Biology subjects

Jobard, G.

Publications and source records attributed to Jobard, G..

9 recordsLinked to original sources

bioRxiv2026

Cognition, but not affect, rests upon a segregated intrinsic network architecture

The brains intrinsic organization into resting-state networks has long been suggested to be fundamental for the offline support of mental processes. Extensive task-based evidence support the relevance of the crosstalk between network segregation, supporting systems specialization, and network integration, allowing to flexibly implement complex behavior. However, only scarce evidence focusing on few behavioral measures directly link changes in these network properties at rest with interindividual differences in behavior. In this work, using a comprehensive set of behavioral measures together with resting-state functional magnetic resonance imaging from the human connectome project, we assessed whether connectivity patterns predictive of behavior reflected segregation or integration based on GINNA, a 33 resting-state-networks atlas with cognitive characterization. We found that connectivity relevant for behavior organizes into 3 main latent dimensions, summarizing Cognition, Positive Affect and Negative Affect. Crucially, we found that connectivity predictive of Cognition, but not Affect, was associated with global network segregation and reduced network integration. We further reveal differential resting-state-networks involvements, with Cognition associated with the segregation of higher-level resting-state-networks, and the integration of lower-level, visual networks. All in all, the present results suggest that cognition may rest upon a segregated, modular intrinsic brain architecture. Author summaryHow psychological processes are maintained when the brain is not engaged in an explicit task remains unclear. Resting-state networks offer a candidate intrinsic architecture, but whether interindividual differences in diverse behavioral domains relate to this architecture in similar ways is unknown. We combined Human Connectome Project resting-state fMRI with 58 behavioral measures to identify functional connectivity patterns predictive of behavior and examine how they relate to network segregation and integration. These patterns organized into three latent dimensions summarizing Cognition, Positive Affect, and Negative Affect. Cognition-related patterns aligned with a segregated intrinsic architecture, showing stronger within-network and weaker between-network connectivity, particularly among higher-order resting-state networks, with complementary integration of visual networks. Affective patterns showed less consistent network signatures, suggesting a more distributed or context-dependent intrinsic organization.

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bioRxiv2025

Brain structure-function coupling - relationship with language lateralisation

Language is one of the most extensively studied lateralised cognitive functions in the human brain, predominantly relying on the left hemisphere in most individuals. However, the mechanisms by which a stable white matter architecture underpins individual language functions remain unclear. Previous studies have employed structural connectivity (SC) and functional connectivity (FC) coupling for individual fingerprinting and task decoding, suggesting that variability in brain entropy may serve as a distinguishing characteristic for language lateralisation. We examined a large cohort of healthy adults (n = 285) to investigate SC-FC coupling and identify markers distinguishing different language laterality groups. Functional connectivity was measured using resting-state fMRI (rsfMRI) time-series data, while structural connectivity was determined via probabilistic fibre tractography. SC-FC coupling was investigated using the SENSAAS language atlas and defined as the Pearson correlation between non-zero elements of regional structural and functional connectivity profiles. Group differences were assessed using the PALM toolbox in FSL. Our findings revealed that increased SC-FC coupling in the left precentral sulcus was associated with typical language lateralisation, while increased coupling in the right middle temporal gyrus and left anterior insula was observed in individuals with atypical language lateralisation (pFDR < 0.05). Non-lateralised individuals exhibited increased coupling in the left anterior insula compared to lateralised (pFDR<0.05). SC-FC coupling offers a promising framework to uncover functional and anatomical differences among individuals with varying language lateralisation. This regional specificity indicates that typical, atypical, and non-lateralised profiles rely on different structural-functional alignments, likely reflecting the recruitment of alternative pathways for language processing.

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bioRxiv2025

Language laterality and cognitive skills: does anatomy matter?

