Publications associées (229)

Reverse engineering Lewy bodies: how far have we come and how far can we go?

Hilal Lashuel, Mohamed Bilal Fares, Somanath Jagannath

Lewy bodies (LBs) are α-synuclein (α-syn)-rich intracellular inclusions that are an important pathological hallmark of Parkinson disease and several other neurodegenerative diseases. Increasing evidence suggests that the aggregation of α-syn has a central ...
2021

Robot-induced hallucinations in Parkinson’s disease depend on altered sensorimotor processing in fronto-temporal network

Dimitri Nestor Alice Van De Ville, Olaf Blanke, Fosco Bernasconi, Jevita Potheegadoo, Michel Akselrod, Nathan Quentin Faivre, Giulio Rognini, Masayuki Hara, Michela Bassolino, Eva Blondiaux, Giedre Stripeikyte, Matteo Franza, Stéphanie Konik

Hallucinations in Parkinson’s disease (PD) are disturbing and frequent non-motor symptoms and constitute a major risk factor for psychosis and dementia. We report a robotics-based approach applying conflicting sensorimotor stimulation, enabling the inducti ...
2021

Dynamic functional brain networks underlying the temporal inertia of negative emotions

Dimitri Nestor Alice Van De Ville, Thomas William Arthur Bolton, Gwladys Rey, Julian Gaviria

Affective inertia represents the lasting impact of transient emotions at one time point on affective state at a subsequent time point. Here we describe the neural underpinnings of inertia following negative emotions elicited by sad events in movies. Using ...
ACADEMIC PRESS INC ELSEVIER SCIENCE2021

EEG Microstates Predict Concurrent fMRI Dynamic Functional Connectivity States

João Pedro Forjaco Jorge, Patricia Figueiredo, Ana Francisca Leal Silva Soares, Thomas Koenig

Brain functional connectivity measured by resting-state fMRI varies over multiple time scales, and recurrent dynamic functional connectivity (dFC) states have been identified. These have been found to be associated with different cognitive and pathological ...
SPRINGER2020

Modeling time-varying brain networks with a self-tuning optimized Kalman filter

David Pascucci, Gijs Plomp

Brain networks are complex dynamical systems in which directed interactions between different areas evolve at the sub-second scale of sensory, cognitive and motor processes. Due to the highly non-stationary nature of neural signals and their unknown noise ...
2020

Sparse coupled logistic regression to estimate co-activation and modulatory influences of brain regions

Dimitri Nestor Alice Van De Ville, Thomas William Arthur Bolton, Ye Tian

Accurate mapping of the functional interactions between remote brain areas with resting-state functional magnetic resonance imaging requires the quantification of their underlying dynamics. In conventional methodological pipelines, a spatial scale of inter ...
IOP PUBLISHING LTD2020

The Inequality of Neural Destiny: Signatures of Lifecourse Socioeconomic Conditions in Markers of Brain Tissue Myelination and Volume

Maria del Carmen Sandi Perez, Bogdan Draganski, Leyla Loued-Khenissi

Socioeconomic status (SES) plays a significant role in health and disease. At the same time, early-life conditions affect neural function and structure, suggesting the brain may be a conduit for the biological embedding of SES. Here, we investigate the neu ...
2020

Exploring dynamic functional connectivity by incorporating prior knowledge of brain structure

Anjali Bagunu Tarun

The synchronized firing of distant neuronal populations gives rise to a wide array of functional brain networks that underlie human brain function. Given the enormous perception, learning, and cognition potential of the human brain, it is not surprising th ...
EPFL2020

Hallucination Engineering: From Neuroscience Robotics to Hallucinations in Health and Disease

Eva Blondiaux

My thesis focuses on a psychotic symptom called the presence hallucination (PH). PHs are defined as the false perception that someone is nearby when no one is actually present. PHs can occur in various populations, ranging from healthy subjects (when expos ...
EPFL2020

Default mode network and the timed up and go in MCI: A structural covariance analysis

Alessandra Griffa

Background: The timed up and go (TUG) is a test used to assess mobility in older adults and patients with neurological conditions. This study aims to compare brain gray matter (GM) correlates and structural covariance networks associated with the TUG time ...
PERGAMON-ELSEVIER SCIENCE LTD2020

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