PD (n = 27; 14 males, 13 females) and cognitively normal (CN) (n = 32; 16 males, 16 females) cases. Anti-ubiquitin for Lewy body and anti--synuclein immunostaining on adjacent slices were analyzed in QuPath and [18F]nifene binding was quantified in OptiQuant. Subiculum had greater [18F]nifene binding (51% to 85%) compared to HP in all subjects. Significantly higher [18F]nifene binding (>250%) was seen in PD SUB and PD HP compared to CN in both males and females. The grey matter (GM) to white matter (WM) ratio in PD=3.53 while CN=1.33, a >150% increase in PD. Binding of [18F]nifene to GM and WM individually was >250% greater in PD compared to CN. Male CN exhibited an increase while and male PD exhibited a significant decrease in [18F]nifene binding with aging, while females did not exhibit significant differences. In summary, 4{beta}2* nAChR measured by [18F]nifene is significantly upregulated in the PD HP and SUB. This increased [18F]nifene binding may be of diagnostic value using PET imaging.

neuroscience↗

bioRxiv2026

Connectome-wide mega-analysis identifies a reproducible functional network signature of temporal lobe epilepsy

Resting-state functional magnetic resonance imaging (MRI) studies have reported abnormal intrinsic functional connectivity (FC) across distributed circuits in patients with temporal lobe epilepsy (TLE), indicating a system-level impact of the disorder. However, findings remain inconsistent due to limited sample sizes and methodological heterogeneity, leaving the structural determinants and clinical relevance of FC alterations unresolved. To identify a robust and reproducible FC signature, we conducted a data-driven, connectome-wide mega-analysis in a large multicentre cohort of 652 participants (297 TLE, 73 disease controls, and 282 healthy controls) with multimodal 3T MRI and deep clinical phenotyping. We identified convergent FC reconfigurations at both group and individual levels that preferentially involved densely connected hubs, manifesting as hyperconnectivity in frontoparietal association systems and hypoconnectivity in temporal and paralimbic systems. Integrating structural cortical wiring features further revealed that these extensive alterations were constrained by corticocortical proximity, microstructural similarity, and white matter connectivity. Clinically, the FC phenotype tracked symptom burden and disease progression, informed postsurgical seizure outcome, and distinguished TLE from other focal epilepsies. Collectively, these findings systematically delineate a neurobiologically grounded, hub-centric pattern of intrinsic network disruption in TLE, anchored in temporolimbic and adjacent transmodal systems, with potential utility for individualized phenotypic stratification and outcome prognostication.

neuroscience↗

bioRxiv2026

Dual plasmepsin IX and X inhibitors are refractory to development of resistance

Artemisinin-based combination therapies (ACTs) remain the cornerstone of malaria treatment, but emerging resistance threatens their efficacy. The potential for the development of drug resistance against plasmepsin X (PMX)-selective inhibitors and dual plasmepsin IX/X (PMIX/X) inhibitors was investigated in Plasmodium falciparum. A series of PMX-selective (WM4, WM76, WM92) and PMIX/X dual inhibitors (WM382, WM09, WM42) were characterised for potency against parasite growth and enzyme inhibition. In vitro selection experiments showed that all compounds had a high barrier to resistance, although parasites with reduced sensitivity to PMX-selective inhibitors could still be selected. Resistance mechanisms involved pmx gene amplification and point mutations (D245N, S315P, S359P, I363L) that alter inhibitor binding. Recombinant expression and Michaelis-Menten kinetics demonstrated that these mutations impair drug binding whilst preserving PMX catalytic function. Reverse genetics confirmed that introducing these mutations into the pmx gene resulted in decreased potency of the inhibitors. In this study, resistance to the PMIX/X dual inhibitors evaluated here could not be selected, despite prolonged selection pressure. Antimalarial Resistome Barcoding (AReBar) assays confirmed the absence of pre-existing resistance to either inhibitor class. Critically, PMIX/X dual inhibitors maintained efficacy against parasites with decreased sensitivity to PMX-selective compounds. These findings demonstrate that dual PMIX/X inhibitors present a substantially higher barrier to resistance than PMX-selective inhibitors, informing antimalarial drug development strategies and highlighting dual-target inhibition as a promising approach to mitigate resistance risks.

microbiology↗

bioRxiv2026

Hierarchical Signatures of Language in the Human Brain

Language relies on a hierarchy of sensory and cognitive processes, yet how different levels of this hierarchy are supported by distinct neural architectures remains unclear. Here we show that semantic processing, compared with phonological processing, is associated with higher-level brain networks, as characterized by resting-state fMRI connectivity, in vivo measures of cortical myelin, and cortical types derived from a cytoarchitecture-defined reference atlas. These relationships were established using individualized ultra-high field fMRI in both English and French speakers leveraging a multi-session, multi-modal 7T MRI protocol including a language localizer. For comparison, we developed an artificial neural network, in which a representational hierarchy spontaneously emerged where phonological information was captured in earlier layers and semantic information in later layers. By integrating individualized functional mapping, neuroanatomical characterization and artificial intelligence, this study advances understanding of the neural basis of language and provides a framework for linking biological and artificial systems of communication. Significance StatementLanguage is widely described as hierarchical, yet how this functional organization is implemented in the brains biological architecture remains unclear. By combining ultra-high field, individualized neuroimaging with in vivo measures of cortical microstructure and large-scale connectivity, this study establishes a framework for linking distinct levels of linguistic computation to the brains structural and functional organization. Integrating these findings with artificial neural network modeling further reveals shared principles between biological and machine systems. Together, this work advances a biologically grounded account of language, bridges cognitive neuroscience and artificial intelligence, and provides a roadmap for understanding how complex cognition emerges from structured brain architecture.

