Biology subjects

Paquola, C.

Publications and source records attributed to Paquola, C..

At least 19 recordsLinked to original sources

bioRxiv2026

Linking human brain functional connectivity to underlying neurotransmission

The human brain is organized into interacting functional systems. Their underlying neurobiological mechanisms remain difficult to study in vivo. Here, we adopt a topological framework to quantify the association between neurobiology and brain functional connectivity derived from both resting-state fMRI and MEG. Across six healthy adult cohorts (n = 19-112), regional variation in fMRI connectivity robustly aligns with the distribution of neurotransmitter receptors and transporters. These patterns are present in every single subject, replicate across all cohorts, and are mirrored in MEG. Most prominently, noradrenergic modulation of connectivity in a sensorimotor-insular network is consistently detected across individuals and linked to autonomic arousal. In pharmacological and clinical samples, associations are sensitive to neurotransmitter system manipulation and are altered in early psychosis, aligning with clinical symptomatology. These findings provide biological insight into typical and atypical functional organization of the human brain using a framework linking underlying neurobiology to the functional connectome (NEOFC).

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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

Intracortical microstructure profiling: a versatile method for indexing cortical lamination

Intracortical microstructure profiling represents a powerful, scalable approach for investigating the laminar organisation of the human cortex on both in vivo and post-mortem datasets. Building upon a long tradition of histological analysis, this method leverages surface-based intracortical sampling to generate profiles of tissue properties across cortical depths. The present work outlines a standardised workflow for intracortical microstructural profiling, newly packaged as an open-source toolbox "CortPro" (https://github.com/caseypaquola/cortpro). Here, we explore the utility of central moments as descriptors of profile shape. Using these measures, we quantify (i) the extent to which in vivo MRI can capture laminar differentiation, (ii) the test-retest reliability of profiles, and (iii) their replicability across sites and studies. Our results demonstrate that intracortical profiles are remarkably robust and effectively mitigate bias-field related limitations of non-quantitative MRI. As applications of microstructure-sensitive imaging expand across development, aging, and disease, microstructure profiling provides a principled means of linking microstructural neuroanatomy with systems-level brain organisation.

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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.

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bioRxiv2025

Disentangling the influences of pre- and postnatal periods on human cortical microstructure

During late gestation and early postnatal development a combination of intrinsic and extrinsic factors drive the maturation of the human cortex. This process is regionally heterogeneous, with cortical areas developing at different paces and trajectories. Leveraging submillimetre T1-weighted/T2w-weighted (T1w/T2w) magnetic resonance imaging (MRI) from pre- and full-term neonates (n = 599, 0-7 weeks), we sampled intracortical microstructure profiles across the cortex and characterised the profiles shapes according to their central moments. We found that gestational age at birth dominated the effects on early cortical development, with significant, global increases in microstructural density, increasing intracortical homogeneity and a bimodal change of the microstructural balance between superficial and deeper cortical layers. On the other hand, weeks since birth (i.e. postnatal age) exhibited different effects on microstructure, with density increasing at a slower pace, increasing intracortical heterogeneity, and intracortical balance only shifting towards deeper layers in posterior temporal, occipital, medial parietal areas and some prefrontal areas. These effects align with low spatial-frequency geometric eigenmodes of the human cortex, specifically the anterior-posterior, superior-inferior and central-polar axes. Our findings demonstrate that separating prenatal from postnatal influences, and analysing intracortical profiles rather than macroscale features, provides finer-grained insights into how human cortical microstructure changes during perinatal development and lays the groundwork for investigating the biological underpinnings that govern normative cortical maturation.

