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Exploring visual cognition: A combined neuropsychological, behavioural, hemodynamic and modelling approach

Ziel

In the last two decades, connectionist modelling in cognitive science has grown ever more sophisticated. At the same time, recent neuroimaging techniques and related statistical analyses make it possible to explore the neural substrates of complex cognitive processes in humans.

Of these techniques, fMRI has one of the most rapidly growing potentials because of its performance for high spatial resolution and whole-brain measurements. Combining neural network modelling and brain imaging will allow us to examine the functional constraints and interactions known to exist in distributed brain architectures.

The main goal of this project is to characterize the functional neurophysiology of the human perceptual and cognitive system related to attention and emotion/motivation states during behavioural and neural changes associated with the learning of visual perceptual skills.

The project addresses three theoretical and experimental issues:
- the development of connectionist models in close relationship with neurophysiological and behavioural data,
- the coupling of this modelling approach with new empirical experiments and
- the behavioural study of hemianopic patients based on results obtained in issues (1) and (2).

The first aim of this project is exploring the neural circuitry from the retina to subsequent cortical and subcortical areas and specifically the computational efficiency of magnocellular vs parvocellular neural pathways for facial expression processing. Complementary, the second aim consists of modelling the effect of top-down attentional feedback on low-level visual processes.

Wissenschaftliches Gebiet (EuroSciVoc)

Thema/Themen

Aufforderung zur Vorschlagseinreichung

FP6-2002-MOBILITY-5
Andere Projekte für diesen Aufruf anzeigen

Finanzierungsplan

EIF - Marie Curie actions-Intra-European Fellowships

Koordinator

UNIVERSITY MEDICAL CENTER, CMU NEUROLOGY & IMAGING OF COGNITION LABORATORY
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