Mila > Team > Blake Richards

Blake Richards

Core Academic Member
Associate Professor, McGill University, Canada CIFAR AI Chair

Blake Richards is an Associate Professor in the School of Computer Science and Department of Neurology and Neurosurgery at McGill University and a Core Faculty Member at Mila. Richards’ research is at the intersection of neuroscience and AI. His laboratory investigates universal principles of intelligence that apply to both natural and artificial agents. He has received several awards for his work, including the NSERC Arthur B. McDonald Fellowship in 2022, the Canadian Association for Neuroscience Young Investigator Award in 2019, and a Canada CIFAR AI Chair in 2018. Richards was a Banting Postdoctoral Fellow at SickKids Hospital from 2011 to 2013. He obtained his PhD in neuroscience from the University of Oxford in 2010 and his BSc in cognitive science and AI from the University of Toronto in 2004.

Publications

2021-12

Your head is there to move you around: Goal-driven models of the primate dorsal pathway
Patrick J Mineault, Shahab Bakhtiari, Blake Aaron Richards and Christopher C Pack
The functional specialization of visual cortex emerges from training parallel pathways with self-supervised predictive learning
Shahab Bakhtiari, Patrick Mineault, Timothy Lillicrap, Christopher Pack and Blake Richards

2021-11

Author Correction: Burst-dependent synaptic plasticity can coordinate learning in hierarchical circuits.
Alexandre Payeur, Jordan Guerguiev, Friedemann Zenke, Blake A Richards and Richard Naud
Nature Neuroscience
(2021-11-02)
europepmc.org

2021-10

From Machine Learning to Robotics: Challenges and Opportunities for Embodied Intelligence
Nicholas Roy, Ingmar Posner, Tim D. Barfoot, Philippe Beaudoin, Yoshua Bengio, Jeannette Bohg, Oliver Brock, Isabelle Depatie, Dieter Fox, Daniel E. Koditschek, Tomás Lozano-Pérez, Vikash Mansinghka, Christopher J. Pal, Blake Richards, Dorsa Sadigh, Stefan Schaal, Gaurav S. Sukhatme, Denis Thérien, Marc Toussaint and Michiel van de Panne
arXiv preprint arXiv:2110.15245
(2021-10-28)
dblp.uni-trier.dePDF

2021-09

Promoting and Optimizing the Use of 3D-Printed Objects in Spontaneous Recognition Memory Tasks in Rodents: A Method for Improving Rigor and Reproducibility.
Mehreen Inayat, Arely Cruz-Sanchez, Hayley H. A. Thorpe, Jude A. Frie, Blake A Richards, Jibran Y. Khokhar and Maithe Arruda-Carvalho
eNeuro
(2021-09-01)
www.eneuro.org
Learning function from structure in neuromorphic networks
Laura E. Suárez, Blake A. Richards, Guillaume Lajoie and Bratislav Misic
Nature Machine Intelligence
(2021-09-01)
europepmc.org[Also on bioRxiv (2020-11-11)]

2021-08

Forgetting Enhances Episodic Control with Structured Memories
Annik Yalnizyan-Carson and Blake A. Richards
bioRxiv
(2021-08-12)
www.biorxiv.orgPDF
Neocortical inhibitory interneuron subtypes are differentially attuned to synchrony- and rate-coded information.
Luke Y Prince, Matthew M Tran, Dorian Grey, Lydia Saad, Helen Chasiotis, Jeehyun Kwag, Michael M Kohl and Blake A Richards
Communications Biology
(2021-08-05)
europepmc.org
Parallel and Recurrent Cascade Models as a Unifying Force for Understanding Subcellular Computation.
Emerson F. Harkin, Peter R. Shen, Anish Goel, Blake A. Richards and Richard Naud
Neuroscience
(2021-08-03)
europepmc.org

2021-07

Time cell encoding in deep reinforcement learning agents depends on mnemonic demands
Dongyan Lin and Blake A. Richards
bioRxiv
(2021-07-16)
www.biorxiv.orgPDF

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)
ui.adsabs.harvard.eduPDF
Adversarial Feature Desensitization
Pouya Bashivan, Mojtaba Faramarzi, Touraj Laleh, Blake Aaron Richards and Irina Rish
NEURIPS 2021
(2021-05-04)
papers.nips.cc
PNS-GAN: Conditional Generation of Peripheral Nerve Signals in the Wavelet Domain via Adversarial Networks
Olivier Tessier-Lariviere, Luke Y. Prince, Pascal Fortier-Poisson, Lorenz Wernisch, Oliver Armitage, Emil Hewage, Guillaume Lajoie and Blake A. Richards
NER 2021
(2021-05-04)
ieeexplore.ieee.org
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
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
Emerson F. Harkin, Peter R. Shen, Blake A. Richards and Richard Naud
bioRxiv
(2021-03-26)
www.biorxiv.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 N. Billeh, Shiella Caldejon, Peter Groblewski, Timothy M. Henley, India Kato, Eric Lee, Jennifer Luviano, Kyla Mace, Chelsea Nayan, Thuyanh V. Nguyen, Kat North, Jed Perkins, Sam Seid, Matthew T. Valley, Ali Williford, Yoshua Bengio... (3 more)
bioRxiv
(2021-01-16)
www.biorxiv.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-nature-com-443.webvpn.bjmu.tsg211.com
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
Adversarial Feature Desensitization
arXiv preprint arXiv:2006.04621
(2020-06-08)
128.84.21.199PDF

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
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
(2020-04-22)
europepmc.orgPDF
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

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)
europepmc.orgPDF

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
Unknown Journal
(2019-06-15)
koreauniv.pure.elsevier.com
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
bioRxiv
(2019-06-15)
www.dpag.ox.ac.ukPDF
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
Unknown Journal
(2019-06-14)
koreauniv.pure.elsevier.com
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
bioRxiv
(2019-06-14)
www.dpag.ox.ac.ukPDF
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-443.webvpn.bjmu.tsg211.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