[CTN] CTN seminar: Blake Richards (University of Toronto), 3:30 Tuesday Sept. 26, PAS 2464.

[Bryan Tripp]

Hi everyone,

Please join us for the first CTN seminar of the season, with Professor
Blake Richards. The title and abstract follow.

Regards,
Bryan

Title: Deep learning with pyramidal neurons

Abstract:
Deep learning has led to significant advances in artificial intelligence,
in part, by adopting strategies motivated by neurophysiology. However, it
is unclear how deep learning could occur in the real brain, due to the
difficulty of performing credit assignment without backpropagation. Here,
we show that deep learning can be achieved in a biologically feasible
simulation by moving away from point neuron models and towards
multi-compartment neurons. Like neocortical pyramidal neurons, neurons in
our model receive feedforward sensory information and higher-order feedback
in electrotonically segregated compartments. Thanks to this segregation,
the neurons in different layers of the network can coordinate local
synaptic weight updates to achieve global optimization. As a result, the
network can take advantage of multilayer architectures---the hallmark of
deep learning. This work demonstrates that deep learning can be achieved
using segregated dendritic compartments for feedforward and feedback
information, which may help to explain the dendritic morphology of
neocortical pyramidal neurons.
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://artsservices.uwaterloo.ca/pipermail/ctn/attachments/20170912/0133d02f/attachment.html>