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Record W2139338873 · doi:10.1093/cercor/bhj175

Sequential Auditory Scene Analysis Is Preserved in Normal Aging Adults

2006· article· en· W2139338873 on OpenAlexaff
Jason S. Snyder, Claude Alain

Bibliographic record

VenueCerebral Cortex · 2006
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsUniversity of TorontoBaycrest Hospital
Fundersnot available
KeywordsPsychologyAuditory scene analysisAudiologyCognitive psychologyNeuroscienceCommunicationPerceptionMedicine

Abstract

fetched live from OpenAlex

Normal aging is accompanied by speech perception difficulties, especially in adverse listening situations such as a cocktail party. To assess whether such difficulties might be related to impairments in sequential auditory scene analysis, event-related brain potentials were recorded from normal-hearing young, middle-aged, and older adults during presentation of low (A) tones, high (B) tones, and silences (--) in repeating 3 tone triplets (ABA--). The likelihood of reporting hearing 2 streams increased as a function of the frequency difference between A and B tones (Delta f) to the same extent for all 3 age groups and was paralleled by enhanced sensory-evoked responses over the frontocentral scalp regions. In all 3 age groups, there was also a progressive buildup in brain activity from the beginning to the end of the sequence of triplets, which was characterized by an enhanced positivity that peaked at about 200 ms after the onset of each ABA--triplet. Similar Delta f- and buildup-related activity also occurred over the right temporal cortex, but only for young adults. We conclude that age-related difficulties in separating competing speakers are unlikely to arise from deficits in streaming and might instead reflect less efficient concurrent sound segregation.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.888
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.266
Teacher spread0.242 · 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.

Study designBench or experimental
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

Citations57
Published2006
Admission routes1
Has abstractyes

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