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Blake Richards

Dr. Blake Richards’ research explores the neurobiology of learning and memory, with the ultimate goal of understanding how experience alters the synaptic connections in the brain. Research in the Richards Lab seeks a unification between experiment and theory by testing hypotheses from computational neuroscience and machine learning. One of the major projects in Dr. Richards’ lab is to identify potential neurophysiological mechanisms for mediating deep learning in the neocortex. This work uses computational models, electrophysiology and in vivo 2-photon imaging to explore how signals between brain regions can coordinate learning across multiple layers of information processing. The second major project in Dr. Richards’ lab explores the interaction between episodic memories, schemata and reinforcement learning. Dr. Richards’ has previously shown that, in-line with computational models of memory consolidation, animals switch over time from using episodic memories to more general or schematic memories when engaged in reinforcement learning. His lab is further exploring the computational utility of this switch as well as the neurobiological mechanisms in the prefrontal cortex and hippocampus that underpin it.


Google Research Faculty Award, 2016.

Human Frontiers Young Investigator Grant, 2015.

NSERC Discovery Grant, 2014.

Banting Postdoctoral Fellowship, 2011.

Relevant Publications

A Santoro, PW Frankland and BA Richards, "Memory Transformation Enhances Reinforcement Learning in Dynamics Environments," Journal of Neuroscience, 36(48), 12228-12242, 2016.

JJ van Rheede, BA Richards and CJ Akerman, "Sensory-evoked spiking behavior emerges via an experience-dependent plasticity mechanism," Neuron, 87 (5), 1050-1062, 2015.

BA Richards, F Xia, A Santoro, J Husse, MA Woodin, SA Josselyn and PW Frankland, "Patterns across multiple memories are identified over time," Nature neuroscience, 17 (7), 981-986, 2014.

AM Muldal, TP Lillicrap, BA Richards and CJ Akerman, "Clonal relationships impact neuronal tuning within a phylogenetically ancient vertebrate brain structure, "Current Biology, 24 (16), 1929-1933, 2014.

AP Yiu et al., "Neurons are recruited to a memory trace based on relative neuronal excitability immediately before training," Neuron, 83 (3), 722-735, 2014.



Fellow Learning in Machines & Brains


University of TorontoDepartment of Biological Sciences


D.Phil. (Neuroscience) University of Oxford

M.Sc. (Neuroscience) University of Oxford

Hon. B.Sc. (Cognitive Science & Artificial Intelligence) University of Toronto



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