Active Inference, Predictive Coding and Cortical Architecture

Abstract

This chapter discusses how many features of cortical anatomy and physiology can be understood in the light of a predictive coding theory of brain function. In Sect. 7.1, we briefly discuss the theoretical reasons to suppose that the brain is likely to use predictive coding. One key theoretical underpinning of predictive coding is the free energy principle, which argues that brains must maximize the evidence for their (generative) model of sensory inputs: a process of ‘active inference’. In Sect. 7.2, we discuss how active inference predicts commonalities in the extrinsic connections of sensory and motor systems. Such commonalities are found in their hierarchical structure (shown by laminar characteristics), their topography, their pharmacology and physiology. In Sect. 7.3, we show how the equations describing hierarchical message passing within a predictive coding scheme can be mapped on to key features of intrinsic connections, namely the canonical cortical microcircuit, and their implications for the oscillatory dynamics of different cell populations. In Sect. 7.4, we briefly review some empirical evidence for predictive coding in the brain.