Evidence map›Paper›PMID 30618553›Full record

ArticleFrontiers in neuroscience2018

Mismatch Negativity in Rat Auditory Cortex Represents the Empirical Salience of Sounds.

Tomoyo Isoguchi Shiramatsu, Hirokazu Takahashi

Open access · goldAbstract read
In one paragraph

Article in Frontiers in neuroscience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.0field-weighted citation impact, top 25% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 13 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Tomoyo Isoguchi ShiramatsuResearch Center for Advanced Science and Technology, The University of Tokyo, Tokyo, Japan.
Hirokazu TakahashiResearch Center for Advanced Science and Technology, The University of Tokyo, Tokyo, Japan.
The University of Tokyo · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mismatch negativity (MMN) is an N-methyl-D-aspartic acid-mediated component and thus has been widely considered a major candidate biomarker of schizophrenia. However, at present, no direct evidence has linked the MMN response and aberrant salience processing reported in schizophrenia patients, i.e., whether MMN represents empirical salience of the deviant stimulus. To test the eligibility of the MMN response as a biomarker of schizophrenia, we hypothesized and verified that the MMN in the rat auditory cortex encodes empirical salience, which depends on both empirical rarity of sound and association of sound with salient events through classical conditioning. We exposed rats to sound or appetitive or aversive classical conditioning and extinction training of aversive conditioning, then recorded MMN from the auditory cortex. We focused on the frequency-dependent asymmetry of the MMN amplitude; increment frequency changes elicit asymmetrically larger MMN amplitudes than do decremental frequency changes. We found that sound exposure reversed this asymmetry in rats, indicating that MMN encodes the empirical rarity of deviant sounds. The MMN amplitude was larger in the appetitive or aversive classical conditioning groups, and smaller after extinction training following aversive conditioning. These results indicate that the MMN response reflects the empirical salience of sound. The present work first linked MMN with empirical salience processing and expands the possibilities of MMN as a strong clinical biomarker of schizophrenia.

Indexed as

classical conditioningempirical saliencemicroelectrode arraymismatch negativityschizophrenia

Identifiers

PMID30618553
PMCPMC6304392
OpenAlexW2904344889

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.