You are here: Home News Talk by Michael Wibral (Goettingen): "Using information theory to test predictive coding theories"

Talk by Michael Wibral (Goettingen): "Using information theory to test predictive coding theories"

When Dec 10, 2019
from 06:00 to 08:00
Add event to calendar vCal
iCal

Affective Neuroscience and Psychophysiology  

Colloquium

Michael Wibral

(Goettingen)

10.12.2019 18:00 - 20:00 — GEMI, Room 1.134, Gosslerstr. 14, Goettingen

 

Using information theory to test predictive coding theories

Predictive coding as a theory arguably dominates today's scientific discourse on how the cortex works. Importantly, it is positioned as a theory of general cortical function – yet, empirical tests so far are limited to situations with an explicitly predictive experimental context, simply to allow for a meaningful analysis. In other words, to find and understand the neurophysiological correlates of predictions and errors, experiments posit a priori, when and what is being predicted in which brain region. There are two problems with this approach: first, knowing what is being predicted when and where in the brain seems to require already a fair understanding of how the brain, or the cortex, works – which may not generally be the case yet. Second, restricting empirical tests of a general theory to experimental contexts that are explicitly designed with predictions in mind, in a strict sense prohibits conclusions about the applicability of that theory in other contexts. One might provocatively frame this problems as: "Is the cortex doing predictive coding when we don't test it?". Last but not least, this restriction excludes drawing on the vast majority of empirical neurophysiological data for testing (and possibly refuting) the theory. i.e. all data that were obtained with a focus on other descriptions of cortical function(s). In this talk I will introduce predictive coding theory along with an information theoretic framework for testing predictive coding theories by translating the concepts of predictability, predictions and errors (surprise) into information theoretic quantities measurable from data.

Georg-August-University Goettingen
Georg-Elias-Müller-Institute of Psychology
Department of Affective Neuroscience and Psychophysiology
Goßlerstr. 14, 37073 Göttingen