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Record W2100983956 · doi:10.1093/cercor/bhm045

Age-Related Differences in Brain Activity Underlying Working Memory for Spatial and Nonspatial Auditory Information

2007· article· en· W2100983956 on OpenAlexaff
He Yu, Claude Alain

Bibliographic record

VenueCerebral Cortex · 2007
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsBaycrest HospitalUniversity of Toronto
Fundersnot available
KeywordsWorking memoryPsychologyNeuroscienceCognitive psychologySpatial memoryBrain activity and meditationAuditory perceptionAudiologyCognitionPerceptionElectroencephalographyMedicine

Abstract

fetched live from OpenAlex

We used functional magnetic resonance imaging and a 1-back task to assess working memory (WM) for spatial (sound location) and nonspatial (sound category) auditory information in younger and older adults. A mixed block-event-related design was used to measure sustained activity during each task block and transient activity to targets (repetitions of location or category). In both groups, there was increased sustained activity for category WM in left anterior temporal cortex and inferior prefrontal cortex (PFC) and increased activity for location WM in right inferior parietal cortex and dorsal PFC. There were no reliable age differences in this pattern of activity. Older adults had more sustained activity than younger adults in left PFC during both tasks, suggesting that additional PFC recruitment in older adults reflects nonspecific engagement of frontally mediated task-monitoring processes. Both groups showed lower transient than sustained activity in auditory cortex bilaterally; however, older adults showed smaller target-related reductions of activity during the category task. A greater reduction of activity to category targets in left auditory cortex was associated with better performance on this task in older adults, suggesting that a failure to modulate activity appropriately when a stimulus is repeated, or when a particular feature of the stimulus is repeated, could lead to reduced ability to detect this repetition.

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 score0.888
Threshold uncertainty score0.546

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 head0.137
GPT teacher head0.352
Teacher spread0.215 · 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

Citations90
Published2007
Admission routes1
Has abstractyes

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