Literature DB >> 21730859

A neural basis of speech-in-noise perception in older adults.

Samira Anderson1, Alexandra Parbery-Clark, Han-Gyol Yi, Nina Kraus.   

Abstract

OBJECTIVE: We investigated a neural basis of speech-in-noise perception in older adults. Hearing loss, the third most common chronic condition in older adults, is most often manifested by difficulty understanding speech in background noise. This trouble with understanding speech in noise, which occurs even in individuals who have normal-hearing thresholds, may arise, in part, from age-related declines in central auditory processing of the temporal and spectral components of speech. We hypothesized that older adults with poorer speech-in-noise (SIN) perception demonstrate impairments in the subcortical representation of speech.
DESIGN: In all participants (28 adults, age 60-73 yr), average hearing thresholds calculated from 500 to 4000 Hz were ≤ 25 dB HL. The participants were evaluated behaviorally with the Hearing in Noise Test (HINT) and neurophysiologically using speech-evoked auditory brainstem responses recorded in quiet and in background noise. The participants were divided based on their HINT scores into top and bottom performing groups that were matched for audiometric thresholds and intelligent quotient. We compared brainstem responses in the two groups, specifically, the average spectral magnitudes of the neural response and the degree to which background noise affected response morphology.
RESULTS: In the quiet condition, the bottom SIN group had reduced neural representation of the fundamental frequency of the speech stimulus and an overall reduction in response magnitude. In the noise condition, the bottom SIN group demonstrated greater disruption in noise, reflecting reduction in neural synchrony. The role of brainstem timing is particularly evident in the strong relationship between SIN perception and quiet-to-noise response correlations. All physiologic measures correlated with SIN perception.
CONCLUSION: Adults in the bottom SIN group differed from the audiometrically matched top SIN group in how speech was neurally encoded. The strength of subcortical encoding of the fundamental frequency appears to be a factor in successful speech-in-noise perception in older adults. Given the limitations of amplification, our results suggest the need for inclusion of auditory training to strengthen central auditory processing in older adults with SIN perception difficulties.

Entities:  

Mesh:

Year:  2011        PMID: 21730859      PMCID: PMC3189261          DOI: 10.1097/AUD.0b013e31822229d3

Source DB:  PubMed          Journal:  Ear Hear        ISSN: 0196-0202            Impact factor:   3.570


  53 in total

1.  GABAergic inhibition shapes frequency tuning and modifies response properties in the auditory midbrain of the leopard frog.

Authors:  J C Hall
Journal:  J Comp Physiol A       Date:  1999-11       Impact factor: 1.836

2.  Central auditory plasticity: changes in the N1-P2 complex after speech-sound training.

Authors:  K Tremblay; N Kraus; T McGee; C Ponton; B Otis
Journal:  Ear Hear       Date:  2001-04       Impact factor: 3.570

3.  Auditory training induces asymmetrical changes in cortical neural activity.

Authors:  Kelly L Tremblay; Nina Kraus
Journal:  J Speech Lang Hear Res       Date:  2002-06       Impact factor: 2.297

4.  Aging alters the neural representation of speech cues.

Authors:  Kelly L Tremblay; Michael Piskosz; Pamela Souza
Journal:  Neuroreport       Date:  2002-10-28       Impact factor: 1.837

5.  Distraction by competing speech in young and older adult listeners.

Authors:  Patricia A Tun; Gail O'Kane; Arthur Wingfield
Journal:  Psychol Aging       Date:  2002-09

6.  Musical experience limits the degradative effects of background noise on the neural processing of sound.

Authors:  Alexandra Parbery-Clark; Erika Skoe; Nina Kraus
Journal:  J Neurosci       Date:  2009-11-11       Impact factor: 6.167

7.  Neural timing is linked to speech perception in noise.

Authors:  Samira Anderson; Erika Skoe; Bharath Chandrasekaran; Nina Kraus
Journal:  J Neurosci       Date:  2010-04-07       Impact factor: 6.167

