no code implementations • NeurIPS 2021 • Shahab Bakhtiari, Patrick Mineault, Timothy Lillicrap, Christopher Pack, Blake Richards
We show that when we train a deep neural network architecture with two parallel pathways using a self-supervised predictive loss function, we can outperform other models in fitting mouse visual cortex.
no code implementations • NeurIPS 2021 • Patrick Mineault, Shahab Bakhtiari, Blake Richards, Christopher Pack
To test this hypothesis, we trained a 3D ResNet to predict an agent's self-motion parameters from visual stimuli in a simulated environment.
no code implementations • 15 Dec 2020 • Tara van Viegen, Athena Akrami, Kate Bonnen, Eric DeWitt, Alexandre Hyafil, Helena Ledmyr, Grace W. Lindsay, Patrick Mineault, John D. Murray, Xaq Pitkow, Aina Puce, Madineh Sedigh-Sarvestani, Carsen Stringer, Titipat Achakulvisut, Elnaz Alikarami, Melvin Selim Atay, Eleanor Batty, Jeffrey C. Erlich, Byron V. Galbraith, Yueqi Guo, Ashley L. Juavinett, Matthew R. Krause, Songting Li, Marius Pachitariu, Elizabeth Straley, Davide Valeriani, Emma Vaughan, Maryam Vaziri-Pashkam, Michael L. Waskom, Gunnar Blohm, Konrad Kording, Paul Schrater, Brad Wyble, Sean Escola, Megan A. K. Peters
Neuromatch Academy designed and ran a fully online 3-week Computational Neuroscience summer school for 1757 students with 191 teaching assistants working in virtual inverted (or flipped) classrooms and on small group projects.