Recorded:
Aug 30, 2021
Uploaded:
August 30, 2021
Part of
Computational Tutorials
CBMM Speaker(s):
Guangyu Robert Yang
Robert Guangyu Yang, MIT
In this hands-on tutorial, we will work together through a number of coding exercises to see how RNNs can be easily used to study cognitive neuroscience questions. We will train and analyze RNNs on various cognitive...
Recorded:
Jul 29, 2021
Uploaded:
August 9, 2021
Part of
All Captioned Videos, Computational Tutorials
Speaker(s):
Carsen Stringer, HHMI Janelia Research Campus
The combination of two-photon microscopy recordings and powerful calcium-dependent fluorescent sensors enables simultaneous recording of unprecedentedly large populations of neurons. While these sensors have matured over several generations of...
Recorded:
Jul 8, 2021
Uploaded:
July 12, 2021
Part of
All Captioned Videos, Computational Tutorials
Speaker(s):
Guillaume Hennequin, Kris Jensen
Guillaume Hennequin, Kris Jensen - University of Cambridge
Colab notebooks:
Introduction to FA and GPFA as probabilistic generative models
Fitting an example data set from a primate reaching task with GPFA
Additional papers and resources...
Recorded:
Apr 8, 2021
Uploaded:
April 9, 2021
Part of
All Captioned Videos, Computational Tutorials
Speaker(s):
Jesse Marshall, Harvard University
Mechanistic studies of complex, ethological animal behaviors are poised to define the next decade of neuroscience. Fully understanding the ontogeny, evolution, and neural basis of these behaviors requires precise 3D measurements of their underlying...
Recorded:
Nov 19, 2020
Uploaded:
November 23, 2020
Part of
All Captioned Videos, Computational Tutorials
Speaker(s):
Eli Pollock
Recurrent neural networks (RNNs) are a powerful model for neural and cognitive phenomena. However, interpreting these models can be a challenge. In this tutorial, we will discuss how dynamical systems theory provides some tools for understanding...
Recorded:
Sep 22, 2020
Uploaded:
September 23, 2020
Part of
All Captioned Videos, Computational Tutorials
Speaker(s):
Christian Bueno, University of California, Santa Barbara
Christian Bueno, University of California, Santa Barbara
Working with lower dimensional representations of data can be valuable for simplifying models, removing noise, and visualization. When data is distributed in geometrically complicated ways,...
Recorded:
Sep 3, 2020
Uploaded:
September 4, 2020
Part of
All Captioned Videos, Computational Tutorials
CBMM Speaker(s):
Maddie Pelz
Lookit is an online platform for designing and running asynchronous developmental studies. This technology allows for more diverse and representative populations to participate in developmental studies than would typically be able to engage in the...
Recorded:
Jul 23, 2020
Uploaded:
July 24, 2020
Part of
All Captioned Videos, Computational Tutorials
Speaker(s):
Shibani Santurkar, MIT
Machine learning models today achieve impressive performance on challenging benchmark tasks. Yet, these models remain remarkably brittle---small perturbations of natural inputs, known as adversarial examples, can severely degrade their behavior.
Why...
Recorded:
Jul 9, 2020
Uploaded:
July 10, 2020
Part of
All Captioned Videos, Computational Tutorials
Speaker(s):
Talmo Pereira, Princeton University
Talmo Pereira, Princeton University
Behavioral quantification, the problem of measuring and describing how an animal interacts with the world, has been gaining increasing attention across disciplines as new computational methods emerge to automate...
Recorded:
Apr 11, 2019
Uploaded:
April 19, 2019
Part of
All Captioned Videos, 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...