Pierre Bellec

The Canadian Pediatric Imaging Platform (C-PIP) Reference Sample: Neuroimaging Protocol and Cross-site Validation for Harmonized Multimodal Pediatric Imaging

The paper describes the development of a harmonized multisite MRI protocol for pediatric brain imaging and validates its cross-site consistency.

Brain states recur across diverse narrative contexts during longitudinal viewing

The paper identifies recurring brain states during longitudinal viewing of a TV series, showing that the repertoire is individual-specific and adapts to narrative content.

Behavioral Imitation with Artificial Neural Networks Leads to Personalized Models of Brain Dynamics During Videogame Play

This paper uses imitation learning with ANNs to model individual brain dynamics during videogame play, finding that subject-specific models better predict brain activity than generic ones.

Training neural networks from scratch in a videogame leads to brittle brain encoding

This study compares brain encoding performance of neural networks trained with different objectives on video game data, finding small advantages for reinforcement learning but overall brittle and limited generalization.

Longitudinal functional connectivity during rest and task is differentially related to Alzheimer's pathology and episodic memory in older adults

The paper examines how changes in functional connectivity during rest and task relate to Alzheimer's pathology and episodic memory in older adults.

Resting-state functional MRI derivatives: A dataset derived from the The Comprehensive Assessment of Neurodegeneration and Dementia Study

The paper provides resting-state functional MRI derivatives from the COMPASS-ND study to aid in neurodegenerative disease research.

Alignment massive of auditory individual artificial networks with fMRI brain data leads to generalizable improvements in brain encoding and downstream tasks

The paper aligns auditory artificial neural networks with individual brain fMRI data, improving brain encoding and downstream auditory tasks, especially with limited training data.

Continuous Evaluation of Denoising Strategies in Resting-State fMRI Connectivity Using fMRIPrep and Nilearn

This paper evaluates denoising strategies in resting-state fMRI using fMRIPrep and Nilearn, finding that scrubbing combined with global signal regression is effective but may disrupt continuous sampling.

Assessment of white matter hyperintensity severity using multimodal MRI in Alzheimer's Disease

This study assesses white matter hyperintensity severity using multimodal MRI in Alzheimer's Disease by analyzing signal measures from different MRI contrasts and their associations with clinical variables.

Interpretable brain decoding from sensations to cognition to action: graph neural networks reveal the representational hierarchy of human cognition

This paper introduces biologically-constrained graph neural networks to decode cognitive processes, revealing functional gradients from sensation to cognition and showing improved inter-subject alignment and behavioral prediction.

Subtypes of functional connectivity associate robustly with ASD diagnosis

The paper identifies functional connectivity subtypes associated with ASD diagnosis and shows their generalizability across independent data.

Deep learning models of cognitive processes constrained by human brain connectomes

This study shows that deep graph neural networks using human connectomes improve cognitive decoding accuracy and robustness by integrating brain dynamics with high-order graph convolutions.

Representational learning of brain responses in executive function and higher-order cognition using deep graph convolutions

This paper uses deep graph convolutions to decode brain activity across cognitive domains, finding that integration boosts high-order cognition decoding while segregation suffices for motor tasks.

Atlas of functional connectivity relationships across rare and common genetic variants, traits, and psychiatric conditions

The paper examines how rare and common genomic variants affect brain functional connectivity, revealing how polygenicity and pleiotropy influence psychiatric conditions and brain networks.

The general impact of haploinsufficiency on brain connectivity underlies the pleiotropic effect of neuropsychiatric CNVs

Neuropsychiatric CNVs reorganize brain connectivity along shared patterns linked to cognitive traits and disorder severity.

Functional Annotation of Human Cognitive States using Deep Graph Convolution

This paper develops a multidomain brain decoder to identify cognitive states from fMRI data with high accuracy across multiple cognitive domains.

Creation of an Open Science Dataset from PREVENT-AD, a Longitudinal Cohort Study of Pre-symptomatic Alzheimer's Disease.

Neuropsychiatric mutations delineate functional brain connectivity dimensions contributing to autism and schizophrenia

The paper examines how CNVs in 16p11.2 and 22q11.2 affect functional brain connectivity in neuropsychiatric disorders, identifying shared dysconnectivity patterns across ASD, SZ, and deletions.

Unraveling reproducible dynamic states of individual brain functional parcellation

This paper introduces a method to identify dynamic states of brain parcellations, finding that dynamic parcellations are more reproducible than static ones and reveal distinct states in heteromodal cortices.

Transferability of Brain decoding using GraphConvolutional Networks

This study investigates the transferability of deep neural networks in brain decoding using fMRI data, finding that scanner site conditions significantly impact feature transfer compared to task domains.

Predicting future cognitive decline from non-brain and multimodal brain imaging data in healthy and pathological aging

The paper predicts future cognitive decline using non-brain and multimodal brain imaging data in healthy and pathological aging, finding that non-brain data and structural MRI improve predictions.

Reproducible functional connectivity endophenotype confers high risk of ASD diagnosis in a subset of individuals

The paper identifies a functional connectivity endophenotype that significantly increases ASD diagnosis risk and generalizes across independent data.

Bagging Improves Reproducibility of Functional Parcellation of the Human Brain

This paper shows that bagging improves reproducibility and test-retest reliability of functional brain parcellations across various conditions and scan times.

Multivariate consistency of resting-state fMRI connectivity maps acquired on a single individual over 2.5 years, 13 sites and 3 vendors

This paper assesses the long-term consistency of resting-state fMRI connectivity maps across multiple sites and vendors over 2.5 years, finding good stability but significant site and vendor effects.

A highly predictive signature of cognition and brain atrophy for progression to Alzheimer’s dementia

The paper identifies a predictive signature of cognition and brain atrophy for progression to Alzheimer’s dementia using machine learning, validated in two MCI cohorts with high positive predictive value.

Data-driven approaches for Tau-PET imaging biomarkers in Alzheimer’s disease

This study uses data-driven clustering to identify spatial patterns of tau-PET distribution in Alzheimer’s disease and compares them to pathology-driven ROIs, finding two clusters with strong cognitive associations.

Multisite Generalizability Of Schizophrenia Diagnosis Classification Based On Functional Brain Connectivity

This study evaluates how well schizophrenia classification using functional brain connectivity generalizes across different sites and cognitive contexts, finding better performance with multisite training data.

Subtypes of functional brain connectivity as early markers of neurodegeneration in Alzheimer’s disease

The paper identifies subtypes of functional brain connectivity in older adults linked to Alzheimer's disease symptoms and risk factors.

BIDS Apps: Improving ease of use, accessibility, and reproducibility of neuroimaging data analysis methods

This paper introduces BIDS Apps, a framework for creating portable neuroimaging analysis tools compatible with BIDS data, improving reproducibility and ease of use.

Resting-state network dysfunction in Alzheimer’s disease: a systematic review and meta-analysis

This study reviews and analyzes functional connectivity changes in Alzheimer's disease and mild cognitive impairment using resting-state fMRI, finding consistent alterations in key networks.