Publications associées à Determining Significant Connectivity by 4D Spatiotemporal Wavelet Packet Resampling of Functional Neuroimaging Data

Impact of a mindfulness-based intervention on neurobehavioral functioning and its association with large-scale brain networks in preterm young adolescents

Dimitri Nestor Alice Van De Ville, Natalia Fernandez, Petra Susan Hüppi, Vanessa Siffredi

Aim: Adolescents born very preterm (VPT;

Wiley2024

Thalamic contributions to psychosis susceptibility: Evidence from co-activation patterns accounting for intra-seed spatial variability (μCAPs)

Dimitri Nestor Alice Van De Ville, Thomas William Arthur Bolton, Nada Kojovic, Farnaz Delavari

The temporal variability of the thalamus in functional networks may provide valuable insights into the pathophysiology of schizophrenia. To address the complexity of the role of the thalamic nuclei in psychosis, we introduced micro-co-activation patterns ( ...

Wiley2024

Brain microstructural and functional MRI: developments and application to a rat model of Alzheimer's disease

Yujian Diao

Magnetic resonance imaging (MRI) has been a valuable tool in investigating the pathological cascade of Alzheimer's disease (AD) and its progression, which are still open questions. Although some MRI-derived hallmarks in terms of functional connectivity and ...

EPFL2023

Functional neuroimaging options for tinnitus

Patrick Karl Alois Neff

Background: The pathophysiology behind tinnitus is still not well understood. Different imaging methods help in the understanding of the complex relationships that lead to the perception of tinnitus.Objective: Herein, different functional imaging methods t ...

SPRINGER2023

The arrow-of-time in neuroimaging time series identifies causal triggers of brain function

Dimitri Nestor Alice Van De Ville, Thomas William Arthur Bolton, Enrico Amico, Maria Giulia Preti, Raphaël Pierre Liégeois

Moving from association to causal analysis of neuroimaging data is crucial to advance our understanding of brain function. The arrow-of-time (AoT), that is, the known asymmetric nature of the passage of time, is the bedrock of causal structures shaping phy ...

Wiley2023

Brain's Dynamic Functional Organization with Simultaneous EEG-fMRI Networks

João Pedro Forjaco Jorge, Patricia Figueiredo

The brain's functional networks can be assessed using imaging techniques like functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). Recent studies have suggested a link between the dynamic functional connectivity (dFC) captured by ...

SPRINGER INTERNATIONAL PUBLISHING AG2023

Markers of limbic system damage following SARS-CoV-2 infection

Dimitri Nestor Alice Van De Ville, Alessandra Griffa, Alexandre Cionca, Idris Guessous

Alterations of the limbic system may be present in the chronic phase of SARS-CoV-2 infection. Our aim was to study the long-term impact of this disease on limbic system-related behaviour and its associated brain functional connectivity, according to the se ...

OXFORD UNIV PRESS2023

Brain connectome correlates of short-term motor learning in healthy older subjects

Manon Chloé Durand-Ruel, Friedhelm Christoph Hummel, Takuya Morishita, Maeva Moyne, Chang-Hyun Park

The motor learning process entails plastic changes in the brain, especially in brain network reconfigurations. In the current study, we sought to characterize motor learning by determining changes in the coupling behaviour between the brain functional and ...

Elsevier Masson, Corp Off2023

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

Task matters: Individual MEG signatures from naturalistic and neurophysiological brain states

Alessandra Griffa, Enrico Amico, Ekansh Sareen

The discovery that human brain connectivity data can be used as a "fingerprint " to identify a given individual from a population, has become a burgeoning research area in the neuroscience field. Recent studies have iden-tified the possibility to extract t ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2023

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

Dimitri Nestor Alice Van De Ville, Hamid Behjat, Maria Giulia Preti, 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

Dataset for "Elastocapillary menisci mediate interaction of neighboring structures at the surface of a compliant solid"

John Martin Kolinski

This dataset supports the publication 'Elastocapillary menisci mediate interaction of neighboring structures at the surface of a compliant solid' by Lebo Molefe and John M. Kolinski, Physical Review E, (2023). The data are surface profiles of textured surf ...

Zenodo2023

CDKL5 sculpts functional callosal connectivity to promote cognitive flexibility

Valerio Zerbi

Functional and structural connectivity alterations in short- and long-range projections have been reported across neurodevelopmental disorders (NDD). Interhemispheric callosal projection neurons (CPN) represent one of the major long-range projections in th ...

SPRINGERNATURE2023

Neuroengineering of hallucinations through fMRI neurofeedback: Understanding and modulating neural dynamics for the control of hallucinations in health and disease

Herberto Dhanis Pedro De Barros Camacho

Recent years have seen considerable progress in understanding brain function, and in modulating it through real-time fMRI neurofeedback (NF). Inspired by these advances, paired with the unique possibility of inducing the clinically relevant Presence Halluc ...

EPFL2023

Data Transformation in the Processing of Neuronal Signals: A Powerful Tool to Illuminate Informative Contents

Mohammad Ali Shaeri

Neuroscientists seek efficient solutions for deciphering the sophisticated unknowns of the brain. Effective development of complicated brain-related tools is the focal point of research in neuroscience and neurotechnology. Thanks to today's technological a ...

2023

E-Scan: Consuming Contextual Data with Model Plugins

Anastasia Ailamaki, Viktor Sanca

Extracting value and insights from increasingly heterogeneous data sources involves multiple systems combining and consuming the data. With multi-modal and context-rich data such as strings, text, videos, or images, the problem of standardizing the data mo ...

2023

Noninvasive deep brain stimulation to modulate human behavior by means of transcranial temporal interference electrical stimulation

Elena Beanato

All functions we use in our everyday life depend on a complex interplay between both cortical and subcortical brain areas, communicating in between each others. When a region is affected by either an accident, aging or neurodegenerative diseases, the whole ...

EPFL2023

Shared metadata for data-centric materials science

Tristan Bereau, Gian-Marco Rignanese, Giovanni Pizzi, Ronald Earle Miller, Matthias Scheffler, Carsten Baldauf

The expansive production of data in materials science, their widespread sharing and repurposing requires educated support and stewardship. In order to ensure that this need helps rather than hinders scientific work, the implementation of the FAIR-data prin ...

Nature Portfolio2023

Noninvasive theta-burst stimulation of the human striatum enhances striatal activity and motor skill learning

Elena Beanato, Pablo Maceira Elvira, Esra Neufeld, Friedhelm Christoph Hummel, Takuya Morishita, Maximilian Jonas Wessel, Chang-Hyun Park, Traian Popa, Pierre Theopistos Vassiliadis, Pauline Menoud, Fabienne Windel

The stimulation of deep brain structures has thus far only been possible with invasive methods. Transcranial electrical temporal interference stimulation (tTIS) is a novel, noninvasive technology that might overcome this limitation. The initial proof-of-co ...

Nature Portfolio2023

Improving Functional Connectome Fingerprinting with Degree-Normalization

Enrico Amico

Background: Functional connectivity quantifies the statistical dependencies between the activity of brain regions, measured using neuroimaging data such as functional magnetic resonance imaging (fMRI) blood-oxygenation-level dependent time series. The netw ...

MARY ANN LIEBERT, INC2022