Critique of the Bayesian brain hypothesis

Understanding the shortcomings of the Bayesian approach to brain

Introduction

Human behavior is driven by incomplete data and methods to turn that data into action and perception. Take, for example, our eyes, which do not actually construct a complete high-resolution picture of our surroundings despite that we experience it so. Instead, that image is filled with noise, missing large chunks, and top of all also inverted. Yet, we can use this incomplete data to navigate the world and successfully perform complex behaviors in it. Based on research in cognitive science, it has been theorized that this results from organisms’ innate ability to carry out statistical inference. This hypothesis is commonly referred to as the Bayesian brain hypothesis, and the theories concerning posit that our minds and brains are near-optimal in solving a variety of tasks (Bower and Davis 2012).

As mentioned by Bowers and Davis (2012), this conclusion that human behavior is close to the Bayesian optimal is exciting as it positions our behavior in a surprising and counterintuitive state of actually being optimal. They continue that this surprising claim has gathered a wide array of research during the years but not that much criticism as highlighted by a 2013 paper by Marcus and Davis.