Pieter Goltstein: Identifying the internal representation of learned visual categories in mice

Abstract

Categorization is a fundamental cognitive process by which we classify and rapidly generalize learned and novel information. But how are category-defining associations internally represented by the brain? In this talk I will present my work on studying neuronal circuits for visual category learning in mice. I will show how the representation of a learned visual category emerges over time in the mouse visual and prefrontal cortex and identify a possible mechanism by which feedback signals enable sensory neurons to acquire category selectivity. Furthermore, I will present recent data on a new approach for studying brain-wide activity patterns, as well as long-range synaptic networks, involved in learning visual associations. Ultimately, the aim of my research is to identify the brain-wide neuronal circuits and computations that underlie the representation of semantic knowledge.

About the speaker and his research

Pieter Goltstein

Presently, I am a postdoctoral researcher and project leader working with Mark Hübener and Tobias Bonhoeffer at the Max Planck Institute for Biological Intelligence in Munich. During my postdoc I developed paradigms for studying the neuronal and synaptic basis of category learning in mice, with the goal to understand neuronal mechanisms underlying semantic memory. During my early scientific training I have obtained a Bachelor's and master's degree in psychology and received a PhD degree in Neurobiology from the University of Amsterdam, investigating effects of learning and behavioral state on primary visual cortex.

Host

Ilka Diester

Whole program

BrainWorlds