Biology subjects

DeKraker, J.

Publications and source records attributed to DeKraker, J..

At least 19 recordsLinked to original sources

bioRxiv2026

HIPPOCAMPAL TAU RELATED SIGNAL INDEXES HYPEREXCITABILITY AND NREM SLEEP MEMORY DYSFUNCTION IN TEMPORAL LOBE EPILEPSY

Background Sleep and memory disturbances are common in temporal lobe epilepsy (TLE), yet their relationship with tau-targeted neuroimaging measures remains unclear. We investigated whether in-vivo temporal 18F-MK6240 tracer retention relates to seizure burden, non-rapid eye movement (NREM) sleep microstructure, and memory performance in TLE. Methods This cross-sectional study was conducted from 2019 to 2024 at the Montreal Neurological Institute-Hospital. Eligible patients had unilateral TLE diagnosed according to International League Against Epilepsy criteria and underwent overnight electroencephalography (EEG) recordings, research-protocol 3T magnetic resonance imaging, and 18F-MK6240 positron emission tomography. Regional 18F-MK6240 standardized uptake value ratios (SUVRs), using the cerebellum as the reference region, were quantified in the ipsilateral hippocampus (defined a priori as the primary region of interest), as well as in peri-hippocampal and lateral temporal regions. Electroclinical and neuropsychological measures, including seizure burden (high vs low), N2 interictal epileptiform discharge frequency (frequent vs non-frequent), and memory performance (impaired vs intact), were classified according to predefined clinical criteria. N2 spindle rate and N3 slow-wave rate were quantified from overnight EEG recordings. Findings Of 70 eligible patients, 25 were included (eight [32%] females; mean age 35.2 years [SD 12.1]). Higher ipsilateral hippocampal 18F-MK6240 uptake was observed in participants with greater focal seizure burden (median [IQR] 0.70 [0.67-0.78] vs 0.64 [0.58-0.65], rank-biserial correlation=-0.58, 95% CI -0.82 to -0.19; p=0.02), was associated with lower N2 spindle rate (r=-0.42, 95% CI -0.70 to -0.03; p=0.04) and higher N3 slow-wave rate (r=0.47; 95% CI 0.09 to 0.73; p=0.02), and was also higher in participants with impaired than intact memory performance (n=21; mean [SD] 0.80 [0.12] vs 0.68 [0.10], Cohen's d=1.15, 95% CI 0.07 to 2.21; p=0.04). Associations outside the hippocampus were generally less consistent and less precise, with the largest non-hippocampal estimate observed in peri-hippocampal regions. Interpretation Higher hippocampal 18F-MK6240 uptake was associated with greater focal seizure burden, altered NREM sleep microstructure, and impaired memory performance in TLE. These findings suggest that hippocampal 18F-MK6240 uptake may represent a candidate marker of circuit vulnerability associated with NREM sleep-memory dysfunction in TLE, warranting validation in larger longitudinal studies.

neuroscience↗

bioRxiv2026

Hippocampal subfields support human novelty detection via distinct signals

Detecting novelty is fundamental to adaptive memory, yet the neural comparisons that allow new events to be distinguished from prior experience are not fully understood. Hippocampal novelty signals are often framed as associative comparator responses that register violations of learned relationships. However, recognition memory models also predict a broader form of comparison: a global, item-based mismatch between an incoming stimulus and aggregate memory traces. Whether such global matching is implemented within human hippocampal circuitry, and whether it contributes to memory decisions, remains unknown. Using ultra-high-field 7T fMRI during dense sampling of a continuous object recognition task (76,800 trials across five sessions), we estimated both univariate novelty responses and multivariate global mismatch signals across hippocampal subfields. CA1 carried the novelty response that most reliably predicted accurate novelty detection, whereas the subiculum expressed a global mismatch signal that predicted detection independently of CA1. This subicular signal also shaped subsequent recognition behaviour, in which low global mismatch was associated with false alarms to novel objects that propagated into later hits. Finally, subicular global mismatch scaled with the experienced similarity of past events, consistent with an item-based comparison against accumulated memory. These findings identify distinct hippocampal mismatch signals for novelty detection and extend the human hippocampal comparator role beyond local associative mismatch to include global, item-based matching.

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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

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.

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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

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

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

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.

