Investigating the neural mechanisms of feature-based and spatial attention in a network model of two coupled brain areas

Objective

"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."

Fields of science (EuroSciVoc)

CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.

• natural sciences computer and information sciences data science
• natural sciences computer and information sciences artificial intelligence computational intelligence

Programme(s)

Multi-annual funding programmes that define the EU’s priorities for research and innovation.

• FP7-PEOPLE - Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013)

Topic(s)

Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.

• FP7-PEOPLE-2010-IEF - Marie-Curie Action: "Intra-European fellowships for career development"

Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

FP7-PEOPLE-2010-IEF
See other projects for this call

Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

MC-IEF - Intra-European Fellowships (IEF)

Coordinator