8.  Subcortical differentiation of stop consonants relates to reading and speech-in-noise perception.

Authors:  Jane Hornickel; Erika Skoe; Trent Nicol; Steven Zecker; Nina Kraus
Journal:  Proc Natl Acad Sci U S A       Date:  2009-07-17       Impact factor: 11.205

9.  Speech recognition and temporal processing in middle-aged women.

Authors:  Karen S Helfer; Megan Vargo
Journal:  J Am Acad Audiol       Date:  2009-04       Impact factor: 1.664

10.  Context-dependent encoding in the human auditory brainstem relates to hearing speech in noise: implications for developmental dyslexia.

Authors:  Bharath Chandrasekaran; Jane Hornickel; Erika Skoe; Trent Nicol; Nina Kraus
Journal:  Neuron       Date:  2009-11-12       Impact factor: 17.173

View more
  66 in total

1.  A comparison of spectral magnitude and phase-locking value analyses of the frequency-following response to complex tones.

Authors:  Li Zhu; Hari Bharadwaj; Jing Xia; Barbara Shinn-Cunningham
Journal:  J Acoust Soc Am       Date:  2013-07       Impact factor: 1.840

2.  Masking Differentially Affects Envelope-following Responses in Young and Aged Animals.

Authors:  Jesyin Lai; Edward L Bartlett
Journal:  Neuroscience       Date:  2018-06-25       Impact factor: 3.590

3.  Training to improve hearing speech in noise: biological mechanisms.

Authors:  Judy H Song; Erika Skoe; Karen Banai; Nina Kraus
Journal:  Cereb Cortex       Date:  2011-07-28       Impact factor: 5.357

4.  Evidence for enhanced neural tracking of the speech envelope underlying age-related speech-in-noise difficulties.

Authors:  Lien Decruy; Jonas Vanthornhout; Tom Francart
Journal:  J Neurophysiol       Date:  2019-05-29       Impact factor: 2.714

5.  Functional Interplay Between the Putative Measures of Rostral and Caudal Efferent Regulation of Speech Perception in Noise.

Authors:  Sandeep Maruthy; U Ajith Kumar; G Nike Gnanateja
Journal:  J Assoc Res Otolaryngol       Date:  2017-04-26

Review 6.  The Physiologic and Psychophysical Consequences of Severe-to-Profound Hearing Loss.

Authors:  Pamela Souza; Eric Hoover
Journal:  Semin Hear       Date:  2018-10-26

7.  Time-Compressed Speech Identification Is Predicted by Auditory Neural Processing, Perceptuomotor Speed, and Executive Functioning in Younger and Older Listeners.

Authors:  James W Dias; Carolyn M McClaskey; Kelly C Harris
Journal:  J Assoc Res Otolaryngol       Date:  2018-11-19

8.  Brainstem Evoked Potential Indices of Subcortical Auditory Processing After Mild Traumatic Brain Injury.

Authors:  Kathy R Vander Werff; Brian Rieger
Journal:  Ear Hear       Date:  2017 Jul/Aug       Impact factor: 3.570

9.  A dynamic auditory-cognitive system supports speech-in-noise perception in older adults.

Authors:  Samira Anderson; Travis White-Schwoch; Alexandra Parbery-Clark; Nina Kraus
Journal:  Hear Res       Date:  2013-03-27       Impact factor: 3.208

10.  Linking anatomical and physiological markers of auditory system degeneration with behavioral hearing assessments in a mouse (Mus musculus) model of age-related hearing loss.

Authors:  Anastasiya Kobrina; Katrina M Schrode; Laurel A Screven; Hamad Javaid; Madison M Weinberg; Garrett Brown; Ryleigh Board; Dillan F Villavisanis; Micheal L Dent; Amanda M Lauer
Journal:  Neurobiol Aging       Date:  2020-08-26       Impact factor: 4.673

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.