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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

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↗

bioRxiv2025

A unified model of cortico-hippocampal interactions through neural field theory

Numerous physical systems evolve on curved manifolds whose geometry constrains their dynamics. The human brain provides a canonical example, with large-scale neural activity evolving on distinct anatomical surfaces such as the cortex and hippocampus. Within each structure, intrinsic feedback loops and manifold geometry shape characteristic neural rhythms. However, core cognitive functions of the brain arise from reciprocal interactions between these spatially distinct neural structures. Here, we introduce a general framework for geometry-constrained coupling between spatially extended dynamical systems evolving on separate manifolds. Using quasi-conformal mapping, we construct neighbourhood-preserving interactions that enable continuous neural activity on distinct geometries to interact while preserving local neighbourhood structure. Applying this framework to neural activity evolving on cortical and hippocampal surfaces, we show that increasing inter-manifold coupling reorganises system dynamics, producing frequency shifts, mode interactions, and coupling-driven instabilities consistent with critical transitions. These effects reproduce key features of large-scale brain activity, including topographically organised synchronisation between cortex and hippocampus during healthy cognition and critical transitions to seizure-like spectral dynamics. These results identify inter-manifold coupling as a core influence on dynamics in the human brain and highlight the broader role of geometry-constrained coupling on emergent dynamics in complex spatially extended systems.

neuroscience↗

bioRxiv2025

A unified imaging-histology framework for superficial white matter architecture studies in the human brain

The superficial white matter (SWM), immediately beneath the cortical mantle, is thought to play a major role in cortico-cortical connectivity as well as large-scale brain function. Yet, this compartment remains rarely studied due to its complex organization. Our objectives were to develop and disseminate a robust computational framework to study SWM organization based on 3D histology and high-field 7T MRI. Using data from the BigBrain and Ahead 3D histology initiatives, we first interrogated variations in cell staining intensities across different cortical regions and different SWM depths. These findings were then translated to in-vivo 7T quantitative myelin-sensitive MRI, including T1 relaxometry (T1 map) and magnetization transfer saturation (MTsat). As indicated by the statistical moments of the SWM intensity profiles, the first 2 mm below the cortico-subcortical boundary were characterized by high structural complexity. We quantified SWM microstructural variation using a non-linear dimensionality reduction method and examined the relationship of the resulting microstructural gradients with indices of cortical geometry, as well as structural and functional connectivity. Our results showed correlations between SWM microstructural gradients, as well as curvature and cortico-cortical functional connectivity. Our study provides novel insights into the organization of SWM in the human brain and underscores the potential of SWM mapping to advance fundamental and applied neuroscience research. HighlightsO_LIDeveloped an anatomy-based open science framework to study SWM organization based on 3D post-mortem histology and/or in-vivo high-field MRI C_LIO_LIThe first 2 mm into the white matter are characterized by high structural complexity C_LIO_LIInter-regional trends in SWM microstructural variation, which related to cortical geometry, as well as cortico-cortical connectivity C_LI

neuroscience↗

bioRxiv2024

MULTIMODAL GRADIENTS UNIFY LOCAL AND GLOBAL CORTICAL ORGANIZATION

AO_SCPLOWBSTRACTC_SCPLOWSpecialization of brain areas and subregions, as well as their integration into large-scale networks are key principles in neuroscience. Consolidating both local and global cortical organization, however, remains challenging. Our study developed a new approach to map global cortex-wise similarities of microstructure, structural connectivity, and functional interactions, and integrate these patterns with maps of cortical arealization. Our analysis combined repeated high-field in-vivo 7 tesla (7T) Magnetic Resonance Imaging (MRI) data collected in 10 healthy adults with a recently introduced probabilistic post-mortem atlas of cortical cytoarchitecture. We obtained multimodal eigenvectors describing cortex-wide gradients at the level of microstructural covariance, structural connectivity, and intrinsic functional interactions, and then assessed inter- and intra-area differences in cortex-wide embedding based on these multimodal eigenvectors. Inter-area similarities followed a canonical sensory-fugal gradient, with primary sensorimotor cortex being the most distinctive from all other areas, while paralimbic regions were least distinctive. This pattern largely corresponded to functional connectivity variations across different tasks collected in the same participants, suggesting that the degree of global cortical integration mirrors the functional diversity of brain areas across contexts. When studying heterogeneity within areas, we did not observe a similar relationship, despite overall higher heterogeneity in association cortices relative to paralimbic and idiotypic cortices. The results were replicated in a different dataset. Our findings highlight a close coupling between cortical arealization and global cortical motifs in shaping specialized versus integrative human brain function. SO_SCPLOWIGNIFICANCEC_SCPLOWOur work situates cytoarchitecture-derived cortical areas within multimodal gradients of cortical microstructure, connectivity, and function derived from high-definition multimodal neuroimaging. We demonstrated that primary sensory and motor areas show most distinctive gradient profiles while paralimbic areas were least distinctive, overall recapitulating a sensory-fugal axis. This axis was shown to relate to the diversity of cortical areas across different functional contexts, and findings could be replicated across an independent dataset. Overall, our work shows how frameworks of cortical arealization and macroscale gradients converge in shaping functional specialization versus integration in the human brain.

