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

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

Imagine attempting to cross the road on a rainy night. You need to process the incoming stimuli (e.g. car lights, slippery ground) to decide whether, when and how it is safe to do so. To make such choices, we interact with the environment by directing our sensors (e.g. moving eyes or fingers) to extract relevant information. Importantly, the processing of information acquired actively from different senses requires the interaction of multiple brain areas implementing sensory, motor and cognitive functions over time. In this project, I wished to answer the following questions: How do we direct our sensors in order to accumulate evidence from the environment? How do we weigh the information obtained from different senses to create a reliable percept of the external stimuli? How do we translate this percept into decisions and how do these decisions drive subsequent actions? Importantly, I did not want to merely measure how people behave in such scenarios but understand how the human brain samples and processes the relevant information and how this process informs the formation of perceptual choices and ultimately guides subsequent actions. Here, by bringing together behavioural neuroscience, biomedical engineering, computational modelling and neuroimaging, I studied study active multi-sensing and decision-making at the behavioural and neural levels. In particular, the proposed research elucidated a) the strategies used by human participants to actively sample the stimulus (by moving their eyes and fingers to reduce uncertainty), b) the behavioural benefit offered by combining multiple sources of information (by integrating the sensory cues depending on their reliability) as well as c) the neural mechanisms underlying this information gain and its translation into perceptual decisions. In the future, I hope that the findings of this project will foster a) neuroscientific studies in similar naturalistic setups, b) development and application of data analytical methodologies to multimodal neuroscientific signals and c) employment of the obtained knowledge to design prosthetic devices suitable for active sensing (e.g. restoration of active touch).

Data: CORDIS, © European Union