Brain anatomy, particularly white matter microstructure, is thought to play a critical role in the relationships between cognitive function and language lateralisation. This study investigates whether white matter microstructural parameters of the arcuate fasciculus and corpus callosum is associated with cognitive performance across distinct language lateralisation groups. Neuroimaging and cognitive data from 279 healthy adults were sourced from the BIL&GIN database. Participants completed a sentence production fMRI task, diffusion MRI, and cognitive tasks assessing verbal, visuospatial, and arithmetic skills. Significant positive associations were observed in strongly atypical individuals between fractional anisotropy in the splenium and working memory (R2 = 0.96, pFDR = 0.042) and between FA in the genu and visuospatial attention (R2 = 0.92, pFDR = 0.042). ANCOVA revealed that cross-dominant individuals had significantly lower visuospatial attention scores compared to consistently lateralised individuals (pFDR = 0.02). These findings challenge the notion that atypical lateralisation is inherently maladaptive and suggest that white matter pathways may serve as an alternative mechanism for supporting cognitive function in individuals with rightward language dominance. Furthermore, the results highlight the cognitive disadvantages of crossed dominance, implicating disrupted interhemispheric communication as a potential underlying mechanism.

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bioRxiv2025

Distinct Structural Connectivity Patterns Associated with Variations in Language Lateralisation

Hemispheric asymmetries in white matter tracts are proposed key determinants of language lateralisation, yet evidence in healthy individuals remains inconsistent. This suggests that simple tractography techniques might not be sensitive enough to identify language dominance. Significant insights into the functional organization of the human brain may be achieved by considering networks and brain connectivity, providing more information about discrepancies in people with different hemispheric language dominance. In this study, we examined 285 healthy participants compare their structural connectomes at the whole-brain level and determine the networks responsible for the three different functional language lateralisation groups (typical, atypical and strongly atypical). Probabilistic tractography generated whole-brain tractograms, and white matter fibres were filtered according to anatomical Boolean guidelines. Connectivity matrices with nodes corresponding to supramodal sentence areas in the language atlas and edges weighted by fractional anisotropy (FA) were generated to compare the groups using graph theory and network-based statistic (NBS) approaches. We demonstrated that both atypical (bilateral) and strongly atypical (right-lateralised) lateralisation are characterised by heightened interhemispheric temporal connectivity. Post-hoc analyses showed that strongly atypical individuals exhibited increased temporo-frontal connectivity, while atypical individuals had enhanced temporal and frontal connectivity but lacked temporo-frontal connections. These connectivity patterns diverge from traditional models of hemispheric dominance, suggesting a reliance on integrated bilateral networks in atypically lateralised individuals. This reflects distinct neural mechanisms underlying atypical language organisation, departing from developmental trajectory of typical lateralisation and offering insights into cognitive flexibility and clinical applications.

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bioRxiv2024

Benchmarking Stroke Outcome Prediction through Comprehensive Data Analysis - NeuralCup 2023

Stroke remains a leading cause of mortality and long-term disability worldwide, with variable recovery trajectories posing substantial challenges in anticipating post-event care and rehabilitation planning. To address these challenges, we established the NeuralCup consortium to benchmark predictive models of stroke outcome through a collaborative, data-driven approach. This study presents findings from 15 international teams who used a comprehensive dataset including clinical and imaging data, to identify and compare predictors of motor, cognitive, and emotional outcomes one year post-stroke. Our analyses integrated traditional statistical approaches and novel machine learning algorithms to uncover optimal recipes for predicting each domain. The differences in these optimal recipes reflect distinct brain mechanisms in response to different tasks. Key predictors across all domains included infarct characteristics, T1-weighted MRI sequences, and demographic factors. Additionally, integrating FLAIR imaging and white matter tract analysis significantly improved the prediction of cognitive and motor outcomes, respectively. These findings support a multifaceted approach to stroke outcome prediction, underscoring the potential of collaborative data science to develop personalized care strategies that enhance recovery and quality of life for stroke survivors. To encourage further model development and validation, we provide access to the training dataset at http://neuralcup.bcblab.com

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bioRxiv2018

Neuroimaging supports the representational nature of the earliest human engravings

The earliest human graphic productions dating to the Lower and Middle Palaeolithic are associated with anatomically modern and archaic hominins. These productions, which consist of abstract patterns engraved on a variety of media, may have been used as symbols, and their emergence is thought to be associated with the evolution of the properties of the visual cortex. To test this hypothesis, we used functional magnetic resonance imaging to compare brain activations triggered by the perception of engraved patterns dating between 540,000 and 30,000 years before the present with those elicited by the perception of scenes, objects, symbol-like characters, and written words. The perception of the engravings bilaterally activated regions in the ventral route in a pattern similar to that produced by the perception of objects, suggesting that these graphic productions are processed as organized visual representations in the brain. Moreover, the perception of the engravings led to a leftward activation of the visual word form area. These results support the hypothesis that in contrast to random doodles, the earliest abstract graphic productions had a representational purpose for modern and archaic hominins.

