Cortical deviance detection represents a canonical difference signal

Context modulates neural processing of sensory stimuli. Neural responses are suppressed to stimuli that are typical in their context and augmented to stimuli that deviate from their context. The latter has been conceptualized as a "prediction error", which can serve to enhance the salience, direct attention, or support learning about behaviorally relevant events. Predictive coding theories posit that prediction errors act to signal the difference between internal predictions and actual sensory input, yet most paradigms simultaneously alter both predictions and input, so cannot test for a true difference signal. Increased neural responses to deviants could, instead, encode generalized surprise or augmented bottom-up signaling. Here we compare neural responses to auditory stimuli across oddball paradigm variants. We found that responses of putative excitatory neurons in primary auditory cortex (A1) to auditory deviants contain frequency change information and a memory trace of contextual information. Interestingly, in a fixed-deviant oddball paradigm where predictions are altered but deviant input remains constant, neural response patterns encoded standard-to-deviant frequency difference. These results support the interpretation that A1 deviance detection can be interpreted as a sensory prediction error that represents the difference between prediction and sensory input, a corollary of the predictive coding framework.

Authors

Institutions

Publication Details

Journal
bioRxiv (Cold Spring Harbor Laboratory)
Published
2026-01-06
DOI
https://doi.org/10.64898/2026.01.06.697993
Primary Topic
Neural dynamics and brain function
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Cortical deviance detection represents a canonical difference signal

Connor G. Gallimore, Manuel S Malmierca, Adam Hockley, Jordan P Hamm
bioRxiv (Cold Spring Harbor Laboratory)
Neural dynamics and brain function
article

Cortical deviance detection represents a canonical difference signal

Connor G. Gallimore, Manuel S Malmierca, Adam Hockley, Jordan P Hamm
article en

Abstract

Context modulates neural processing of sensory stimuli. Neural responses are suppressed to stimuli that are typical in their context and augmented to stimuli that deviate from their context. The latter has been conceptualized as a "prediction error", which can serve to enhance the salience, direct attention, or support learning about behaviorally relevant events. Predictive coding theories posit that prediction errors act to signal the difference between internal predictions and actual sensory input, yet most paradigms simultaneously alter both predictions and input, so cannot test for a true difference signal. Increased neural responses to deviants could, instead, encode generalized surprise or augmented bottom-up signaling. Here we compare neural responses to auditory stimuli across oddball paradigm variants. We found that responses of putative excitatory neurons in primary auditory cortex (A1) to auditory deviants contain frequency change information and a memory trace of contextual information. Interestingly, in a fixed-deviant oddball paradigm where predictions are altered but deviant input remains constant, neural response patterns encoded standard-to-deviant frequency difference. These results support the interpretation that A1 deviance detection can be interpreted as a sensory prediction error that represents the difference between prediction and sensory input, a corollary of the predictive coding framework.

bioRxiv (Cold Spring Harbor Laboratory)
Nathan Kline Institute for Psychiatric Research (US), Universidad de Salamanca (ES), Instituto de Estudios de Ciencias de la Salud de Castilla y León (ES), Instituto de Investigación Biomédica de Salamanca (ES), New York University (US)
European Commission, Consejería de Educación, Junta de Castilla y León, Junta de Castilla y León, National Institutes of Health, European Regional Development Fund, Agencia Estatal de Investigación
Openalex Percentile: Top 94%
Neural dynamics and brain function
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.