Evidence map›Paper›PMID 32103139›Full record

ArticleScientific reports2020

Binaural summation of amplitude modulation involves weak interaural suppression.

D H Baker, G Vilidaite, E McClarnon, E Valkova, A Bruno, R E Millman

Abstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
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

5 citing papers in PubMed.

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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

6 authors.

D H BakerDepartment of Psychology, University of York, Heslington, York, YO10 5DD, UK. daniel.baker@york.ac.uk.ORCID http://orcid.org/0000-0002-0161-443X
G VilidaiteDepartment of Psychology, University of York, Heslington, York, YO10 5DD, UK.
E McClarnonDepartment of Psychology, University of York, Heslington, York, YO10 5DD, UK.ORCID http://orcid.org/0000-0002-2969-2819
E ValkovaDepartment of Psychology, University of York, Heslington, York, YO10 5DD, UK.
A BrunoDepartment of Psychology, University of York, Heslington, York, YO10 5DD, UK.
R E MillmanManchester Centre for Audiology and Deafness, University of Manchester, Manchester, M13 9PL, UK.

Funding

Wellcome TrustWellcome Trust 213616/Z/18/Z
6 · The paper itself

Abstract

The brain combines sounds from the two ears, but what is the algorithm used to achieve this summation of signals? Here we combine psychophysical amplitude modulation discrimination and steady-state electroencephalography (EEG) data to investigate the architecture of binaural combination for amplitude-modulated tones. Discrimination thresholds followed a 'dipper' shaped function of pedestal modulation depth, and were consistently lower for binaural than monaural presentation of modulated tones. The EEG responses were greater for binaural than monaural presentation of modulated tones, and when a masker was presented to one ear, it produced only weak suppression of the response to a signal presented to the other ear. Both data sets were well-fit by a computational model originally derived for visual signal combination, but with suppression between the two channels (ears) being much weaker than in binocular vision. We suggest that the distinct ecological constraints on vision and hearing can explain this difference, if it is assumed that the brain avoids over-representing sensory signals originating from a single object. These findings position our understanding of binaural summation in a broader context of work on sensory signal combination in the brain, and delineate the similarities and differences between vision and hearing.

Indexed as

Electrophysiological PhenomenaAlgorithmsAuditory PerceptionBrainElectroencephalographyHumansModels, Biological

Identifiers

PMID32103139
PMCPMC7044261

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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.