Summary
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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More information & hyperlinks
Web resources: | https://cordis.europa.eu/project/id/845884 |
Start date: | 01-04-2019 |
End date: | 31-03-2021 |
Total budget - Public funding: | 224 933,76 Euro - 224 933,00 Euro |
Cordis data
Original 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.Status
CLOSEDCall topic
MSCA-IF-2018Update Date
28-04-2024
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