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bioRxiv2025

In vivo cartography of state-dependent signal flow hierarchy in the human cerebral cortex

Understanding the principle of information flow across distributed brain networks is of paramount importance in neuroscience. Here, we introduce a novel neuroimaging framework, leveraging integrated effective connectivity (iEC) and unconstrained signal flow mapping for data-driven discovery of the human cerebral functional hierarchy. Simulation and empirical validation demonstrated the high fidelity of iEC in recovering connectome directionality and its potential relationship with histologically defined feedforward and feedback pathways. Notably, the iEC-derived hierarchy revealed a monotonically increasing level along the axis where the sensorimotor, association, and paralimbic areas are sequentially ordered - a pattern supported by the Structural Model of laminar connectivity. This hierarchy was further demonstrated to flexibly reorganize across brain states: flattening during an externally oriented condition, evidenced by a reduced slope in the hierarchy, and steepening during an internally focused condition, reflecting heightened engagement of interoceptive regions. Our study highlights the unique role of macroscale directed functional connectivity in uncovering a biologically interpretable state-dependent signal flow hierarchy.

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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

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bioRxiv2025

Associations between epilepsy-related polygenic risk and brain morphology in childhood

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

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bioRxiv2025

Human cortical dynamics reflect graded contributions of local geometry and network topography

The brain is a physically embedded and heavily interconnected system that expresses neural rhythms across multiple time scales. While these dynamics result from the complex interplay of local and inter-regional factors, the relative contribution of such mechanisms across the cortex remains unclear. Our study explores geometric, microstructural, and connectome-level constraints on cortex-wide neural activity. We leverage intracranial electroencephalography recordings to derive a coordinate system of human cortical dynamics. Using multimodal neuroimaging, we could then demonstrate that these patterns are largely explainable by geometric properties indexed by inter-regional distance. However, dynamics in transmodal association regions are additionally explainable by incorporation of inter-regional microstructural similarity and connectivity information. Our findings are generally consistent when cross-referencing electroencephalography and imaging data from large-scale atlases and when using data obtained in the same individuals, suggesting subject-specificity and population-level generalizability. Together, our results suggest that the relative contribution of local and macroscale constraints on cortical dynamics varies systematically across the cortical sheet, specifically highlighting the role of transmodal networks in inter-regional cortical coordination.

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bioRxiv2024

Procrustes Alignment in Individual-level Analyses of Functional Gradients

Functional connectivity (FC) gradients provide valuable insights into individual differences in brain organization, yet aligning these gradients across individuals poses challenges. Procrustes alignment is often employed to standardize gradients across multiple subjects, but the choice of the number of gradients used in alignment introduces complexities that may impact individual-level analyses. In this study, we systematically investigate the impact of varying gradient counts in Procrustes alignment on the principal FC gradient, using data from four resting state fMRI datasets, including the Human Connectome Project (HCP-YA), Amsterdam Open MRI Collection (AOMIC) PIOP1 and PIOP2, and Cambridge Centre for Ageing and Neuroscience (Cam-CAN). We find that increasing the number of gradients used in alignment enhances identification accuracy but can reduce differential identifiability, as additional gradients risk introducing nuisance signals such as motion back into the principal gradient. To further probe these effects, machine learning to predict fluid intelligence and age, and a motion prediction analysis, revealing that higher alignment gradient counts may leak information from lower gradients into the principal gradient for individual-level analyses. These findings highlight the trade-off between alignment precision and the potential reintroduction of noise. Key PointsO_LIGradient count used in Procrustes alignment impacts identification accuracy and differential identifiability obtained using the principal gradient C_LIO_LIThe magnitude of the Procrustes transformation correlates with motion measures, and this correlation increases with higher gradient count used in alignment. C_LIO_LIGradient count used in Procrustes alignment impacts prediction of fluid intelligence and age C_LI

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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.

