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Journal of Basic and Clinical Physiology and Pharmacology

Editor-in-Chief: Horowitz, Michal

Editorial Board Member: Das, Kusal K. / Epstein, Yoram / S. Gershon MD, Elliot / Haim, Abraham / Kodesh , Einat / Kohen, Ron / Lichtstein, David / Maloyan, Alina / Mechoulam, Raphael / Roth, Joachim / Schneider, Suzanne / Shohami, Esther / Sohmer, Haim / Yoshikawa, Toshikazu

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CiteScore 2016: 1.01

SCImago Journal Rank (SJR) 2016: 0.349
Source Normalized Impact per Paper (SNIP) 2016: 0.495

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2191-0286
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Volume 25, Issue 3 (Sep 2014)

Issues

Auditory-evoked cortical activity: contribution of brain noise, phase locking, and spectral power

Kelly C. Harris
  • Corresponding author
  • Department of Otolaryngology – Head and Neck Surgery, Medical University of South Carolina, SC, USA
  • Email
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Kenneth I. Vaden Jr.
  • Department of Otolaryngology – Head and Neck Surgery, Medical University of South Carolina, SC, USA
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Judy R. Dubno
  • Department of Otolaryngology – Head and Neck Surgery, Medical University of South Carolina, SC, USA
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
Published Online: 2014-07-19 | DOI: https://doi.org/10.1515/jbcpp-2014-0047

Abstract

Background: The N1-P2 is an obligatory cortical response that can reflect the representation of spectral and temporal characteristics of an auditory stimulus. Traditionally, mean amplitudes and latencies of the prominent peaks in the averaged response are compared across experimental conditions. Analyses of the peaks in the averaged response only reflect a subset of the data contained within the electroencephalogram (EEG) signal. We used single-trial analyses techniques to identify the contribution of brain noise, neural synchrony, and spectral power to the generation of P2 amplitude and how these variables may change across age group. This information is important for appropriate interpretation of event-related potentials (ERPs) results and in understanding of age-related neural pathologies.

Methods: EEG was measured from 25 younger and 25 older normal hearing adults. Age-related and individual differences in P2 response amplitudes, and variability in brain noise, phase locking value (PLV), and spectral power (4–8 Hz) were assessed from electrode FCz. Model testing and linear regression were used to determine the extent to which brain noise, PLV, and spectral power uniquely predicted P2 amplitudes and varied by age group.

Results: Younger adults had significantly larger P2 amplitudes, PLV, and power compared to older adults. Brain noise did not differ between age groups. The results of regression testing revealed that brain noise and PLV, but not spectral power were unique predictors of P2 amplitudes. Model fit was significantly better in younger than in older adults.

Conclusions: ERP analyses are intended to provide a better understanding of the underlying neural mechanisms that contribute to individual and group differences in behavior. The current results support that age-related declines in neural synchrony contribute to smaller P2 amplitudes in older normal hearing adults. Based on our results, we discuss potential models in which differences in neural synchrony and brain noise can account for associations with P2 amplitudes and behavior and potentially provide a better explanation of the neural mechanisms that underlie declines in auditory processing and training benefits.

Keywords: aging; auditory; brain noise; cortical-evoked potentials; electroencephalogram (EEG); P2; phase locking; spectral power

References

  • 1.

    Kuhnis J, Elmer S, Meyer M, Jancke L. Musicianship boosts perceptual learning of pseudoword-chimeras: an electrophysiological approach. Brain Topogr 2013;26:110–25.Web of ScienceCrossrefPubMedGoogle Scholar

  • 2.

    Kuriki S, Ohta K, Koyama S. Persistent responsiveness of long-latency auditory cortical activities in response to repeated stimuli of musical timbre and vowel sounds. Cereb Cortex 2007;17:2725–32.PubMedWeb of ScienceCrossrefGoogle Scholar

  • 3.

    Tremblay K, Kraus N, Carrell TD, McGee T. Central auditory system plasticity: generalization to novel stimuli following listening training. J Acoust Soc Am 1997;102:3762–73.CrossrefPubMedGoogle Scholar

  • 4.

    Tremblay K, Kraus N, McGee T. The time course of auditory perceptual learning: neurophysiological changes during speech-sound training. Neuroreport 1998;9:3557–60.PubMedGoogle Scholar

  • 5.

    Harris KC, Wilson S, Eckert MA, Dubno JR. Human evoked cortical activity to silent gaps in noise: effects of age, attention, and cortical processing speed. Ear Hear 2012;33:330–9.PubMedWeb of ScienceCrossrefGoogle Scholar

  • 6.

    Campbell J, Sharma A. Cross-modal re-organization in adults with early stage hearing loss. PLoS One 2014;9:e90594.Web of SciencePubMedGoogle Scholar

  • 7.

