Blake Richards

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Core Academic Member
Blake Richards
Assistant Professor, McGill University
Blake Richards

Blake Richards is an Assistant Professor in the School of Computer Science and the Montreal Neurological Institute at McGill University and a Core Faculty Member at Mila. From 2014 to July 2019 he was an Assistant Professor at the University of Toronto in the Department of Biological Sciences (Scarborough) with a cross-appointment to the Department of Cell and Systems Biology and a Faculty Affiliation at the Vector Institute. He was the 2019 Canadian Association for Neuroscience Young Investigator Award Recipient, and one of 29 Canadian Institute for Advanced Research (CIFAR) Canada AI Chairs announced in 2018. He is also a Fellow of the CIFAR Learning in Machines and Brains Program, and a Lab Scientist with the Creative Destruction Lab. From October 2011 to December 2013, Dr. Richards was a Banting Postdoctoral Fellow in the laboratory of Dr. Paul Frankland at SickKids Hospital, where he studied memory consolidation and neural plasticity. From 2007 to 2010, he was a Welcome Trust 4-year PhD student at the University of Oxford in the Department of Pharmacology with Dr. Colin Akerman, where he explored synaptic plasticity in Xenopus laevis embryos. During the MSc component of the program he worked with Dr. Wyeth Bair and Dr. Ole Paulsen, studying computational models of visual processing and voltage bistability in neocortical dendrites. Before his graduate studies, he worked as a programmer and research analyst in magnetic resonance imaging at the Centre for Addiction and Mental Health from 2004-2006. Dr. Richards received his Bachelors degree in Cognitive Science and Artificial Intelligence from the University of Toronto in 2004.

Publications

2021-05

The overfitted brain hypothesis.
Luke Y. Prince and Blake A. Richards
Patterns (New York, N.Y.)
(2021-05-14)
europepmc.org
Burst-dependent synaptic plasticity can coordinate learning in hierarchical circuits.
Alexandre Payeur, Jordan Guerguiev, Friedemann Zenke, Blake A. Richards and Richard Naud
Nature Neuroscience
(2021-05-13)
europepmc.org[Also on bioRxiv (2020-03-31)]
CCN GAC Workshop: Issues with learning in biological recurrent neural networks.
Luke Y. Prince, Ellen Boven, Roy Henha Eyono, Arna Ghosh, Joe Pemberton, Franz Scherr, Claudia Clopath, Rui Ponte Costa, Wolfgang Maass, Blake A. Richards, Cristina Savin and Katharina Anna Wilmes
arXiv preprint arXiv:2105.05382
(2021-05-12)
dblp.uni-trier.dePDF
CaLFADS: latent factor analysis of dynamical systems in calcium imaging data
Luke Yuri Prince, Shahab Bakhtiari, Colleen J Gillon and Blake Aaron Richards
(venue unknown)
(2021-05-04)
openreview.netPDF
Adversarial Feature Desensitization
Pouya Bashivan, Mojtaba Faramarzi, Touraj Laleh, Blake Aaron Richards and Irina Rish
arxiv:cs.LG
(2021-05-04)
ui.adsabs.harvard.eduPDF
Learning to live with Dale's principle: ANNs with separate excitatory and inhibitory units
Jonathan Cornford, Damjan Kalajdzievski, Marco Leite, Amélie Lamarquette, Dimitri Michael Kullmann and Blake Aaron Richards

2021-03

Parallel and recurrent cascade models as a unifying force for understanding sub-cellular computation
Harkin Ef, Shen Pr, Richards Ba and Naud R
bioRxiv
(2021-03-26)
europepmc.orgPDF
Parallel inference of hierarchical latent dynamics in two-photon calcium imaging of neuronal populations
Prince Ly, Bakhtiari S, Gillon Cj and Richards Ba
bioRxiv
(2021-03-08)
europepmc.orgPDF

2021-01

Learning from unexpected events in the neocortical microcircuit
Colleen J. Gillon, Jason E. Pina, Jérôme A. Lecoq, Ruweida Ahmed, Yazan Billeh, Shiella Caldejon, Peter Groblewski, Tim M. Henley, India Kato, Eric Lee, Jennifer Luviano, Kyla Mace, Chelsea Nayan, Thuyanh Nguyen, Kat North, Jed Perkins, Sam Seid, Matthew Valley, Ali Williford, Yoshua Bengio... (3 more)
bioRxiv
(2021-01-16)
www.biorxiv.org

2020-11

Learning function from structure in neuromorphic networks
Suárez Le, Richards Ba, Lajoie G and Misic B
bioRxiv
(2020-11-11)
europepmc.orgPDF

