Brains, Minds + Machines Seminar Series: Probing memory circuits in the primate brain: from single neurons to neural networks

Mar 22, 2019 - 4:00 pm
Venue:  Singleton Auditorium (46-3002) Address:  MIT Brain and Cognitive Sciences Complex (MIT Bldg 46), 43 Vassar Street, Cambridge MA 02139 Speaker/s:  Julio Martinez-Trujillo

Abstract: The brain’s memory systems are like time machines for thought: they transport sensory experiences from the past to the present, to guide our current decisions and actions. Memories have been classified into long-term, stored for time intervals of days, months, or years, and short-term, stored for shorter intervals of seconds or minutes. There is a consensus that these two types of memories involve different brain systems and have different underlying mechanisms. In this talk I will present data from different experiments in non-human primates examining brain circuits and mechanisms of both short-term memory and long-term memory.

 

Biography: Julio Martinez-Trujillo is Professor in the Department of Physiology and Pharmacology and Scientist at the Robarts Research Institute. He holds an Academic Chair in Autism. Prior to joining Western University in 2014, he was Associate Professor in the Department of Physiology and Canada Research Chair in Neuroscience at McGill University.

Organizer:  Hector Penagos Frederico Azevedo Organizer Email:  cbmm-contact@mit.edu

Brains, Minds + Machines Seminar Series: Apical dendrites as a site for gradient calculations

Apr 26, 2019 - 4:00 pm
Photo of Blake Richards
Venue:  Singleton Auditorium(46-3002) Address:  MIT Bldg 46-3002, 43 Vassar Street, Cambridge MA 02139 Speaker/s:  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 requires changes to synaptic weights that approximate the gradient of a global loss function. For neuroscientists, this means that the brain must have mechanisms for communicating loss gradients between regions, either explicitly or implicitly. Here, I describe our research into potential means of communicating loss gradients using the unique properties of apical dendrites in pyramidal neurons. I will present modelling work showing that, in principle, ensembles of pyramidal neurons could using the temporal derivative of their activity to estimate cost gradients. I will also show how this can be learned using the discontinuities that spikes induce. Finally, I will discuss specific experimental predictions that arise from these theories.

 

This event is co-organized by the CBMM Trainee Leadership Council.

Organizer:  Hector Penagos Frederico Azevedo Martin Schrimpf Organizer Email:  cbmm-contact@mit.edu

ML seminar: Is Learning Compatible with (Over)fitting to the Training Data?

Nov 14, 2018 - 4:30 am
Prof. Sasha Rakhlin
Venue:  Stata Blgd, 32-155 Speaker/s:  Sasha Rakhlin, MIT, LIDS, CBMM

Prof. Rakhlin will be presenting the ML seminar talk next week in CSAIL, MIT Bldg 32.

Abstract: We revisit the basic question: can a learning method be successful if it perfectly fits (interpolates/memorizes) the data? The question is motivated by the good out-of-sample performance of ``overparametrized'' deep neural networks that have the capacity to fit training data exactly, even if labels are randomized. The conventional wisdom in Statistics and ML is to regularize the solution and avoid data interpolation. We challenge this wisdom and propose several interpolation methods that work well, both in theory and in practice. In particular, we present a study of kernel ``ridgeless'' regression and describe a new phenomenon of implicit regularization, even in the absence of explicit bias-variance trade-off. We will discuss the nature of successful learning with interpolation, both in regression and classification._

Organizer:  Tomaso Poggio Organizer Email:  cbmm-contact@mit.edu

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