neuroscience↗

bioRxiv2024

HippoMaps: Multiscale cartography of the human hippocampal formation

The hippocampus has a unique microarchitecture, is situated at the nexus of multiple macroscale functional networks, contributes to numerous cognitive as well as affective processes, and is highly susceptible to brain pathology across common disorders. These features make the hippocampus a model to understand how brain structure covaries with function, in both health and disease. Here, we introduce HippoMaps, an open access toolbox and online data warehouse for the mapping and contextualization of subregional hippocampal data in the human brain (http://hippomaps.readthedocs.io). HippoMaps capitalizes on a unified hippocampal unfolding approach as well as shape intrinsic registration capabilities to allow for cross-subject and cross-modal data aggregation. We initialize this repository with an unprecedented combination of hippocampal data spanning 3D ex-vivo histology, ex-vivo 9.4 Tesla MRI, as well as in-vivo structural MRI and resting-state functional MRI (rsfMRI) obtained at 3 and 7 Tesla, together with intracranial encephalography (iEEG) recordings in epilepsy patients. HippoMaps also contains validated tools for spatial map association analysis in the hippocampus that correct for autocorrelation. All code and data are compliant with community standards, and comprehensive online tutorials facilitate broad adoption. Applications of this work span methodologies and modalities, spatial scales, as well as clinical and basic research contexts, and we encourage community feedback and contributions in the spirit of open and iterative scientific resource development.

neuroscience↗

bioRxiv2023

Hippocampal connectivity patterns echo macroscale cortical evolution in the primate brain

The hippocampus is involved in numerous cognitive functions, some of which have uniquely human aspects, such as autobiographical memory. Hippocampal anatomy, however, is typically considered conserved across primates and its evolutionary diversification is rarely studied. Comparing hippocampal structure and function is, therefore, critical for understanding human brain architecture. Here, we developed a novel comparative framework to study the hippocampus across species characterising its geometry, microstructure, and functional network embedding. In humans and macaques, we generated a new comparative space that represents the hippocampus as an unfolded surface, which respects its sheet-like anatomy. We mapped histological and MRI-derived markers of microstructure to the hippocampal surface and integrated it with low-dimensional embedding of resting-state MRI connectivity data. Our results demonstrate that the micro- and macro-structural organisation of the hippocampus are overall conserved in both species, showing consistent anterior-posterior and subfield-to-subfield differentiation. Furthermore, while hippocampal functional organisation also follows anterior-posterior trends in both species, hippocampal functional connectivity markedly reflected evolutionary reconfiguration of transmodal networks, in particular the default-mode network. Specifically, the inferior parietal lobe in the macaque mirrors an incomplete integration of the default mode network in non-human primates. By combining fine-grained anatomical investigation with large-scale functional imaging, we showed that microstructurally preserved regions like the hippocampus may still undergo functional reconfiguration, due to their embedding in higher-order association networks. SummaryWhile the hippocampus is key for uniquely human cognitive abilities, it is also a phylogenetically old cortex and paradoxically considered evolutionarily preserved. Here, we introduce a comparative framework to quantify preservation and reconfiguration of hippocampal organisation in primate evolution, by analysing the hippocampus as an unfolded cortical surface that is geometrically matched across species. Our findings revealed an overall conservation of hippocampal macro- and micro-structure, showing anterior-posterior and, perpendicularly, subfield-related organisational axes in both humans and macaques. However, while functional organisation in both species also followed an anterior-posterior axis, the latter showed a marked evolutionary reconfiguration, which mirrors a rudimentary integration of the default-mode-network in non-human primates. Our findings suggest that microstructurally preserved regions like the hippocampus may still undergo functional reconfiguration in primate evolution, due to their embedding in heteromodal association networks.

