Neural ComputationNeurosciencePeer-reviewed journal article
Visuomotor mismatch responses as a hallmark of explaining away in causal inference
Abstract
How are visuomotor mismatch responses in visual cortex embedded into cortical processing? We here argue that mismatch responses are best understood as the result of a cooperation of motor and visual areas to jointly explain optic flow. This cooperation ensures that optic flow is not explained redundantly by both areas, which in the language of causal inference is termed explaining away. This improves the efficiency of the resulting neural code, and allows the animal to easily detect movements that are independent of its own locomotion. We demonstrate the emergence of mismatch responses from explaining away in simulations, where spiking neurons learn to encode optic flow stimuli and locomotion. We furthermore lay out arguments against the prevailing idea that mismatch signals are the result of a dedicated error computation in a hierarchical model. These results provide a new perspective on several recent experiments of cross-modal neural interactions in cortex.
- Citations
- 14
- FWCI
- 1.68
- Field percentile
- top 17%
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Locomotion-induced gain of visual responses cannot explain visuomotor mismatch responses in layer 2/3 of primary visual cortex
Anna Vasilevskaya, Felix C Widmer, … Rebecca Jordan·Cell ReportsPeer-reviewed·Feb 22, 2023
- Feature selectivity explains mismatch signals in mouse visual cortex
Tomaso Muzzu, Aman B. Saleem·Cell ReportsPeer-reviewed·Oct 1, 2021
- Visuomotor mismatch EEG responses over occipital cortex of freely moving human subjects
Magdalena Sołyga, Marek Żelechowski, Georg B. Keller·eLifePeer-reviewed·Aug 20, 2026
- Learning to segment self-generated from externally caused optic flow through sensorimotor mismatch circuits
Matthias Brucklacher, Giovanni Pezzulo, … Cyriel M. A. Pennartz·Neural NetworksPeer-reviewed·Sep 28, 2024
- Opposing influence of top-down and bottom-up input on different types of excitatory layer 2/3 neurons in mouse visual cortex
Rebecca Jordan, Georg B. Keller·NeuronPeer-reviewed·Oct 21, 2020
- Multimodal mismatch responses in mouse auditory cortex
Magdalena Sołyga, Georg B. Keller·eLifePeer-reviewed·Feb 10, 2025