Publications de Hamid Behjat | EPFL Graph Search

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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 ...

Oxford2023

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

Domain-Informed Spline Interpolation

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

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, Hamid Behjat, Nora Leonardi

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

Hamid Behjat

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