Project

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Dynamic Networks of Perception, Cognition and Action

Applicant Plomp Gijs
Number 190065
Funding scheme SNSF Professorships
Research institution Université de Fribourg Département de Psychologie
Institution of higher education University of Fribourg - FR
Main discipline Psychology
Start/End 01.04.2020 - 31.03.2021
Approved amount 305'320.00
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All Disciplines (2)

Discipline
Psychology
Neurophysiology and Brain Research

Keywords (8)

Electroencephalography (EEG); Visual perception; Cognition; Networks; Electrophysiology; Granger causality; Functional connectivity; Dynamics

Lay Summary (German)

Lead
Die visuelle Wahrnehmung ist eine der wichtigsten Informationsquellen über unsere Umwelt. Visuelle Wahrnehmung informiert uns über den Stand der Umwelt in Bezug auf unsere aktuellen Ziele und Motivationen und dient dazu, dass wir unser Verhalten entsprechend anpassen können. Bislang ist noch wenig darüber bekannt, wie die dynamische Koordination der Aktivität in unterschiedlichen Gehirnarealen dazu führt, dass unsere visuelle Wahrnehmung unser Denken und Handeln informiert.
Lay summary

In diesem Projekt werden in mehreren Experimenten visuelle Stimulation und Ziele des Beobachters unabhängig voneinander variiert, während die Gehirnaktivität beim Menschen nicht-invasiv mit Hilfe der Elektroenzephalographie (EEG) gemessen wird. Die zeitliche Dynamik, die der Interaktion der dabei aktiven Hirnareale zugrunde liegt, wird mit modernen Netzwerk-basierten Analysemethoden untersucht. Dies liefert Aufschluss darüber, wie dieselbe visuelle Informationen in Abhängigkeit unterschiedlicher Ziele variieren kann.

Ein weiterer Teilaspekt des Projektes beschäftigt sich mit den elementaren Mechanismen, die dem Informationsaustausch zwischen Hirnarealen zugrunde liegen. Dazu wird die elektrische Gehirnaktivität direkt im Tiermodellen gemessen, was in Kollaboration mit der Abteilung für Physiologie der Universität Fribourg stattfindet.

Das Ziel des Projektes ist, besser zu verstehen, wie unterschiedlichen Hirnareale miteinander kommunizieren, und wie solche Interaktionen zwischen Hirnarealen es ermöglichen, visuelle Information mit unseren Zielen und Handlungen zu vereinbaren.

Direct link to Lay Summary Last update: 08.11.2019

Responsible applicant and co-applicants

Employees

Publications

Publication
Nested oscillations and brain connectivity during sequential stages of feature-based attention
Pagnotta Mattia F., Pascucci David, Plomp Gijs (2020), Nested oscillations and brain connectivity during sequential stages of feature-based attention, in NeuroImage, 223, 117354-117354.
Connectome spectral analysis to track EEG task dynamics on a subsecond scale
Glomb Katharina, Rué Queralt Joan, Pascucci David, Defferrard Michaël, Tourbier Sébastien, Carboni Margherita, Rubega Maria, Vulliémoz Serge, Plomp Gijs, Hagmann Patric (2020), Connectome spectral analysis to track EEG task dynamics on a subsecond scale, in NeuroImage, 221, 117137-117137.
Modeling time-varying brain networks with a self-tuning optimized Kalman filter
Pascucci D., Rubega M., Plomp G. (2020), Modeling time-varying brain networks with a self-tuning optimized Kalman filter, in PLOS Computational Biology, 16(8), e1007566-e1007566.

Datasets

VEPCON: Source imaging of high-density visual evoked potentials with multi-scale brain parcellations and connectomes

Author Pascucci, David; Tourbier, Sebastien; Rué-Queralt, Joan; Carboni, Margherita; Hagmann, Patric; Plomp, Gijs
Persistent Identifier (PID) 10.18112/openneuro.ds003505.v1.0.1
Repository OpenNeuro
Abstract
The multimodal dataset VEPCON follows the BIDS standard and provides raw data of high-density EEG, structural MRI and diffusion weighted images (DWI) recorded in 20 participants and derivatives.Visual evoked potentials were recorded while participants discriminated briefly presented faces from scrambled faces, or coherently moving stimuli from incoherent ones. MRI and DWI were recorded in a separate session from the same participants.The dataset contains pre-processed EEG of single trials in each condition, behavioral measures, structural MRIs, individual brain parcellations at 5 spatial resolutions (66 to 998 regions), and corresponding structural connectomes based on fiber count, fiber density, average fractional anisotropy and mean diffusivity maps. In addition, we provide EEG inverse solutions for source imaging based on individual anatomy, and Python and Matlab code for deriving time-series of activity in each brain region, at each parcellation level.This dataset can contribute to multimodal methods development, studying structure-function relations, as well as unimodal optimization of source imaging and graph analysis, among many other possibilities.

Communication with the public

Communication Title Media Place Year
Media relations: print media, online media (Un)durchschaubare Intelligenzen Universitas German-speaking Switzerland 2021

Associated projects

Number Title Start Funding scheme
183714 Dynamic Networks of Perception, Cognition and Action 01.04.2019 SNSF Professorships
157420 Dynamic Networks of Perception, Cognition and Action 01.04.2015 SNSF Professorships

Abstract

The primary function of visual perception is to inform cognition and action. But how vision and its interrelated aspects arise from quickly coordinated activity in multiple brain areas is not well understood. This project uses a dynamic network approach that combines EEG source-imaging, fMRI and Granger-causal modeling to study directed interactions between brain areas in vision with high temporal resolution. Three lines of research are proposed: one for investigating the dynamic interactions underlying visual function in humans, a second for the systematic evaluation of connectivity methods, and a third for identifying the elementary cortical mechanisms underlying visual processing in animal models. The cross-disciplinary approach is expected to link psychological theories to elementary mechanisms and to provide a better understanding of vision and its function for the organism.
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