Multiple concurrent predictions inform prediction error in the human auditory pathway.


Journal

The Journal of neuroscience : the official journal of the Society for Neuroscience
ISSN: 1529-2401
Titre abrégé: J Neurosci
Pays: United States
ID NLM: 8102140

Informations de publication

Date de publication:
10 Nov 2023
Historique:
received: 02 12 2022
revised: 08 09 2023
accepted: 16 09 2023
medline: 11 11 2023
pubmed: 11 11 2023
entrez: 10 11 2023
Statut: aheadofprint

Résumé

The key assumption of the predictive coding framework is that internal representations are used to generate predictions on how the sensory input will look like in the immediate future. These predictions are tested against the actual input by the so-called prediction error units, which encode the residuals of the predictions. What happens to prediction errors, however, if predictions drawn by different stages of the sensory hierarchy contradict each other? To answer this question, we conducted two fMRI experiments while male and female human participants listened to sequences of sounds: pure tones in the first experiment, frequency-modulated sweeps in the second experiment. In both experiments we used repetition to induce predictions based on stimulus statistics (stats-informed predictions) and abstract rules disclosed in the task instructions to induce an orthogonal set of (task-informed) predictions. We tested three alternative scenarios: neural responses in the auditory sensory pathway encode prediction error with respect to 1) the stats-informed predictions, 2) the task-informed predictions, or 3) a combination of both. Results showed that neural populations in all recorded regions (bilateral inferior colliculus, medial geniculate body, and primary and secondary auditory cortices) encode prediction error with respect to a combination of the two orthogonal sets of predictions. The findings suggest that predictive coding exploits the non-linear architecture of the auditory pathway for the transmission of predictions. Such non-linear transmission of predictions might be crucial for the predictive coding of complex auditory signals like speech.

Identifiants

pubmed: 37949655
pii: JNEUROSCI.2219-22.2023
doi: 10.1523/JNEUROSCI.2219-22.2023
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

Copyright © 2023 the authors.

Auteurs

Alejandro Tabas (A)

Department of Engineering, University of Cambridge, UK.
Department of Psychology, Technische Universität Dresden, Dresden, Germany.
Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.

Katharina von Kriegstein (K)

Department of Psychology, Technische Universität Dresden, Dresden, Germany.
Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.

Classifications MeSH