Neural & Computational Principles of Multisensory Integration during Active Sensing and Decision-Making
Sector: Education • Location: United Kingdom
Source: EU Funding & Tenders Portal
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 ov
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Participants
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Company | Obfuscated Data |
Status
Original status | ended |
Taiyo status | Obfuscated Data |
Taiyo last update | 00-00-0000 |
Available timestamps | 00-00-0000 |
Available timestamp type | Obfuscated Data |
Contact
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Description
Description | 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. |
Original sub-sector | Obfuscated |
Original Currency | USD |
Original budget | 000000000000000 |
Procurement method | Obfuscated Data |
Budget | 000000000000000 |
Location
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Source
Source reliability | High |
Data quality score | 100% |
Source | Obfuscated Data |
URL | obfuscated_data,obfuscateddata.com |
More Details
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