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[R] End-to-end neural system identification with neural information flow

We propose a method for training convolutional neural networks to learn similar systems of transformations as exist in the human brain. We recorded brain data from exposing a participant to plenty of visual data (a TV series) and use the same visual data as input to a network. We train the network by attaching brain activity observation models for different visual system regions to the layer activity tensors (through low-rank tensor decomposition).

The sole training signal is the error between the measured brain activity and the activity predicted by these observation models. We could verify that the model learns several known properties of the visual system.

https://www.biorxiv.org/content/10.1101/553255v2

submitted by /u/kseeliger
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.