Tightening the Biological Constraints on Gradient-Based Predictive Coding

Understand

Predictive coding (PC) is a general theory of cortical function.

• The local, gradient-based learning rules found in one kind of PC model have recently been shown to closely approximate backpropagation.
• This finding suggests that this gradient-based PC model may be useful for understanding how the brain solves the credit assignment problem.
• The model may also be useful for developing local learning algorithms that are compatible with neuromorphic hardware.