neuroscience↗

bioRxiv2025

Memory network activity flow failures in temporal and frontal lobe epilepsy

Declarative memory deficits represent considerable challenges to adequate functioning and wellbeing in temporal lobe epilepsy (TLE) and frontal lobe epilepsy (FLE), two of the most common pharmaco-resistant epilepsies. TLE and FLE are impacted differently however, with TLE affecting primarily episodic, and mildly semantic memory, while FLE presenting with overall lesser declarative impairments and a greater involvement of language processes. Although functional magnetic resonance imaging (fMRI) studies are overall compatible with differential disruptions of medial temporal and fronto-limbic networks in both syndromes, direct comparisons of brain activity and connectivity remain scarce. The current study investigated how alterations in intrinsic functional brain organization, as mapped with resting-state connectivity (rsFC), shapes altered brain network activations in both episodic and semantic memory states. To this end, we acquired task- and rs-fMRI data in 28 TLE patients and 17 FLE patients and 87 age- and sex-matched healthy controls (HCs). We used activity flow mapping (AFM), a generative machine learning technique that derives plausible task activation patterns via individualized rsFC as well as normative task activation data. Previous studies in HC as well as patient populations have shown that this technique has been effective in identifying mechanisms contributing to atypical functional organization across different context. Overall, AFM reliably predicted task activations across HC, TLE, and FLE, but prediction accuracy was consistently reduced in both patient groups, indicating impaired propagation of task-relevant signals. These reductions co-occurred with abnormal episodic and semantic task activation patterns, atypical rsFC, and behavioral profiles marked by preserved semantic but impaired episodic memory performance in both patient groups. Importantly, although neither task-evoked abnormalities nor rsFC disruptions alone were associated with clinical variables, lower AFM accuracy in patients robustly tracked poorer episodic and semantic memory performance and longer disease duration. Prediction accuracy was driven more by intrinsic functional than structural network features, suggesting that altered network communication, rather than gross anatomy, constrains AFM in pharmaco-resistant epilepsy. Our work revealed syndrome-specific yet convergent disruptions in paralimbic and heteromodal association systems, linking intrinsic dysconnectivity to a shared episodic vulnerability and semantic resilience across TLE and FLE. By modelling how intrinsic connectivity shapes task-evoked responses, AFM provides a mechanistic account of imbalanced memory-state activations and isolates network-flow pathways as targets for intervention and rehabilitation.

neuroscience↗

bioRxiv2025

Patterns of intersubject correlations parallel organizational gradients during naturalistic viewing

Recent studies have robustly demonstrated that human cortical function can be described through sensory-transmodal gradients of cortical function, while naturalistic movie watching paradigms have been leveraged to index cortical synchronization. We leveraged two independent 7T movie fMRI datasets to assess correlations between intersubject correlation and functional gradients across movies, datasets, and spatial scales. At the whole-brain level, we observed robust relationships between intersubject correlations and a visual-transmodal connectivity gradient which was independent of movie content. Within functional networks, correlations were particularly pronounced for the visual, dorsal attention, and default mode networks. Our results demonstrate that naturalistic paradigms can provide targeted insight into multiscale processing hierarchies. Robust relationships across movies suggest that movie-watching can be viewed as a brain state that is independent of movie-content. Overall, this work suggests an important confluence of within-subject functional organizational axes and inter-subject synchronization when the brain is engaged in the processing of naturalistic stimuli.

neuroscience↗

bioRxiv2025

State dependent shifts in large scale functional topographies

Although functional networks can be consistently identified across cognitive states, they also undergo dynamic reconfigurations across different contexts. For example, naturalistic movie watching paradigms amplify activity in sensory systems compared to resting conditions. However, it remains unclear how these different states affect large-scale brain organization. The current study leveraged high-resolution in vivo 7T fMRI data from the Human Connectome Project (HCP) and the Precision NeuroImaging (PNI) datasets to examine large scale functional connectivity changes between resting and movie-watching conditions. To understand these changes within topographic and geometric principles of brain organization, connectivity shifts were stratified relative to macroscale cortical hierarchy and geodesic distance. Our results revealed that primary sensory areas showed increased local connectivity and reduced long-range interactions during movie watching relative to resting conditions, whereas the default mode network (DMN) exhibited an opposing pattern characterized by reduced within-network long-range connectivity and enhanced connectivity with distant regions outside the DMN. Together, these findings demonstrate that different cognitive states involve geometry-and hierarchy-informed reorganization of large-scale functional networks.

neuroscience↗