Literature DB >> 30456729

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

James W Dias1, Carolyn M McClaskey2, Kelly C Harris2.   

Abstract

Older adults typically have difficulty identifying speech that is temporally distorted, such as reverberant, accented, time-compressed, or interrupted speech. These difficulties occur even when hearing thresholds fall within a normal range. Auditory neural processing speed, which we have previously found to predict auditory temporal processing (auditory gap detection), may interfere with the ability to recognize phonetic features as they rapidly unfold over time in spoken speech. Further, declines in perceptuomotor processing speed and executive functioning may interfere with the ability to track, access, and process information. The current investigation examined the extent to which age-related differences in time-compressed speech identification were predicted by auditory neural processing speed, perceptuomotor processing speed, and executive functioning. Groups of normal-hearing (up to 3000 Hz) younger and older adults identified 40, 50, and 60 % time-compressed sentences. Auditory neural processing speed was defined as the P1 and N1 latencies of click-induced auditory-evoked potentials. Perceptuomotor processing speed and executive functioning were measured behaviorally using the Connections Test. Compared to younger adults, older adults exhibited poorer time-compressed speech identification and slower perceptuomotor processing. Executive functioning, P1 latency, and N1 latency did not differ between age groups. Time-compressed speech identification was independently predicted by P1 latency, perceptuomotor processing speed, and executive functioning in younger and older listeners. Results of model testing suggested that declines in perceptuomotor processing speed mediated age-group differences in time-compressed speech identification. The current investigation joins a growing body of literature suggesting that the processing of temporally distorted speech is impacted by lower-level auditory neural processing and higher-level perceptuomotor and executive processes.

Entities:  

Keywords:  N1; P1; auditory temporal processing; connections test; executive functioning; perceptuomotor; time-compressed speech

Mesh:

Year:  2018        PMID: 30456729      PMCID: PMC6364265          DOI: 10.1007/s10162-018-00703-1

Source DB:  PubMed          Journal:  J Assoc Res Otolaryngol        ISSN: 1438-7573


  70 in total

1.  Effects of stimulus and noise rate variability on speech perception by younger and older adults.

Authors:  Sandra Gordon-Salant; Peter J Fitzgibbons
Journal:  J Acoust Soc Am       Date:  2004-04       Impact factor: 1.840

2.  Processing of fast speech by elderly listeners.

Authors:  Esther Janse
Journal:  J Acoust Soc Am       Date:  2009-04       Impact factor: 1.840

3.  Relations between cognitive abilities and measures of executive functioning.

Authors:  Timothy A Salthouse
Journal:  Neuropsychology       Date:  2005-07       Impact factor: 3.295

4.  Auditory and auditory-visual recognition of clear and conversational speech by older adults.

Authors:  K S Helfer
Journal:  J Am Acad Audiol       Date:  1998-06       Impact factor: 1.664

5.  Age-related deficits in auditory temporal processing: unique contributions of neural dyssynchrony and slowed neuronal processing.

Authors:  Kelly C Harris; Judy R Dubno
Journal:  Neurobiol Aging       Date:  2017-01-16       Impact factor: 4.673

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

Authors:  Samira Anderson; Alexandra Parbery-Clark; Han-Gyol Yi; Nina Kraus
Journal:  Ear Hear       Date:  2011 Nov-Dec       Impact factor: 3.570

Review 7.  Auditory neuropathy/dys-synchrony and its perceptual consequences.

Authors:  Gary Rance
Journal:  Trends Amplif       Date:  2005

8.  Temporal envelope of time-compressed speech represented in the human auditory cortex.

Authors:  Kirill V Nourski; Richard A Reale; Hiroyuki Oya; Hiroto Kawasaki; Christopher K Kovach; Haiming Chen; Matthew A Howard; John F Brugge
Journal:  J Neurosci       Date:  2009-12-09       Impact factor: 6.167

9.  Effects of age and age-related hearing loss on the neural representation of speech cues.

Authors:  Kelly L Tremblay; Michael Piskosz; Pamela Souza
Journal:  Clin Neurophysiol       Date:  2003-07       Impact factor: 3.708

10.  Temporal factors and speech recognition performance in young and elderly listeners.

Authors:  S Gordon-Salant; P J Fitzgibbons
Journal:  J Speech Hear Res       Date:  1993-12
View more
  10 in total

1.  Effects of aging and hearing loss on perceptual and electrophysiological measures of pulse-rate discrimination.

Authors:  Lindsay DeVries; Samira Anderson; Matthew J Goupell; Ed Smith; Sandra Gordon-Salant
Journal:  J Acoust Soc Am       Date:  2022-03       Impact factor: 1.840

2.  Afferent loss, GABA, and Central Gain in older adults: Associations with speech recognition in noise.

Authors:  Kelly C Harris; James W Dias; Carolyn M McClaskey; Jeffrey Rumschlag; James Prisciandaro; Judy R Dubno
Journal:  J Neurosci       Date:  2022-08-19       Impact factor: 6.709

3.  Early auditory cortical processing predicts auditory speech in noise identification and lipreading.

Authors:  James W Dias; Carolyn M McClaskey; Kelly C Harris
Journal:  Neuropsychologia       Date:  2021-08-30       Impact factor: 3.054

4.  The Intelligibility of Time-Compressed Speech Is Correlated with the Ability to Listen in Modulated Noise.

Authors:  Robin Gransier; Astrid van Wieringen; Jan Wouters
Journal:  J Assoc Res Otolaryngol       Date:  2022-03-07

5.  Neural Presbyacusis in Humans Inferred from Age-Related Differences in Auditory Nerve Function and Structure.

Authors:  Kelly C Harris; Jayne B Ahlstrom; James W Dias; Lilyana B Kerouac; Carolyn M McClaskey; Judy R Dubno; Mark A Eckert
Journal:  J Neurosci       Date:  2021-11-09       Impact factor: 6.709

6.  Age-related central gain with degraded neural synchrony in the auditory brainstem of mice and humans.

Authors:  Jeffrey A Rumschlag; Carolyn M McClaskey; James W Dias; Lilyana B Kerouac; Kenyaria V Noble; Clarisse Panganiban; Hainan Lang; Kelly C Harris
Journal:  Neurobiol Aging       Date:  2022-03-25       Impact factor: 5.133

Review 7.  Improving older adults' understanding of challenging speech: Auditory training, rapid adaptation and perceptual learning.

Authors:  Rebecca E Bieber; Sandra Gordon-Salant
Journal:  Hear Res       Date:  2020-08-07       Impact factor: 3.208

8.  Intra- and interhemispheric white matter tract associations with auditory spatial processing: Distinct normative and aging effects.

Authors:  James W Dias; Carolyn M McClaskey; Mark A Eckert; Jens H Jensen; Kelly C Harris
Journal:  Neuroimage       Date:  2020-04-09       Impact factor: 6.556

9.  Speech Perception in Older Adults: An Interplay of Hearing, Cognition, and Learning?

Authors:  Liat Shechter Shvartzman; Limor Lavie; Karen Banai
Journal:  Front Psychol       Date:  2022-02-17

10.  The recognition of time-compressed speech as a function of age in listeners with cochlear implants or normal hearing.

Authors:  Anna R Tinnemore; Lauren Montero; Sandra Gordon-Salant; Matthew J Goupell
Journal:  Front Aging Neurosci       Date:  2022-09-29       Impact factor: 5.702

  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.