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Content archived on 2024-05-29

Neural decision-making in motion


Our objectives are:
(1) to understand the neural mechanisms underlying fast target selection and sensory-guided decisions in humans in motion and
(2) to transfer this knowledge into an artificial cognitive system for robotic navigation.

We here foster a combined experimental and modelling approach that aims to reveal the mechanisms of visual cognition as they interact with processes of neural decision-making and attention selection. A critical new departure will be to evaluate and model performance for a moving observer. The project aims to integrate cognitive processes, such as decision-making, the relation between decision-making and learning, attention selection based on such decisions, and the coordination of sensory processes with selection processes in the moving participant.

We will approach this question at five levels:

1) We will study fast decisions, motion-based attention selection and scene interpretation in humans at the behavioural level as well as at the level of the underlying brain activity using neuro-imaging methods.
2) We will focus on sensory and cognitive processes in animal models to investigate their role in fast neural processing in motion perception.
3) We will develop neural network models that are constructed on the basis of the information obtained in the animal models and simulate them in order to demonstrate the key behavioural patterns.
4) Deficits arising from brain damage will be explored in patients. We intend to determine the contribution of cortical areas as they contribute to whole-system behaviour in the estimation of self-motion and navigation. We apply these results to optimise behavioural monitoring with algorithms for extracting eye/head movements in the moving observer.
5) The resulting models will endow artificial cognitive systems with the ability to interpret and act on data arising from real-world events.

All five approaches will be integrated to form a new theory on decision-making in motion.

Call for proposal

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Participants (9)