neuroscience↗

bioRxiv2023

Cerebral perfusion alterations in temporal lobe epilepsy: Structural underpinnings and network disruptions

AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSOO_SCPLOWBJECTIVEC_SCPLOWC_ST_ABSNeuroimaging has been the prevailing method to study brain networks in temporal lobe epilepsy (TLE), showing widespread 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. MO_SCPLOWETHODSC_SCPLOWWe studied 24 individuals with pharmaco-resistant TLE and 38 healthy adults using multimodal 3T magnetic resonance imaging. We compared regional CBF changes in patients relative to controls and related our perfusion findings to morphological and microstructural metrics. We further probed inter-regional vascular networks in TLE, using graph theoretical CBF covariance analysis. Finally, we assessed the effects of disease duration to study progressive changes. RO_SCPLOWESULTSC_SCPLOWCompared to controls, individuals with TLE showed widespread CBF reductions, predominantly in fronto-temporal regions, with 83% of patients showing more marked decreases ipsilateral than contralateral to the seizure focus. Parallel structural profiling and network-based models showed that cerebral hypoperfusion may be partly constrained by grey and white matter changes and topologically segregated from whole-brain perfusion networks. Negative effects of progressive disease duration further targeted regional CBF profiles in patients. Findings were confirmed in a subgroup of patients who remained seizure-free after surgery. IO_SCPLOWNTERPRETATIONC_SCPLOWOur multimodal findings provide insights into vascular contributions to TLE pathophysiology and highlight their clinical potential in seizure lateralization.

neuroscience↗

bioRxiv2023

Novel insights into hippocampal perfusion using high-resolution, multi-modal 7T MRI

We present a comprehensive study on the non-invasive measurement of hippocampal perfusion. Using high-resolution 7 Tesla arterial spin labelling data, we generated robust perfusion maps and observed significant variations in perfusion among hippocampal subfields, with CA1 exhibiting the lowest perfusion levels. Notably, these perfusion differences were robust and detectable even within five minutes and just fifty perfusion-weighted images per subject. To understand the underlying factors, we examined the influence of image quality metrics, various tissue microstructure and morphometry properties, macrovasculature and cytoarchitecture. We observed higher perfusion in regions located closer to arteries, demonstrating the influence of vascular proximity on hippocampal perfusion. Moreover, ex vivo cytoarchitectonic features based on neuronal density differences appeared to correlate stronger with hippocampal perfusion than morphometric measures like gray matter thickness. These findings emphasize the interplay between microvasculature, macrovasculature, and metabolic demand in shaping hippocampal perfusion. Our study expands the current understanding of hippocampal physiology and its relevance to neurological disorders. By providing in vivo evidence of perfusion differences between hippocampal subfields, our findings have implications for diagnosis and potential therapeutic interventions. In conclusion, our study provides a valuable resource for extensively characterising hippocampal perfusion.

neuroscience↗

bioRxiv2023

Atypical connectome topography and signal flow in temporal lobe epilepsy

Temporal lobe epilepsy (TLE) is one of the most common pharmaco-resistant epilepsies in adults. While hippocampal pathology is the hallmark of this condition, emerging evidence indicates that brain alterations extend beyond the mesiotemporal epicenter and affect macroscale brain function and cognition. We studied macroscale functional reorganization in TLE, explored structural substrates, and examined cognitive associations. We investigated a multisite cohort of 95 patients with pharmaco-resistant TLE and 95 healthy controls using state-of-the-art multimodal 3T magnetic resonance imaging (MRI). We quantified macroscale functional topographic organization using connectome dimensionality reduction techniques and estimated directional functional flow using generative models of effective connectivity. We observed atypical functional topographies in patients with TLE relative to controls, manifesting as reduced functional differentiation between sensory/motor networks and transmodal systems such as the default mode network, with peak alterations in bilateral temporal and ventromedial prefrontal cortices. TLE-related topographic changes were consistent in all three included sites and reflected reductions in hierarchical flow patterns between cortical systems. Integration of parallel multimodal MRI data indicated that these findings were independent of TLE-related cortical grey matter atrophy, but mediated by microstructural alterations in the superficial white matter immediately beneath the cortex. The magnitude of functional perturbations was robustly associated with behavioral markers of memory function. Overall, this work provides converging evidence for macroscale functional imbalances, contributing microstructural alterations, and their associations with cognitive dysfunction in TLE.

neuroscience↗