Literature DB >> 23151506

Frequency modulation entrains slow neural oscillations and optimizes human listening behavior.

Molly J Henry1, Jonas Obleser.   

Abstract

The human ability to continuously track dynamic environmental stimuli, in particular speech, is proposed to profit from "entrainment" of endogenous neural oscillations, which involves phase reorganization such that "optimal" phase comes into line with temporally expected critical events, resulting in improved processing. The current experiment goes beyond previous work in this domain by addressing two thus far unanswered questions. First, how general is neural entrainment to environmental rhythms: Can neural oscillations be entrained by temporal dynamics of ongoing rhythmic stimuli without abrupt onsets? Second, does neural entrainment optimize performance of the perceptual system: Does human auditory perception benefit from neural phase reorganization? In a human electroencephalography study, listeners detected short gaps distributed uniformly with respect to the phase angle of a 3-Hz frequency-modulated stimulus. Listeners' ability to detect gaps in the frequency-modulated sound was not uniformly distributed in time, but clustered in certain preferred phases of the modulation. Moreover, the optimal stimulus phase was individually determined by the neural delta oscillation entrained by the stimulus. Finally, delta phase predicted behavior better than stimulus phase or the event-related potential after the gap. This study demonstrates behavioral benefits of phase realignment in response to frequency-modulated auditory stimuli, overall suggesting that frequency fluctuations in natural environmental input provide a pacing signal for endogenous neural oscillations, thereby influencing perceptual processing.

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Mesh:

Year:  2012        PMID: 23151506      PMCID: PMC3523826          DOI: 10.1073/pnas.1213390109

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  46 in total

1.  An oscillatory hierarchy controlling neuronal excitability and stimulus processing in the auditory cortex.

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2.  What's that sound? Matches with auditory long-term memory induce gamma activity in human EEG.

Authors:  Daniel Lenz; Jeanette Schadow; Stefanie Thaerig; Niko A Busch; Christoph S Herrmann
Journal:  Int J Psychophysiol       Date:  2006-09-07       Impact factor: 2.997

3.  Phase patterns of neuronal responses reliably discriminate speech in human auditory cortex.

Authors:  Huan Luo; David Poeppel
Journal:  Neuron       Date:  2007-06-21       Impact factor: 17.173

4.  This is the rhythm of your eyes: the phase of ongoing electroencephalogram oscillations modulates saccadic reaction time.

Authors:  Jan Drewes; Rufin VanRullen
Journal:  J Neurosci       Date:  2011-03-23       Impact factor: 6.167

5.  Tuning of the human neocortex to the temporal dynamics of attended events.

Authors:  Julien Besle; Catherine A Schevon; Ashesh D Mehta; Peter Lakatos; Robert R Goodman; Guy M McKhann; Ronald G Emerson; Charles E Schroeder
Journal:  J Neurosci       Date:  2011-03-02       Impact factor: 6.167

6.  The topography of event-related potentials in passive and active conditions of a 3-tone auditory oddball test.

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Journal:  Int J Neurosci       Date:  1995-04       Impact factor: 2.292

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Authors:  M R Jones
Journal:  Psychol Rev       Date:  1976-09       Impact factor: 8.934

8.  Important associations among EEG-dynamics, event-related potentials, short-term memory and learning.

Authors:  E Başar; H G Stampfer
Journal:  Int J Neurosci       Date:  1985-05       Impact factor: 2.292

9.  Concurrent encoding of frequency and amplitude modulation in human auditory cortex: MEG evidence.

Authors:  Huan Luo; Yadong Wang; David Poeppel; Jonathan Z Simon
Journal:  J Neurophysiol       Date:  2006-03-01       Impact factor: 2.714

10.  FieldTrip: Open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data.

Authors:  Robert Oostenveld; Pascal Fries; Eric Maris; Jan-Mathijs Schoffelen
Journal:  Comput Intell Neurosci       Date:  2010-12-23
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  112 in total

1.  Cortical entrainment to music and its modulation by expertise.

Authors:  Keith B Doelling; David Poeppel
Journal:  Proc Natl Acad Sci U S A       Date:  2015-10-26       Impact factor: 11.205

2.  Oscillatory phase shapes syllable perception.

Authors:  Sanne ten Oever; Alexander T Sack
Journal:  Proc Natl Acad Sci U S A       Date:  2015-12-14       Impact factor: 11.205

Review 3.  Neural correlates of auditory scene analysis and perception.

Authors:  Kate L Christison-Lagay; Adam M Gifford; Yale E Cohen
Journal:  Int J Psychophysiol       Date:  2014-03-25       Impact factor: 2.997

4.  Theta and Gamma Bands Encode Acoustic Dynamics over Wide-Ranging Timescales.

Authors:  Xiangbin Teng; David Poeppel
Journal:  Cereb Cortex       Date:  2020-04-14       Impact factor: 5.357

5.  Neuronal phase consistency tracks dynamic changes in acoustic spectral regularity.

Authors:  Adam M Gifford; Michael R Sperling; Ashwini Sharan; Richard J Gorniak; Ryan B Williams; Kathryn Davis; Michael J Kahana; Yale E Cohen
Journal:  Eur J Neurosci       Date:  2018-11-29       Impact factor: 3.386

Review 6.  A New Unifying Account of the Roles of Neuronal Entrainment.

Authors:  Peter Lakatos; Joachim Gross; Gregor Thut
Journal:  Curr Biol       Date:  2019-09-23       Impact factor: 10.834

Review 7.  Exploring how musical rhythm entrains brain activity with electroencephalogram frequency-tagging.

Authors:  Sylvie Nozaradan
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2014-12-19       Impact factor: 6.237

8.  Intracortical Microstimulation Modulates Cortical Induced Responses.

Authors:  Mathias Benjamin Voigt; Prasandhya Astagiri Yusuf; Andrej Kral
Journal:  J Neurosci       Date:  2018-07-27       Impact factor: 6.167

9.  Surmising synchrony of sound and sight: Factors explaining variance of audiovisual integration in hurdling, tap dancing and drumming.

Authors:  Nina Heins; Jennifer Pomp; Daniel S Kluger; Stefan Vinbrüx; Ima Trempler; Axel Kohler; Katja Kornysheva; Karen Zentgraf; Markus Raab; Ricarda I Schubotz
Journal:  PLoS One       Date:  2021-07-22       Impact factor: 3.240

10.  An oscillating computational model can track pseudo-rhythmic speech by using linguistic predictions.

Authors:  Sanne Ten Oever; Andrea E Martin
Journal:  Elife       Date:  2021-08-02       Impact factor: 8.140

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