    Tremblay KL, Billings C, Rohila N. Speech evoked cortical potentials: effects of age and stimulus presentation rate. J Am Acad Audiol 2004;15:226–37; quiz 264.CrossrefWeb of ScienceGoogle Scholar

  • 8.

    Harkrider AW, Plyler PN, Hedrick MS. Effects of hearing loss and spectral shaping on identification and neural response patterns of stop-consonant stimuli. J Acoust Soc Am 2006;120:915–25.CrossrefPubMedGoogle Scholar

  • 9.

    Harris KC, Mills JH, Dubno JR. Electrophysiologic correlates of intensity discrimination in cortical evoked potentials of younger and older adults. Hear Res 2007;228:58–68.Web of ScienceGoogle Scholar

  • 10.

    Harris KC, Mills JH, He NJ, Dubno JR. Age-related differences in sensitivity to small changes in frequency assessed with cortical evoked potentials. Hear Res 2008;243:47–56.Web of ScienceGoogle Scholar

  • 11.

    Picton TW, Stuss DT, Champagne SC, Nelson RF. The effects of age on human event-related potentials. Psychophysiology 1984;21:312–25.CrossrefPubMedGoogle Scholar

  • 12.

    Nunez P, Srinivasan R. Electric fields of the brain. The neurophysics of EEG. New York: Oxford University Press, 2006.Google Scholar

  • 13.

    MacDonald SW, Nyberg L, Backman L. Intra-individual variability in behavior: links to brain structure, neurotransmission and neuronal activity. Trends Neurosci 2006;29:474–80.CrossrefPubMedGoogle Scholar

  • 14.

    McIntosh AR, Kovacevic N, Lippe S, Garrett D, Grady C, Jirsa V. The development of a noisy brain. Arch Ital Biol 2010;148:323–37.Google Scholar

  • 15.

    Hammerer D, Li SC, Volkle M, Muller V, Lindenberger U. A lifespan comparison of the reliability, test-retest stability, and signal-to-noise ratio of event-related potentials assessed during performance monitoring. Psychophysiology 2013;50:111–23.Web of ScienceCrossrefPubMedGoogle Scholar

  • 16.

    Winterer G, Ziller M, Dorn H, Frick K, Mulert C, Wuebben Y, et al. Schizophrenia: reduced signal-to-noise ratio and impaired phase-locking during information processing. Clin Neurophysiol 2000;111:837–49.CrossrefPubMedGoogle Scholar

  • 17.

    Zhu L, Bharadwaj H, Xia J, Shinn-Cunningham B. A comparison of spectral magnitude and phase-locking value analyses of the frequency-following response to complex tones. J Acoust Soc Am 2013;134:384–95.Web of ScienceGoogle Scholar

  • 18.

    Zilany MS, Bruce IC, Nelson PC, Carney LH. A phenomenological model of the synapse between the inner hair cell and auditory nerve: long-term adaptation with power-law dynamics. J Acoust Soc Am 2009;126:2390–412.Web of SciencePubMedCrossrefGoogle Scholar

  • 19.

    Ahissar E, Nagarajan S, Ahissar M, Protopapas A, Mahncke H, Merzenich MM. Speech comprehension is correlated with temporal response patterns recorded from auditory cortex. Proc Natl Acad Sci USA 2001;98:13367–72.CrossrefGoogle Scholar

  • 20.

    Clinard CG, Tremblay KL. Aging degrades the neural encoding of simple and complex sounds in the human brainstem. J Am Acad Audiol 2013;24:590–9; quiz 643–4.CrossrefWeb of ScienceGoogle Scholar

  • 21.

    Ruggles D, Bharadwaj H, Shinn-Cunningham BG. Normal hearing is not enough to guarantee robust encoding of suprathreshold features important in everyday communication. Proc Natl Acad Sci USA 2011;108:15516–21.CrossrefGoogle Scholar

  • 22.

    Ruggles D, Bharadwaj H, Shinn-Cunningham BG. Why middle-aged listeners have trouble hearing in everyday settings. Curr Biol 2012;22:1417–22.Web of SciencePubMedCrossrefGoogle Scholar

  • 23.

    Delorme A, Makeig S. EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J Neurosci Methods 2004;134:9–21.Google Scholar

  • 24.

    Delorme A, Sejnowski T, Makeig S. Enhanced detection of artifacts in EEG data using higher-order statistics and independent component analysis. Neuroimage 2007;34:1443–9.Web of ScienceCrossrefPubMedGoogle Scholar

  • 25.

    Frodl T, Meisenzahl EM, Muller D, Leinsinger G, Juckel G, Hahn K, et al. The effect of the skull on event-related P300. Clin Neurophysiol 2001;112:1773–6.Google Scholar

  • 26.

