Challenging and extending predictive coding as an account of brain function - EXPC

Programme(s): H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC)

Topic(s): ERC-2018-STG - ERC Starting Grant

Call for proposal: ERC-2018-STG

Funding Scheme: ERC-STG - Starting Grant

Grant agreement ID: 804701

Project description

Exploring the nature of predictive coding while being open to unpredictable results

Scientists often discern between the brain – the physical substrate of synaptic connections – and the mind as it relates to thought, emotion and consciousness. Tremendous progress has been made towards enhancing understanding of both. However, while pieces of the puzzle are continually being added, a holistic model of brain function combining the known parts into a realistic whole remains elusive. The EU-funded EXPC project is focused on one of the most popular models of brain function, predictive coding, with the goal of either enhancing its detail or delivering a different model that explains things better. Combining human behavioural data, neuroimaging and computational neuroscience, the team has all the right tools to accomplish their goals.

Objective

Probabilistic models of brain function, which propose that the brain can be understood as implementing the principles of optimal statistical inference, have become extremely influential in recent years. Predictive coding is perhaps the most widely held, and best supported, of these models, particularly within cognitive neuroscience. However, current models of predictive coding and its neuronal substrates are still relatively simple, and do not explain how humans solve a number of fundamental problems. This limits their power to explain brain function. I propose a series of experiments designed to test how human subjects address a number of these core problems. I will use behavioural and neuroimaging data to develop and test extensions to current models (or, if necessary, provide an alternative framework for understanding brain function). The purpose of this is two-fold, to give insight into the computations that underlie cognitive function, and to provide understanding of the neurobiological processes that support those computations. The project will thus constitute a stepping stone towards developing a mechanistic model of how the brain implements cognition.