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Conférence Neurospin

Lundi 12 mars 2018 - 10h00, Amphi NeuroSpin
Centre d’études de Saclay

« fMRI-guided optogenetic manipulation of the attention network in primates »

Wim Vanduffel, K. U. Leuven


Abstract :

In my talk I will present an unpublished study whereby we investigated the causal role of a parietal node of the dorsal attention network in primates during top-down and bottom-up driven selective spatial attention. In this study, we used high resolution fMRI to target task-driven sectors of parietal cortex. Hyperpolarizing optogenetics was then applied to study the effects of short inactivations of small sectors in parietal cortex during selective attention trials. I will show and discuss the effects induced by such short inactivations on local single unit activity, whole-brain network activity (measured with fMRI) and behavioral performance.



Lundi 12 mars 2018 - 11h00, Amphi NeuroSpin
Centre d’études de Saclay

« Dynamics of fMRI brain activity : perspectives for cognitive & clinical neurosciences »

Dimitri Van de Ville, Ecole Polytechnique Fedérale Lausanne


Abstract :

Over the past decade, approaches from signal processing, machine learning, and network science, have had a profound impact on the analysis and the interpretation of brain activity measured by functional magnetic resonance imaging (fMRI). Functional connectivity studies have given not only insights into how the brain supports coordinated cognition, learning, or stability in a changing environment, but also to what extent networks are altered in neurological disease and disorder. Recently, the quest for better understanding of brain dynamics has triggered new ways to approach functional connectivity ; i.e., using time-resolved rather that summarizing correlational measures that miss essential details of network interaction dynamics. In this talk, I will highlight a promising recent advances where fMRI data is analyzed in terms of transient activity. This new framework can deal with spatial and temporal overlap of functional networks, and thus unravels their interdigitated and parallel organization. I will put these developments in perspective for building better, more mechanistic, models of brain function and their potential for disease diagnosis and prognosis.




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