| Title |
Assessing the Role of Place and Timing Cues in Coding Frequency and Amplitude Modulation as a Function of Age
|
|---|---|
| Published in |
Journal of the Association for Research in Otolaryngology, April 2017
|
| DOI | 10.1007/s10162-017-0624-x |
| Pubmed ID | |
| Authors |
Kelly L. Whiteford, Heather A. Kreft, Andrew J. Oxenham |
| Abstract |
Natural sounds can be characterized by their fluctuations in amplitude and frequency. Ageing may affect sensitivity to some forms of fluctuations more than others. The present study used individual differences across a wide age range (20-79 years) to test the hypothesis that slow-rate, low-carrier frequency modulation (FM) is coded by phase-locked auditory-nerve responses to temporal fine structure (TFS), whereas fast-rate FM is coded via rate-place (tonotopic) cues, based on amplitude modulation (AM) of the temporal envelope after cochlear filtering. Using a low (500 Hz) carrier frequency, diotic FM and AM detection thresholds were measured at slow (1 Hz) and fast (20 Hz) rates in 85 listeners. Frequency selectivity and TFS coding were assessed using forward masking patterns and interaural phase disparity tasks (slow dichotic FM), respectively. Comparable interaural level disparity tasks (slow and fast dichotic AM and fast dichotic FM) were measured to control for effects of binaural processing not specifically related to TFS coding. Thresholds in FM and AM tasks were correlated, even across tasks thought to use separate peripheral codes. Age was correlated with slow and fast FM thresholds in both diotic and dichotic conditions. The relationship between age and AM thresholds was generally not significant. Once accounting for AM sensitivity, only diotic slow-rate FM thresholds remained significantly correlated with age. Overall, results indicate stronger effects of age on FM than AM. However, because of similar effects for both slow and fast FM when not accounting for AM sensitivity, the effects cannot be unambiguously ascribed to TFS coding. |
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 30 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 10 | 33% |
| Student > Ph. D. Student | 4 | 13% |
| Student > Doctoral Student | 3 | 10% |
| Other | 2 | 7% |
| Professor | 1 | 3% |
| Other | 2 | 7% |
| Unknown | 8 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 6 | 20% |
| Psychology | 5 | 17% |
| Engineering | 4 | 13% |
| Agricultural and Biological Sciences | 2 | 7% |
| Nursing and Health Professions | 2 | 7% |
| Other | 2 | 7% |
| Unknown | 9 | 30% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 August 2017.
All research outputs
#21,186,729
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Outputs from Journal of the Association for Research in Otolaryngology
#380
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Outputs of similar age
#272,208
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Outputs of similar age from Journal of the Association for Research in Otolaryngology
#6
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