Predictive cost functions in the neocortex
Predictive cost functions in the neocortex by Prof. Blake Richards
Neural computation is the product of two optimization procedures: natural selection and learning in the individual's lifetime. But, identifying what the neocortex has been optimized for, given its repeated circuit motifs and complex relationship to behaviour, is very challenging. Put another way, is it possible to say what cost functions have shaped the representations in the neocortex? Here, I will describe research in my laboratory aimed at answering this question. I will present both experimental and modelling data to show that the representations in the visual cortex of mice are likely shaped by predictive cost functions – i.e. cost functions that promote the ability to predict the future given the past. I will discuss the potential implications of these results for AI, and argue that converging lines of evidence from multiple fields indicate that predictive cost functions are key to intelligent behaviour, whether in natural or artificial agents.
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