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bioRxiv2024

Multimodal Precision Neuroimaging of the Individual Human Brain at Ultra-high fields

Multimodal neuroimaging, in particular magnetic resonance imaging (MRI), allows for non-invasive examination of human brain structure and function across multiple scales. Precision neuroimaging builds upon this foundation, enabling the mapping of brain structure, function, and connectivity patterns with high fidelity in single individuals. Highfield MRI, operating at magnetic field strengths of 7 Tesla (T) or higher, increases signal-to-noise ratio and opens up possibilities for gains spatial resolution. Here, we share a multimodal Precision Neuroimaging and Connectomics (PNI) 7T MRI dataset. Ten healthy individuals underwent a comprehensive MRI protocol, including T1 relaxometry, magnetization transfer imaging, T2*-weighted imaging, diffusion MRI, and multi-state functional MRI paradigms, aggregated across three imaging sessions. Alongside anonymized raw MRI data, we release cortex-wide connectomes from different modalities across multiple parcellation scales, and supply "gradients" that compactly characterize spatial patterning of cortical organization. Our precision MRI dataset will advance our understanding of structure-function relationships in the individual human brain and is publicly available via the Open Science Framework.

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bioRxiv2024

Microstructural asymmetry in the human cortex

While macroscale brain asymmetry and its relevance for human cognitive function have been consistently shown, the underlying neurobiological signatures remain an open question. Here, we probe layer-specific microstructural asymmetry of the human cortex using intensity profiles from post-mortem cytoarchitecture. An anterior-posterior cortical pattern of left-right asymmetry was found, varying across cortical layers. A similar anterior-posterior pattern was observed using in vivo microstructural imaging, with in vivo asymmetry showing the strongest similarity with layer III. Microstructural asymmetry varied as a function of age and sex and was found to be heritable. Moreover, asymmetry in microstructure corresponded to asymmetry of intrinsic function, in particular in sensory areas. Last, probing the behavioral relevance, we found differential association of language and markers of mental health with asymmetry, illustrating a functional divergence between inferior-superior and anterior-posterior microstructural axes anchored in microstructural development. Our study highlights the layer-based patterning of microstructural asymmetry of the human cortex and its functional relevance.

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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.

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bioRxiv2023

GAN-MAT: Generative Adversarial Network-based Microstructural Profile Covariance Analysis Toolbox

AO_SCPLOWBSTRACTC_SCPLOWMultimodal magnetic resonance imaging (MRI) provides complementary information for investigating brain structure and function; for example, an in vivo microstructure-sensitive proxy can be estimated using the ratio between T1- and T2-weighted structural MRI. However, acquiring multiple imaging modalities is challenging in patients with inattentive disorders. In this study, we proposed a comprehensive framework to provide multiple imaging features related to the brain microstructure using only T1-weighted MRI. Our toolbox consists of (i) synthesizing T2-weighted MRI from T1-weighted MRI using a conditional generative adversarial network; (ii) estimating microstructural features, including intracortical covariance and moment features of cortical layer-wise microstructural profiles; and (iii) generating a microstructural gradient, which is a low-dimensional representation of the intracortical microstructure profile. We trained and tested our toolbox using T1- and T2-weighted MRI scans of 1,104 healthy young adults obtained from the Human Connectome Project database. We found that the synthesized T2-weighted MRI was very similar to the actual image and that the synthesized data successfully reproduced the microstructural features. The toolbox was validated using an independent dataset containing healthy controls and patients with episodic migraine as well as the atypical developmental condition of autism spectrum disorder. Our toolbox may provide a new paradigm for analyzing multimodal structural MRI in the neuroscience community, and is openly accessible at https://github.com/CAMIN-neuro/GAN-MAT.

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bioRxiv2023

The spatial arrangement of laminar thickness profiles in the human cortex scaffolds processing hierarchy

