Activation Relaxation: A Local Dynamical Approximation to Backpropagation in the Brain

Understand

The backpropagation of error algorithm (backprop) has been instrumental in the recent success of deep learning.

• However, a key question remains as to whether backprop can be formulated in a manner suitable for implementation in neural circuitry.
• The primary challenge is to ensure that any candidate formulation uses only local information, rather than relying on global signals as in standard backprop.
• Recently several algorithms for approximating backprop using only local signals have been proposed.