Topic: hidden-layer neural activities

Predictive coding (PC) has emerged as an influential normative model of neural computation, with numerous extensions and applications. As such, much effort has been put into mapping PC faithfully onto the cortex, but there are issues that remain unresolved or controversial. In particular, current implementations often involve biologically unrealistic features such as separate value and error neurons and symmetric forward and backward weights across different brain regions. In this work, we show that the PC framework in the linear regime can be modified to map faithfully onto the cortical hier