Publications by Younes Farouj | EPFL Graph Search

Large-scale brain network dynamics in very preterm children and relationship with socio-emotional outcomes: an exploratory study

Dimitri Nestor Alice Van De Ville, Daniel Mourad Alfy Ramzy Tadros, Lorena Gonçalves de Alcântara e Freitas Krikler, Younes Farouj, Vanessa Siffredi

Background Children born very preterm (VPT;

SPRINGERNATURE2022

Large-scale functional network dynamics in human callosal agenesis: Increased subcortical involvement and preserved laterality

Dimitri Nestor Alice Van De Ville, Anjali Bagunu Tarun, Younes Farouj, Vanessa Siffredi

In the human brain, the corpus callosum is the major white-matter commissural tract enabling the transmission of sensory-motor, and higher level cognitive information between homotopic regions of the two cerebral hemispheres. Despite developmental absence ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2021

When makes you unique: Temporality of the human brain fingerprint

Dimitri Nestor Alice Van De Ville, Enrico Amico, Maria Giulia Preti, Younes Farouj, Raphaël Pierre Liégeois

The extraction of "fingerprints" from human brain connectivity data has become a new frontier in neuroscience. However, the time scales of human brain identifiability are still largely unexplored. We here investigate the dynamics of brain fingerprints alon ...

AMER ASSOC ADVANCEMENT SCIENCE2021

Altered anterior default mode network dynamics in progressive multiple sclerosis

Dimitri Nestor Alice Van De Ville, Maria Giulia Preti, Anjali Bagunu Tarun, Younes Farouj, Giulia Bommarito

Background: Modifications in brain function remain relatively unexplored in progressive multiple sclerosis (PMS), despite their potential to provide new insights into the pathophysiology of the disease at this stage. Objectives: To characterize the dynamic ...

SAGE PUBLICATIONS LTD2021

Deconvolution of Sustained Neural Activity From Large-Scale Calcium Imaging Data

Dimitri Nestor Alice Van De Ville, Fikret Isik Karahanoglu, Younes Farouj

Recent technological advances in light-sheet microscopy make it possible to perform whole-brain functional imaging at the cellular level with the use of Ca2+ indicators. The outstanding spatial extent and resolution of this type of data open unique opportu ...

Institute of Electrical and Electronics Engineers2020

Bold Signal Deconvolution Under Uncertain HÆModynamics: A Semi-Blind Approach

Dimitri Nestor Alice Van De Ville, Fikret Isik Karahanoglu, Younes Farouj

The investigation of spontaneous and evoked neuronal activity from functional Magnetic Resonance Imaging (fMRI) data has come to play a significant role in deepening our understanding of brain function. As this research trend continues, activity detection ...

IEEE2019

Structurally-Informed Deconvolution Of Functional Magnetic Resonance Imaging Data

Dimitri Nestor Alice Van De Ville, Thomas William Arthur Bolton, Younes Farouj, Mert Inan

Neural activity occurs in the shape of spatially organized patterns: networks of brain regions activate in synchrony. Many of these functional networks also happen to be strongly structurally connected. We use this information to revisit the fundamental pr ...

IEEE2019

Quantification Of Resting-State Fmri Networks Driven By Hemodynamically Informed Spatiotemporal Regularization

Dimitri Nestor Alice Van De Ville, Fikret Isik Karahanoglu, Younes Farouj

The brain's spontaneous fluctuations measured by functional magnetic resonance imaging during rest cluster into recurrent activity patterns known as resting-state networks (RSNs). The spatial organization of RSNs in health and disease has been immensely in ...

IEEE2018

Ultrasound spatiotemporal despeckling via Kronecker wavelet-Fisz thresholding

Younes Farouj

2018

Graph Slepians To Strike A Balance Between Local And Global Network Interactions: Application To Functional Brain Imaging

Dimitri Nestor Alice Van De Ville, Thomas William Arthur Bolton, Younes Farouj, Silvia Obertino

Brain function exhibits coordinated activity patterns that are also reflected in anatomy, a finding that can be harnessed to constrain the dynamics of functional time series to the underlying structure while performing various signal processing operations. ...

IEEE2018