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ATTENTIONLOOP

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Investigating the neural mechanisms of feature based and spatial attention in a...

Investigating the neural mechanisms of feature based and spatial attention in a network model of two coupled brain areas "Attention is the ability to focus the processing resources of the brain onto relevant sensory information. This cognitive ability allows us to perceive attended aspects of the environment with enormous precision without being ove... ver más

31/05/2013

CONSORCI INSTITUT...

167K€

Presupuesto del proyecto: 167K€

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CONSORCI INSTITUT D INVESTIGACIONS BIOMEDIQUE... Otra investigación y desarrollo experimental en ciencias naturales y técnicas organismos publicos

TRL 4-5 | 50K€

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Financiación concedida El organismo FP7 notifico la concesión del proyecto el día 2013-05-31 No tenemos la información de la convocatoria

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Líder del proyecto

CONSORCI INSTITUT D INVESTIGACIONS BIOMEDIQUE... Otra investigación y desarrollo experimental en ciencias naturales y técnicas organismos publicos

TRL 4-5 | 50K€

Presupuesto del proyecto 167K€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto "Attention is the ability to focus the processing resources of the brain onto relevant sensory information. This cognitive ability allows us to perceive attended aspects of the environment with enormous precision without being overwhelmed by irrelevant information. Recordings from neurons in the cortex of monkeys performing attentional tasks have demonstrated attentional modulation of sensory neurons in attend-to-location and attend-to-feature tasks (spatial and feature-based attention). The neural activity in sensory areas is not only modulated by attentional top-down signals but also by sensory-driven bottom-up processes such as neural adaptation. Despite extensive research on these phenomena, an explanation of attention at the level of single neurons and neural networks has remained elusive. The goal of the proposed project is to integrate bottom-up and top-down processes in a computational model in order to progress in the mechanistic understanding of visual attention. We propose using a multidisciplinary approach, based on a tight interaction of modeling and experiment. Experimental data from direction selective neurons of the visual cortex, which have been recorded by our collaborators, will guide the development of a biophysical network model and the model will, in turn, facilitate the data analysis. The model will consist of two cortical areas, one devoted to the active maintenance of information (working memory circuit in prefrontal or parietal cortex) and the other one responsive to novel stimuli (visual cortex, endowed with adaptation mechanisms). We expect the model to clarify the contribution to attentional modulation of interactions within and across cortical areas. In particular, we aim to investigate (1) the underlying mechanisms of bottom-up and top-down processes, (2) the interaction of spatial and feature-based attention, and (3) the influence of attention on the oscillatory synchronization and variability of neuronal responses."

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