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bioRxiv2018

Brain areas commonly activated and asymmetrical in production, listening and reading tasks at the word level: an fMRI study of 144 right-handers.

Even if speech perception and production have been revealed to share a common recruitment of both discrete auditory and motor areas, this overlap being also common to reading and listening, no study has investigated the involvement of larger networks in the three tasks yet. So, we first identified the multimodal bilateral brain areas conjointly activated and asymmetrical during listening, production and reading of word-list using fMRI in 144 healthy right-handers (27 years {+/-} 6 years). Such a selection made it possible to unravel 14 regions of the left hemisphere including motor, premotor and inferior parietal cortical areas. On the right, 7 regions were selected, including the posterior Human Voice Area (pHVA). To characterize the network organization within these 21 regions, we then analysed resting-state functional connectivity in 138 of the same participants. It allowed us to segregate a network of executive areas in relation with task completion from a bilateral WORD_CORE network composed of (1) all left areas supporting the action-perception cycle, in which articulatory gestures are the central motor units on which word perception, production, but also reading, would develop and act together according to the motor theory of speech; (2) the right pHVA, acting as a prosodic integrative area, underpinning the intertwining across hemispheres between prosodic (pHVA) and phonemic (left SMG) processing. The present results show that word processing, whatever the language modality involved, is based on a network of plurimodal areas hosting processes specific to each hemisphere and on their cooperation built upon synchronisation at rest.

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bioRxiv2018

FALCON: a Functional Atlas of Language COmprehension Networks based on multiple task-induced activation mapping and graph analysis of intrinsic connectivity in 137 healthy right-handers

We herein propose an atlas of 32 sentence-related areas based on a 3-step method combining the analysis of activation and asymmetry during multiple language tasks with hierarchical clustering of resting-state connectivity and graph analyses. 144 healthy right-handers performed fMRI runs based on language production, reading and listening, both with sentences and lists of over-learned words. Sentence minus word-list BOLD contrast and left-minus-right BOLD asymmetry for each task were computed in pairs of homotopic regions of interest (hROIs) from the AICHA atlas. Thirty-two hROIs were identified that were conjointly activated and leftward asymmetrical in each of the 3 language contrasts. Analysis of resting- state temporal correlations of BOLD variations between these 32 hROIs allowed the segregation of a core network, SENT_CORE including 18 hROIs. Resting-state graph analysis applied to SENT_CORE hROIs revealed that the pars triangularis of the inferior frontal gyrus and the superior temporal sulcus were hubs based on their degree centrality, betweenness, and participation values, corresponding to epicentres of sentence processing. Positive correlations between DC and BOLD activation values for SENT_CORE hROIs were observed across individuals and across regions regardless of the task: the more a SENT_CORE area is connected at rest the stronger it is activated during sentence processing. DC measurements in SENT_CORE may thus be a valuable index for the evaluation of inter-individual variations in language areas functional activity in relation to anatomical or clinical patterns in large populations. SENSAAS (SENtence Supramodal Areas AtlaS), comprising the 32 supramodal sentence areas, including SENT-CORE network, can be downloaded at http://www.gin.cnrs.fr/en/tools/.

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bioRxiv2018

A probabilistic atlas of the human pyramidal tract in 410 healthy participants

With the advances in diffusion MRI and tractography, numerous atlases of the human pyramidal tract (PyT) have been proposed but the inherent limitation of tractography to resolve crossing bundles within the centrum semiovale have so far prevented the complete description of the most lateral PyT projections. Here, we combined a precise manual positioning of individual subcortical regions of interest along the descending pathway of the PyT with a new bundle-specific tractography algorithm. This later is based on anatomical priors to improve streamlines tracking in crossing areas. We then extracted both left and right PyT in a large cohort of 410 healthy participants and built a population-based atlas of the whole-fanning PyT with a complete description of its most cortico-lateral projections. Clinical applications are envisaged, the whole-fanning PyT atlas being likely a better marker of corticospinal integrity metrics than those currently used within the frame of prediction of post-stroke motor recovery. The present population-based PyT, freely available, provides an interesting tool for clinical applications in order to locate specific PyT damage and its impact to the short and long-term motor recovery after stroke.

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