The human neocortex consists of tangentially organized layers with unique cytoarchitectural properties. These layers show spatial variations in thickness and cytoarchitecture across the neocortex, which is thought to support brain function through enabling targeted corticocortical connections. Here, leveraging maps of the six cortical layers in 3D human brain histology, we aimed to quantitatively characterize the systematic covariation of laminar structure in the cortex and its functional consequences. After correcting for the effect of cortical curvature, we identified a spatial pattern of changes in laminar thickness covariance from lateral frontal to posterior occipital regions, which differentiated the dominance of infra- versus supragranular layer thickness. Corresponding to the laminar regularities of cortical connections along cortical hierarchy, the infragranular-dominant pattern of laminar thickness was associated with higher hierarchical positions of regions, mapped based on resting-state effective connectivity in humans and tract-tracing of structural connections in macaques. Moreover, we show that regions with comparable laminar thickness patterns correspond to inter-regional structural covariance, maturational coupling, and transcriptomic patterning, indicating developmental relevance. In sum, here we characterize the association between organization of laminar thickness and processing hierarchy, anchored in ontogeny. As such, we illustrate how laminar organization may provide a foundational principle ultimately supporting human cognitive functioning.

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bioRxiv2022

Cortical microstructural gradients capture memory network reorganization in temporal lobe epilepsy

Temporal lobe epilepsy (TLE), one of the most common pharmaco-resistant epilepsies, is associated with pathology of paralimbic brain regions, particularly in the mesiotemporal lobe. Cognitive dysfunction in TLE is frequent, and particularly affects episodic memory. Crucially, these difficulties challenge the quality of life of patients, sometimes more than seizures, underscoring the need to assess neural processes of cognitive dysfunction in TLE to improve patient management. Our work harnessed a novel conceptual and analytical approach to assess spatial gradients of microstructural differentiation between cortical areas based on high-resolution MRI analysis. Gradients track region-to-region variations in intracortical lamination and myeloarchitecture, serving as a system-level measure of structural and functional reorganization. Comparing cortex-wide microstructural gradients between 21 patients and 35 healthy controls, we observed a contracted gradient in TLE driven by reduced microstructural differentiation between paralimbic cortices and the remaining cortex with marked abnormalities in ipsilateral temporopolar and dorsolateral prefrontal regions. Findings were replicated in an independent cohort. Using an independent post mortem dataset, we observed that in vivo findings reflected topographical variations in cortical lamination patterns, confirming that TLE-related changes in the microstructural gradient reflected increased proximity of regions with more dissimilar laminar structure. Disease-related transcriptomics could furthermore show specificity of our findings to TLE over other common epilepsy syndromes. Finally, microstructural dedifferentiation was associated with cognitive network reorganization seen during an episodic memory functional MRI paradigm, and correlated with inter-individual differences in task accuracy. Collectively, our findings showing a pattern of reduced microarchitectural differentiation between paralimbic regions and the remaining cortex provide a parsimonious explanation for functional network reorganization and cognitive dysfunction characteristic of TLE.

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bioRxiv2022

Micapipe: a pipeline for multimodal neuroimaging and connectome analysis

AO_SCPLOWBSTRACTC_SCPLOWMultimodal magnetic resonance imaging (MRI) has accelerated human neuroscience by fostering the analysis of brain structure, function, and connectivity across multiple scales and in living brains. The richness and complexity of multimodal neuroimaging, however, demands processing methods to integrate information across modalities and different spatial scales. Here, we present micapipe, an open processing pipeline for BIDS-conform multimodal MRI datasets. micapipe can generate i) structural connectomes derived from diffusion tractography, ii) functional connectomes derived from resting-state signal correlations, iii) geodesic distance matrices that quantify cortico-cortical proximity, and iv) microstructural profile covariance matrices that assess inter-regional similarity in cortical myelin proxies. These matrices are routinely generated across established 18 cortical parcellations (100-1000 parcels), in addition to subcortical and cerebellar parcellations. Results are represented on three different surface spaces (native, conte69, fsaverage5), and outputs are BIDS-conform. Processed outputs can be quality controlled at the individual and group level. micapipe was tested on several datasets and is available at https://github.com/MICA-MNI/micapipe, documented at https://micapipe.readthedocs.io/, and containerized as a BIDS App http://bids-apps.neuroimaging.io/apps/. We hope that micapipe will foster robust and integrative studies of human brain microstructure, morphology, and connectivity.

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