Publications by Raphaël Pierre Liégeois

Connectome embedding in multidimensional graph spaces

Dimitri Nestor Alice Van De Ville, Alessandra Griffa, Maria Giulia Preti, Enrico Amico, Raphaël Pierre Liégeois

Nodal properties are of particular importance when investigating patterns in brain networks. Nodal information is usually studied by comparing a few nodal measurements (up to three), resulting in analyses in three-dimensional spaces, at maximum. We offer a ...

MIT PRESS2024

Dynamic functional connectivity to tile the spatiotemporal mosaic of brain states

Dimitri Nestor Alice Van De Ville, Raphaël Pierre Liégeois

Resting-state fMRI has spurred an impressive amount of methods development, among which dynamic functional connectivity (dFC) is one important branch. However, the relevance of time-varying and time-resolved features has led to debate, to which we want to ...

2024

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

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

Precision dynamical mapping using topological data analysis reveals a hub-like transition state at rest

Raphaël Pierre Liégeois

In the absence of external stimuli, neural activity continuously evolves from one configuration to another. Whether these transitions or explorations follow some underlying arrangement or lack a predictable ordered plan remains to be determined. Here, usin ...

Nature Portfolio2022

Brain structure-function coupling provides signatures for task decoding and individual fingerprinting

Dimitri Nestor Alice Van De Ville, Alessandra Griffa, Maria Giulia Preti, Enrico Amico, Raphaël Pierre Liégeois

Brain signatures of functional activity have shown promising results in both decoding brain states, meaning distinguishing between different tasks, and fingerprinting, that is identifying individuals within a large group. Importantly, these brain signature ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2022

On the Spatial Distribution of Temporal Complexity in Resting State and Task Functional MRI

Dimitri Nestor Alice Van De Ville, Maria Giulia Preti, Enrico Amico, Raphaël Pierre Liégeois, Amir Hossein Omidvarnia

Measuring the temporal complexity of functional MRI (fMRI) time series is one approach to assess how brain activity changes over time. In fact, hemodynamic response of the brain is known to exhibit critical behaviour at the edge between order and disorder. ...

MDPI2022

Interpreting null models of resting-state functional MRI dynamics: not throwing the model out with the hypothesis

Dimitri Nestor Alice Van De Ville, Raphaël Pierre Liégeois

Null models are useful for assessing whether a dataset exhibits a non-trivial property of interest. These models have recently gained interest in the neuroimaging community as means to explore dynamic properties of functional Magnetic Resonance Imaging (fM ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2021

When makes you unique: Temporality of the human brain fingerprint

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

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

Community-Aware Graph Signal Processing: Modularity Defines New Ways of Processing Graph Signals

Dimitri Nestor Alice Van De Ville, Thomas William Arthur Bolton, Raphaël Pierre Liégeois, Miljan Petrovic

The emerging field of graph signal processing (GSP) allows one to transpose classical signal processing operations (e.g., filtering) to signals on graphs. The GSP framework is generally built upon the graph Laplacian, which plays a crucial role in studying ...

2020

Revisiting correlation-based functional connectivity and its relationship with structural connectivity

Ali H. Sayed, Dimitri Nestor Alice Van De Ville, Raphaël Pierre Liégeois, Augusto José Rabelo Almeida Santos

Patterns of brain structural connectivity (SC) and functional connectivity (FC) are known to be related. In SC-FC comparisons, FC has classically been evaluated from correlations between functional time series, and more recently from partial correlations o ...

MIT PRESS2020