Publications de Hamid Behjat | EPFL Graph Search

On Reconstruction of Cortical Functional Maps Using Subject-Specific Geometric and Connectome Eigenmodes

Dimitri Nestor Alice Van De Ville, Hamid Behjat

Understanding the interplay between human brain structure and function is crucial to discern neural dynamics. This study explores the relation between brain structure and macroscale functional activity using subject-specific structural connectome eigenmode ...

IEEE2025

Voxel-Wise Brain Graphs From Diffusion MRI: Intrinsic Eigenspace Dimensionality and Application to Functional MRI

Hamid Behjat, Anjali Bagunu Tarun

Goal: Structural brain graphs are conventionally limited to defining nodes as gray matter regions from an atlas, with edges reflecting the density of axonal projections between pairs of nodes. Here we explicitly model the entire set of voxels within a brai ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2025

Joint Subject-Identification and Task-Decoding From Inferred Functional Brain Graphs Via a Multi-Task Neural Network

Dimitri Nestor Alice Van De Ville, Hamid Behjat, Ekansh Sareen

Functional connectivity (FC) between brain regions as manifested via fMRI entails signatures that can be used to differentiate individuals and decode cognitive tasks. In this work, we use methods from graph structure inference to estimate FC, which is in c ...

IEEE Computer Society2024

Spectral representation of EEG data using learned graphs with application to motor imagery decoding

Dimitri Nestor Alice Van De Ville, Hamid Behjat, Maliheh Miri

Electroencephalography (EEG) data entail a complex spatiotemporal structure that reflects ongoing organi-zation of brain activity. Characterization of the spatial patterns is an indispensable step in numerous EEG processing pipelines. We present a novel me ...

Elsevier Sci Ltd2023

Brain Fingerprinting Using Fmri Spectral Signatures On High-Resolution Cortical Graphs

Dimitri Nestor Alice Van De Ville, Maria Giulia Preti, Hamid Behjat, Stefano Moia, Carlo Ferritto

Resting-state fMRI has proven to entail subject-specific signatures that can serve as a fingerprint to identify individuals. Conventional methods are based on building a connectivity matrix based on correlation between the average time course of pairs of b ...

IEEE2023

Structural mediation of human brain activity revealed by white-matter interpolation of fMRI

Dimitri Nestor Alice Van De Ville, Thomas William Arthur Bolton, Hamid Behjat, Anjali Bagunu Tarun

Understanding how the anatomy of the human brain constrains and influences the formation of large-scale functional networks remains a fundamental question in neuroscience. Here, given measured brain activity in gray matter, we interpolate these functional ...

2020

Graph Spectral Analysis Of Voxel-Wise Brain Graphs From Diffusion-Weighted Mri

Dimitri Nestor Alice Van De Ville, Hamid Behjat, Anjali Bagunu Tarun

Non-invasive characterization of brain structure has been made possible by the introduction of magnetic resonance imaging (MRI). Graph modeling of structural connectivity has been useful, but is often limited to defining nodes as regions from a brain atlas ...

IEEE2019

Domain-Informed Spline Interpolation

Dimitri Nestor Alice Van De Ville, Zafer Dogan, Hamid Behjat

Standard interpolation techniques are implicitly based on the assumption that the signal lies on a single homogeneous domain. In contrast, many naturally occurring signals lie on an inhomogeneous domain, such as brain activity associated to different brain ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2019

Signal-Adapted Tight Frames on Graphs

Dimitri Nestor Alice Van De Ville, Hamid Behjat

The analysis of signals on complex topologies modeled by graphs is a topic of increasing importance. Decompositions play a crucial role in the representation and processing of such information. Here, we propose a new tight frame design that is adapted to a ...

Institute of Electrical and Electronics Engineers2016

Anatomically-adapted graph wavelets for improved group-level fMRI activation mapping

Dimitri Nestor Alice Van De Ville, Nora Leonardi, Hamid Behjat

A graph based framework for fMRI brain activation mapping is presented. The approach exploits the spectral graphwavelet transform (SGWT) for the purpose of defining an advanced multi-resolutional spatial transformation for fMRI data. The framework extends ...

Elsevier2015