2020-08

Different scaling of linear models and deep learning in UKBiobank brain images versus machine-learning datasets.
Marc-Andre Schulz, B T Thomas Yeo, Joshua T Vogelstein, Janaina Mourao-Miranada, Jakob N Kather, Konrad Kording, Blake Richards and Danilo Bzdok
Nature Communications
(2020-08-25)
www.ncbi.nlm.nih.gov
Dimensionality and flexibility of learning in biological recurrent neural networks
Blake Aaron Richards, Claudia Clopath, Rui Ponte Costa, Wolfgang Maass, Luke Yuri Prince, Arna Ghosh, Roy Pavel Samuel henha Eyono and Franz Scherr
(venue unknown)
(2020-08-03)
openreview.netPDF

2020-06

Dissociating memory accessibility and precision in forgetting.
Sam C Berens, Blake A Richards and Aidan J Horner
Nature Human Behaviour
(2020-06-08)
europepmc.org

2020-05

Systems Consolidation Impairs Behavioral Flexibility
Sankirthana Sathiyakumar, Sofia Skromne Carrasco, Lydia Saad and Blake A. Richards
Learning & Memory
(2020-05-01)
learnmem.cshlp.orgPDF

2020-04

Spike-based causal inference for weight alignment
Jordan Guerguiev, Konrad Kording and Blake Richards
Decision letter: Population coupling predicts the plasticity of stimulus responses in cortical circuits
Blake A Richards and Brent Doiron
eLife
(2020-04-01)
dx.doi.org
Distinct roles of parvalbumin and somatostatin interneurons in gating the synchronization of spike times in the neocortex.
Hyun Jae Jang, Hyowon Chung, James M. Rowland, Blake A. Richards, Michael M. Kohl and Jeehyun Kwag
Science Advances
(2020-04-01)
europepmc.orgPDF

2020-01

Optogenetic activation of parvalbumin and somatostatin interneurons selectively restores theta-nested gamma oscillations and oscillation-induced spike timing-dependent long-Term potentiation impaired by amyloid β oligomers
Kyerl Park, Jaedong Lee, Hyun Jae Jang, Blake A. Richards, Michael M. Kohl and Jeehyun Kwag
BMC Biology
(2020-01-15)
bmcbiol.biomedcentral.comPDF

2019-12

Forgetting at biologically realistic levels of neurogenesis in a large-scale hippocampal model.
Lina M. Tran, Sheena A. Josselyn, Blake A. Richards and Paul W. Frankland
Behavioural Brain Research
(2019-12-30)
www.sciencedirect.com

2019-10

A deep learning framework for neuroscience
Blake A Richards, Timothy P Lillicrap, Philippe Beaudoin, Yoshua Bengio, Rafal Bogacz, Amelia Christensen, Claudia Clopath, Rui Ponte Costa, Archy de Berker, Surya Ganguli, Colleen J Gillon, Danijar Hafner, Adam Kepecs, Nikolaus Kriegeskorte, Peter Latham, Grace W Lindsay, Kenneth D Miller, Richard Naud, Christopher C Pack, Panayiota Poirazi... (12 more)
Nature Neuroscience
(2019-10-28)
www.nature.comPDF

2019-09

Variational inference of latent hierarchical dynamical systems in neuroscience: an application to calcium imaging data
Luke Y. Prince and Blake A. Richards
(venue unknown)
(2019-09-25)
openreview.netPDF
Inferring hierarchies of latent features in calcium imaging data
Luke Y. Prince and Blake A. Richards
(venue unknown)
(2019-09-11)
openreview.netPDF
Deep learning for brains?: Different linear and nonlinear scaling in UK Biobank brain images vs. machine-learning datasets
Marc-Andre Schulz, B Yeo, Joshua Vogelstein, Janaina Mourao-Miranada, Jakob Kather, Konrad Kording, Blake Aaron Richards and Danilo Bzdok
bioRxiv
(2019-09-03)
hal.archives-ouvertes.frPDF

2019-06

Distinct roles of parvalbumin and somatostatin interneurons in the synchronization of spike-times in the neocortex
Hyun Jae Jang, Hyowon Chung, James M. Rowland, Blake A. Richards, Michael M. Kohl and Jeehyun Kwag
Neocortical inhibitory interneuron subtypes display distinct responses to synchrony and rate of inputs
Matthew M. Tran, Luke Y. Prince, Dorian Gray, Lydia Saad, Helen Chasiotis, Jeehyun Kwag, Michael M. Kohl and Blake A. Richards
Dissociating memory accessibility and precision in forgetting [Collection]
Sam Berens, Blake A. Richards and Aidan Horner
(venue unknown)
(2019-06-05)
figshare.com

2019-05

Moving beyond reward prediction errors
Nature Machine Intelligence
(2019-05-01)
www.nature.com

2019-02

Dendritic solutions to the credit assignment problem.
Blake A Richards and Timothy P Lillicrap
Current Opinion in Neurobiology
(2019-02-01)
www.sciencedirect.com

Publications collected and formatted using Paperoni

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