    Picton TW, Taylor MJ. Electrophysiological evaluation of human brain development. Dev Neuropsychol 2007;31:249–78.CrossrefWeb of SciencePubMedGoogle Scholar

  • 27.

    Harkrider AW, Plyler PN, Hedrick MS. Effects of age and spectral shaping on perception and neural representation of stop consonant stimuli. Clin Neurophysiol 2005;116:2153–64.PubMedCrossrefGoogle Scholar

  • 28.

    Charlton RA, Schiavone F, Barrick TR, Morris RG, Markus HS. Diffusion tensor imaging detects age related white matter change over a 2 year follow-up which is associated with working memory decline. J Neurol Neurosurg Psychiatry 2010;81:13–9.CrossrefGoogle Scholar

  • 29.

    Fieremans E, Jensen JH, Helpern JA. White matter characterization with diffusional kurtosis imaging. Neuroimage 2011;58:177–88.Web of SciencePubMedCrossrefGoogle Scholar

  • 30.

    Gunning-Dixon FM, Brickman AM, Cheng JC, Alexopoulos GS. Aging of cerebral white matter: a review of MRI findings. Int J Geriatr Psychiatry 2009;24:109–17.Web of ScienceCrossrefGoogle Scholar

  • 31.

    Helpern JA, Adisetiyo V, Falangola MF, Hu C, Di Martino A, Williams K, et al. Preliminary evidence of altered gray and white matter microstructural development in the frontal lobe of adolescents with attention-deficit hyperactivity disorder: a diffusional kurtosis imaging study. J Magn Reson Imaging 2011;33:17–23.Web of SciencePubMedCrossrefGoogle Scholar

  • 32.

    Tremblay KL, Ross B, Inoue K, McClannahan K, Collet G. Is the auditory evoked P2 response a biomarker of learning? Front Syst Neurosci 2014;8:28.Google Scholar

  • 33.

    Golestani N, Molko N, Dehaene S, LeBihan D, Pallier C. Brain structure predicts the learning of foreign speech sounds. Cereb Cortex 2007;17:575–82.PubMedWeb of ScienceGoogle Scholar

  • 34.

    Zatorre RJ, Fields RD, Johansen-Berg H. Plasticity in gray and white: neuroimaging changes in brain structure during learning. Nat Neurosci 2012;15:528–36.PubMedWeb of ScienceCrossrefGoogle Scholar

  • 35.

    Zatorre RJ, Krumhansl CL. Neuroscience. Mental models and musical minds. Science 2002;298:2138–9.Google Scholar

  • 36.

    Tremblay KL, Shahin AJ, Picton T, Ross B. Auditory training alters the physiological detection of stimulus-specific cues in humans. Clin Neurophysiol 2009;120:128–35.Web of ScienceGoogle Scholar

  • 37.

    Tremblay KL, Piskosz M, Souza P. Effects of age and age-related hearing loss on the neural representation of speech cues. Clin Neurophysiol 2003;114:1332–43.PubMedCrossrefGoogle Scholar

  • 38.

    Yang H, Xiong H, Yu R, Wang C, Zheng Y, Zhang X. The characteristic and changes of the event-related potentials (ERP) and brain topographic maps before and after treatment with rTMS in subjective tinnitus patients. PLoS One 2013;8:e70831.Web of SciencePubMedGoogle Scholar

  • 39.

    Zhong Z, Henry KS, Heinz MG. Sensorineural hearing loss amplifies neural coding of envelope information in the central auditory system of chinchillas. Hear Res 2014; 309:55–62.Web of ScienceGoogle Scholar

  • 40.

    Chen GD, Stolzberg D, Lobarinas E, Sun W, Ding D, Salvi R. Salicylate-induced cochlear impairments, cortical hyperactivity and re-tuning, and tinnitus. Hear Res 2013;295:100–13.Web of ScienceGoogle Scholar

  • 41.

    Llano DA, Turner J, Caspary DM. Diminished cortical inhibition in an aging mouse model of chronic tinnitus. J Neurosci 2012;32:16141–8.CrossrefGoogle Scholar

About the article

Corresponding author: Kelly C. Harris, Department of Otolaryngology – Head and Neck Surgery, Medical University of South Carolina, 135 Rutledge Ave MSC550 Charleston, SC 29425, USA, Phone: +843-792-7977, Fax: +843-792-7736, E-mail:


Received: 2014-04-15

Accepted: 2014-05-23

Published Online: 2014-07-19

Published in Print: 2014-09-01


Citation Information: Journal of Basic and Clinical Physiology and Pharmacology, ISSN (Online) 2191-0286, ISSN (Print) 0792-6855, DOI: https://doi.org/10.1515/jbcpp-2014-0047.

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