Evidence map›Paper›PMID 42571115›Full record

ArticleCognitive neurodynamics2026

Acetylcholine enhances deviance detection in Hodgkin-Huxley neuronal networks.

Fei Fang, Zi-Gang Huang, Zenas C Chao

Abstract read
In one paragraph

Article in Cognitive neurodynamics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Fei FangKey Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049 China.
Zi-Gang HuangKey Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049 China.ORCID 0000-0001-9648-3067
Zenas C ChaoInternational Research Center for Neurointelligence (WPI-IRCN), UTIAS, The University of Tokyo, Tokyo, Japan.ORCID 0000-0001-9402-0851

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The brain's ability to detect unexpected events, deviance detection (DD), is critical for survival. While DD has been computationally explained by synaptic plasticity, the role of neuromodulators such as acetylcholine (ACh) remains less understood. Here, we examine how ACh modulates DD. Using a cholinergic-sensitive Hodgkin-Huxley network of 200 neurons arranged in 2D space and stimulated via five spatially distinct inputs (A-E), we implemented an oddball paradigm with three conditions: standard (80% A, 20% B), deviant (20% A, 80% B), and a multi-standard control (20% each of A-E). ACh levels were modeled by varying the conductance of a slow K⁺ current, reflecting cholinergic modulation of the M-current. In the absence of ACh, the network already exhibited DD, responding more strongly to deviant A compared to control A. Notably, introducing a small amount of ACh amplified DD, while further increases suppressed it. Maximal DD occurred when strong spike frequency adaptation to standard B reduced competition, and enhanced phase-locking synchronized the network's response to deviant A. These findings reveal how neuromodulation can shape context-sensitive neural computation, optimizing detection of salient events through a dynamic balance of suppression and synchronization. Supplementary Information: The online version contains supplementary material available at 10.1007/s11571-026-10522-3.

Indexed as

AcetylcholineDeviance detectionHodgkin-HuxleyNeuromodulator

Identifiers

PMID42571115
PMCPMC13451467

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.