There has been renewed interest in dendrites in computational neuroscience. The corresponding concept in artificial neural networks is that of compartmentalised inputs: integrating different pathways in distinct locations within each unit, with potentially different learning rules. Here we show how a single layer of neurons with multiple compartments can learn sparse codes and their predictive context using a local unsupervised rule, and how this could be used as a building block for cognitive architectures.

Date: 09/03/2018
Time: 16:00
Location: LB252