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Record W2518614174 · doi:10.1097/aud.0000000000000324

Human Envelope Following Responses to Amplitude Modulation: Effects of Aging and Modulation Depth

2016· article· en· W2518614174 on OpenAlexaff
Andrew Dimitrijevic, Jamal Alsamri, M. Sasha John, David W. Purcell, Sahara E. George, Fan‐Gang Zeng

Bibliographic record

VenueEar and Hearing · 2016
Typearticle
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsBaycrest HospitalHealth Sciences CentreUniversity of TorontoSunnybrook Health Science CentreWestern University
FundersNational Institute on Deafness and Other Communication Disorders
KeywordsAudiologyMonauralAmplitude modulationElectrophysiologyEnvelope (radar)PsychophysicsAmplitudeNoise (video)Modulation (music)PsychologyTwo-alternative forced choiceMathematicsFrequency modulationMedicineStatisticsPhysicsTelecommunicationsAcousticsOpticsNeurosciencePerceptionComputer science

Abstract

fetched live from OpenAlex

OBJECTIVE: To record envelope following responses (EFRs) to monaural amplitude-modulated broadband noise carriers in which amplitude modulation (AM) depth was slowly changed over time and to compare these objective electrophysiological measures to subjective behavioral thresholds in young normal hearing and older subjects. PARTICIPANTS: three groups of subjects included a young normal-hearing group (YNH 18 to 28 years; pure-tone average = 5 dB HL), a first older group ("O1"; 41 to 62 years; pure-tone average = 19 dB HL), and a second older group ("O2"; 67 to 82 years; pure-tone average = 35 dB HL). Electrophysiology: In condition 1, the AM depth (41 Hz) of a white noise carrier, was continuously varied from 2% to 100% (5%/s). EFRs were analyzed as a function of the AM depth. In condition 2, auditory steady-state responses were recorded to fixed AM depths (100%, 75%, 50%, and 25%) at a rate of 41 Hz. Psychophysics: A 3 AFC (alternative forced choice) procedure was used to track the AM depth needed to detect AM at 41 Hz (AM detection). The minimum AM depth capable of eliciting a statistically detectable EFR was defined as the physiological AM detection threshold. RESULTS: Across all ages, the fixed AM depth auditory steady-state response and swept AM EFR yielded similar response amplitudes. Statistically significant correlations (r = 0.48) were observed between behavioral and physiological AM detection thresholds. Older subjects had slightly higher (not significant) behavioral AM detection thresholds than younger subjects. AM detection thresholds did not correlate with age. All groups showed a sigmoidal EFR amplitude versus AM depth function but the shape of the function differed across groups. The O2 group reached EFR amplitude plateau levels at lower modulation depths than the normal-hearing group and had a narrower neural dynamic range. In the young normal-hearing group, the EFR phase did not differ with AM depth, whereas in the older group, EFR phase showed a consistent decrease with increasing AM depth. The degree of phase change (or phase slope) was significantly correlated to the pure-tone threshold at 4 kHz. CONCLUSIONS: EFRs can be recorded using either the swept modulation depth or the discrete AM depth techniques. Sweep recordings may provide additional valuable information at suprathreshold intensities including the plateau level, slope, and dynamic range. Older subjects had a reduced neural dynamic range compared with younger subjects suggesting that aging affects the ability of the auditory system to encode subtle differences in the depth of AM. The phase-slope differences are likely related to differences in low and high-frequency contributions to EFR. The behavioral-physiological AM depth threshold relationship was significant but likely too weak to be clinically useful in the present individual subjects who did not suffer from apparent temporal processing deficits.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.844
Threshold uncertainty score0.203

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.041
GPT teacher head0.317
Teacher spread0.277 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations46
Published2016
Admission routes1
Has abstractyes

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