Evidence map›Paper›PMID 25122702›Full record

ArticleJournal of neurophysiology2014

Adaptation of high-gamma responses in human auditory association cortex.

Steven J Eliades, Nathan E Crone, William S Anderson, Deepti Ramadoss, Frederick A Lenz, Dana Boatman-Reich

Abstract read
In one paragraph

Article in Journal of neurophysiology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
2.2field-weighted citation impact, top 13% 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

14 citing papers in PubMed, 31 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Broadband Dynamics Rather than Frequency-Specific Rhythms Underlie Prediction Error in the Primate Auditory Cortex.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2021
    Article
  5. Article
  6. Article
  7. Modeling Neural Adaptation in Auditory Cortex.Frontiers in neural circuits · 2018
    Article
  8. Article
  9. Article
  10. Article
  11. Hierarchy of prediction errors for auditory events in human temporal and frontal cortex.Proceedings of the National Academy of Sciences of the United States of America · 2016
    Article
  12. Article
  13. Article
  14. 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

6 authors at 3 institutions in 1 country.

Steven J EliadesDepartment of Otorhinolaryngology Head and Neck Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania;
Nathan E CroneDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland; and.
William S AndersonDepartment of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Deepti RamadossDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland; and.
Frederick A LenzDepartment of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Dana Boatman-ReichDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland; and dboatma@jhmi.edu.
Johns Hopkins University · USJohns Hopkins Medicine · USUniversity of Pennsylvania · US

Funding

Electrocorticographic studies of human cortical functionR01NS040596 · NINDS · JOHNS HOPKINS UNIVERSITY · PI CRONE, NATHAN E · 2001 to 2014
$6.7M
The Biology of Human Thalamo-Cortical Pain Related ActivityR01NS038493 · NINDS · JOHNS HOPKINS UNIVERSITY · PI LENZ, FRED · 1999 to 2015
$5.2M
Variability in Cortical Auditory Event-Related ResponsesK24DC010028 · NIDCD · JOHNS HOPKINS UNIVERSITY · PI BOATMAN, DANA F. · 2009 to 2014
$812k
NIDCD NIH HHS DC010028NINDS NIH HHS NS040596NINDS NIH HHS R01 NS038493NINDS NIH HHS R01 NS040596
6 · The paper itself

Abstract

This study investigates adaptation of high-frequency cortical responses [>60 Hz; high-gamma (HG)] to simple and complex sounds in human nonprimary auditory cortex. We used intracranial electrocorticographic recordings to measure event-related changes in HG power as a function of stimulus probability. Tone and speech stimuli were presented in a series of traditional oddball and control paradigms. We hypothesized that HG power attenuates with stimulus repetition over multiple concurrent time scales in auditory association cortex. Time-frequency analyses were performed to identify auditory-responsive sites. Single-trial analyses and quantitative modeling were then used to measure trial-to-trial changes in HG power for high (frequent), low (infrequent), and equal (control) stimulus probabilities. Results show strong reduction of HG responses to frequently repeated tones and speech, with no differences in responses to infrequent and equal-probability stimuli. Adaptation of the HG frequent response, and not stimulus-acoustic differences or deviance-detection enhancement effects, accounted for the differential responses observed for frequent and infrequent sounds. Adaptation of HG responses showed a rapid onset (less than two trials) with slower adaptation between consecutive, repeated trials (2-10 s) and across trials in a stimulus block (∼7 min). The auditory-evoked N100 response also showed repetition-related adaptation, consistent with previous human scalp and animal single-unit recordings. These findings indicate that HG responses are highly sensitive to the regularities of simple and complex auditory events and show adaptation on multiple concurrent time scales in human auditory association cortex.

Indexed as

Adaptation, PhysiologicalEvoked Potentials, AuditoryGamma RhythmAdolescentAdultAuditory CortexEpilepsyFemaleHumansMaleadaptationauditory cortexdeviance detectionelectrocorticographygammaoddball

Identifiers

PMID25122702
PMCPMC4274926
OpenAlexW2031495209

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.