Embedded thumbnail for [video] Evolving Images for Visual Neurons Using a Deep Generative Network Reveals Coding Principles and Neuronal Preferences
[video] Evolving Images for Visual Neurons Using a Deep Generative Network Reveals Coding Principles and Neuronal Preferences
Recorded:
May 1, 2019
Uploaded:
May 13, 2019
Part of
All Captioned Videos, Publication Releases
CBMM Speaker(s):
Gabriel Kreiman, Margaret S. Livingstone, Will Xiao, Carlos Ponce, Peter Schade
Five authors of the above paper, published in the journal "Cell", describe their methods and findings on exciting neurons using generative neural networks in real time.
Embedded thumbnail for Demonstration of MEG data analysis using Brainstorm
Demonstration of MEG data analysis using Brainstorm
Recorded:
May 6, 2019
Uploaded:
May 8, 2019
Part of
MEG Workshop
Speaker(s):
Dimitrios Pantazis
Dimitrios Pantazis, MIT - McGovern Institute for Brain Research
Embedded thumbnail for Large scale high temporal resolution effective connectivity analysis from MEG and the problem of inference
Large scale high temporal resolution effective connectivity analysis from MEG and the problem of inference
Recorded:
May 6, 2019
Uploaded:
May 8, 2019
Part of
MEG Workshop
Speaker(s):
David Gow
David Gow, Massachusetts General Hospital slides (PPTX) and associated video file (MOV)
Embedded thumbnail for Decoding cognitive function with MEG: Recent advances, challenges, and future prospects
Decoding cognitive function with MEG: Recent advances, challenges, and future prospects
Recorded:
May 6, 2019
Uploaded:
May 8, 2019
Part of
MEG Workshop
Speaker(s):
Dimitrios Pantazis
Dimitrios Pantazis, MIT - McGovern Institute for Brain Research slides (PDF)
Embedded thumbnail for MEG/EEG Source Estimation Approaches: A Spectrum of Purpose-Built Optimal Tools
MEG/EEG Source Estimation Approaches: A Spectrum of Purpose-Built Optimal Tools
Recorded:
May 6, 2019
Uploaded:
May 8, 2019
Part of
MEG Workshop
Speaker(s):
Matti Hämäläinen
Matti Hämäläinen, Massachusetts General Hospital slides (PDF)
Embedded thumbnail for A Conversation with Prof. Blake Richards
A Conversation with Prof. Blake Richards
Recorded:
May 2, 2019
Uploaded:
May 2, 2019
Part of
Scientific Interviews
CBMM Speaker(s):
Martin Schrimpf
Speaker(s):
Blake Richards
On April 26, 2019, CBMM graduate student Martin Schrimpf took the opportunity to sit down and chat briefly with Prof. Blake Richards of the University of Toronto / McGill University.
Embedded thumbnail for Neural Population Control via Deep Image Synthesis
Neural Population Control via Deep Image Synthesis
Recorded:
Apr 25, 2019
Uploaded:
May 2, 2019
Part of
All Captioned Videos, Publication Releases
CBMM Speaker(s):
James DiCarlo, Pouya Bashivan, Kohitij Kar
Center for Brains, Minds and Machines researchers and paper authors Jim DiCarlo, Pouya Bashivan and Kohitij Kar discuss their recent research findings as published in the journal Science.
Embedded thumbnail for Evidence that recurrent circuits are critical to the ventral stream’s execution of core object recognition behavior
Evidence that recurrent circuits are critical to the ventral stream’s execution of core object recognition behavior
Recorded:
Apr 25, 2019
Uploaded:
April 29, 2019
Part of
All Captioned Videos, Publication Releases
CBMM Speaker(s):
James DiCarlo, Kohitij Kar
Speaker(s):
Diane Beck
Center for Brains, Minds and Machines researchers and paper authors Jim DiCarlo and Kohitij Kar discuss their recent research findings as published in the journal Nature Neuroscience. Diane Beck of the University of Illinois, Beckman Institute...
Embedded thumbnail for Apical dendrites as a site for gradient calculations
Apical dendrites as a site for gradient calculations
Recorded:
Apr 26, 2019
Uploaded:
April 26, 2019
Part of
All Captioned Videos, Brains, Minds and Machines Seminar Series
Speaker(s):
Blake Richards
Blake Richards, Assistant Professor, Associate Fellow of the Canadian Institute for Advanced Research (CIFAR) Abstract:  Theoretical and empirical results in the neural networks literature demonstrate that effective learning at a real-world scale...
Embedded thumbnail for Principles and applications of relational inductive biases in deep learning
Principles and applications of relational inductive biases in deep learning
Recorded:
Apr 11, 2019
Uploaded:
April 19, 2019
Part of
Computational Tutorials
CBMM Speaker(s):
Kelsey Allen
Kelsey Allen, MIT Common intuition posits that deep learning has succeeded because of its ability to assume very little structure in the data it receives, instead learning that structure from large numbers of training examples. However, recent work...

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