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Neural & Computational Principles of Multisensory Integration during Active Sensing and Decision-Making

Project description

Unveiling neural mechanisms that underly perceptual decisions

Every day we decide if, when and how we should act according to our goal at a specific moment. We do this by evaluating our external world through our different senses. We elaborate and integrate collected stimuli to make decisions. Such perceptual decisions require various interactions of neural processes. Yet, their profound complex neural processes remain unknown. The EU-funded NeuCoDe project aims to research and explain how multisensory information is processed during active sensing and decision making by applying a unique active sensing model combined with innovative neuroimaging and computational modelling. Ultimately, this project will have a significant impact on the treatment and diagnosis of cognitive and developmental disorders in the future.

Objective

Perceptual decisions rely on the integration of information from the environment, which typically involves the combination of stimuli from different senses. The quality of sensory evidence depends highly on our actions that affect how we acquire information from the external world. Importantly, the processing of this multisensory information requires the interaction of multiple neural processes over time. However, the neural mechanisms underlying this complex human behaviour remain elusive. In this project, I will employ a novel active sensing paradigm coupled with state-of-the-art neuroimaging and computational modelling to probe how the brain samples, processes and integrates multisensory information in order to make fast and accurate decisions. I will devise a reaction-time task where human subjects will actively sense and discriminate the amplitude of two texture stimuli a) using only visual information, b) using only haptic information and c) combining the two sensory cues, while electroencephalograms (EEG) will be recorded. To study this, I will develop a novel computational methodology for the joint analysis of brain activity (EEG), sensorimotor signals (movement kinematics) and behavioural measurements (choice and response time). First, behavioural modelling will provide a mechanistic account of the constituent processes underlying decision fomation. Then, model predictions will inform the joint analysis of neural and sensorimotor signals, to characterize the neural and behavioural basis of active multi-sensing and decision-making. To achieve this, I will devise an information-theoretic methodology that quantifies a) the contribution of each sensory modality to perception and b) the interaction of their neural representations to drive perceptual decisions. Ultimately, this project will elucidate the brain networks involved in active multisensory decision-making and characterize their respective functional roles in behavioural performance.

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MSCA-IF-EF-RI - RI – Reintegration panel

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Call for proposal

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(opens in new window) H2020-MSCA-IF-2018

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Coordinator

UNIVERSITY OF LEEDS
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 224 933,76
Address
WOODHOUSE LANE
LS2 9JT Leeds
United Kingdom

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Region
Yorkshire and the Humber West Yorkshire Leeds
Activity type
Higher or Secondary Education Establishments
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 224 933,76
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