Evidence map›Paper›PMID 30402926›Full record

ArticleThe European journal of neuroscience2019

Neuronal phase consistency tracks dynamic changes in acoustic spectral regularity.

Adam M Gifford, Michael R Sperling, Ashwini Sharan, Richard J Gorniak, Ryan B Williams, Kathryn Davis, Michael J Kahana, Yale E Cohen

Abstract read
In one paragraph

Article in The European journal of neuroscience, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

8 authors.

Adam M GiffordNeuroscience Graduate Group, University of Pennsylvania, Philadelphia, Pennsylvania.
Michael R SperlingJefferson Comprehensive Epilepsy Center, Department of Neurology, Thomas Jefferson University, Philadelphia, Pennsylvania.
Ashwini SharanJefferson Comprehensive Epilepsy Center, Department of Neurology, Thomas Jefferson University, Philadelphia, Pennsylvania.
Richard J GorniakDepartment of Radiology, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, Pennsylvania.
Ryan B WilliamsDepartment of Psychology, University of Pennsylvania, Philadelphia, Pennsylvania.
Kathryn DavisDepartment of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania.
Michael J KahanaNeuroscience Graduate Group, University of Pennsylvania, Philadelphia, Pennsylvania.
Yale E CohenNeuroscience Graduate Group, University of Pennsylvania, Philadelphia, Pennsylvania.ORCID 0000-0002-0830-5162

Funding

SYSTEMS AND INTEGRATIVE BIOLOGYT32GM007517 · NIGMS · UNIVERSITY OF PENNSYLVANIA · PI GOLD, JOSHUA I · 1985 to 2017
$8.0M
Representations of sound processing in the auditory cortexR01DC009224 · NIDCD · UNIVERSITY OF PENNSYLVANIA · PI COHEN, YALE E · 2008 to 2018
$3.1M
Multi-scale study of auditory scene analysis in the ventral auditory pathwayR01DC013961 · NIDCD · UNIVERSITY OF PENNSYLVANIA · PI COHEN, YALE E, FISHMAN, YONATAN · 2015 to 2019
$2.3M
Localizing epileptic networks using novel 7T MRI glutamate imagingK23NS092973 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI DAVIS, KATHRYN ADAMIAK · 2016 to 2020
$980k
Boucai Hearing Restoration FundDARPA Restoring Active Memory (RAM)NIDCD-NIHNIDCD NIH HHS R01 DC009224NIDCD NIH HHS R01 DC013961NIGMS NIH HHS T32 GM007517NIMH-NIHNINDS NIH HHS K23 NS092973
6 · The paper itself

Abstract

The brain parses the auditory environment into distinct sounds by identifying those acoustic features in the environment that have common relationships (e.g., spectral regularities) with one another and then grouping together the neuronal representations of these features. Although there is a large literature that tests how the brain tracks spectral regularities that are predictable, it is not known how the auditory system tracks spectral regularities that are not predictable and that change dynamically over time. Furthermore, the contribution of brain regions downstream of the auditory cortex to the coding of spectral regularity is unknown. Here, we addressed these two issues by recording electrocorticographic activity, while human patients listened to tone-burst sequences with dynamically varying spectral regularities, and identified potential neuronal mechanisms of the analysis of spectral regularities throughout the brain. We found that the degree of oscillatory stimulus phase consistency (PC) in multiple neuronal-frequency bands tracked spectral regularity. In particular, PC in the delta-frequency band seemed to be the best indicator of spectral regularity. We also found that these regularity representations existed in multiple regions throughout cortex. This widespread reliable modulation in PC - both in neuronal-frequency space and in cortical space - suggests that phase-based modulations may be a general mechanism for tracking regularity in the auditory system specifically and other sensory systems more generally. Our findings also support a general role for the delta-frequency band in processing the regularity of auditory stimuli.

Indexed as

AcousticsAcoustic StimulationAdultAuditory PerceptionBrainElectrocorticographyEvoked Potentials, AuditoryFemaleHumansMaleNeuronsSignal Processing, Computer-AssistedSound Spectrography

Identifiers

PMID30402926
PMCPMC6520206

What OpenQuestion holds

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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.