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Project

Unraveling stroke-induced attention deficits by combining computational modeling and brain imaging

Attention helps us to concentrate on what is important and not to get distracted. As such, it pervades what we see, think, remember, do and decide. It comes as no surprise that attention deficits in neurological disorders have a detrimental effect on our daily life. In the context of stroke, these deficits are strongly related to poor recovery. The goal of this project is to unravel attention deficits after stroke and their neural underpinnings. More specifically, we aim to design a timeefficient and patient-friendly tool that reliably measures different aspects of attention, such as the abilities to maintain concentration and ignore distracting information. To understand the brain mechanisms of these attention deficits, we will investigate how they are related to changes in communication between brain areas, and whether changes in brain communication can predict clinical improvement. We will take advantage of state-of-the art neuroimaging techniques that allow us to visualize brain connections at millimeter resolution and track their dynamics at millisecond resolution. The project is expected not only to facilitate the diagnosis of attention deficits after stroke and their underlying neural underpinnings, but also to provide novel insights that can be used to design individualised rehabilitation protocols.

Date:1 Jan 2017 →  31 Dec 2020
Keywords:stroke-induced, attention deficits
Disciplines:Animal experimental and comparative psychology, Applied psychology, Human experimental psychology