Workshop on Methods of Information Theory in Computational NeuroscienceThomas ParrUniversity College London
In recent years, the "planning as inference" paradigm has become central to the study of behaviour. The advance offered by this is the formalisation of motivation as a prior belief about "how I am going to act". In this talk, I will overview some the factors that contribute to this prior - through the lens of active inference. These are rooted in optimal experimental design, information theory, and statistical decision making. The first part of the talk summarises the principles that underwrite active inference and motivates the question of how we formulate prior beliefs about how to act. The second part unpacks this in terms of exploitative and explorative behaviours. Finally, we consider the implementation of behavioural policies in terms of movement, the neuronal message passing that underwrites this, and the computational pathologies that result from aberrant priors.
