Notes

Predictive Coding in Biology: Problems Problems:

• Errors, Representations and Interpretations
• Learning and Mismatch Negativity

Errors, Representations and Interpretations

Suppose you have a line and then you interrupt it, you would expect in Predictive Coding that the end of the line is an error. But it is difficult to disentangle between a neuron that signals an error and a neuron that signals the end of a line. Is the firing of the neuron a representation of the end of the line or is it a firing in response to an error in prediction?

Kanizsa illusory triangle. Neurons with receptive fields fire at the illusory lines. Are they perception neurons or error neurons? The triangle is not there, so the triangle that we perceive is the result of prediction errors or perception? It is hard to make a proper interpretation.

Learning and Mismatch Negativity When you make an error in prediction, neurons fire to signal the error. In PC, we would expect that the most active neurons get suppressed over time. Because as we learn the mismatch negativity firing activity should go down as the predictions get better. The weird thing is that the activity does not go down in the most active neurons, it goes down in the neurons that are only slightly active.