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Record W4232603341 · doi:10.32920/ryerson.14651655

The Interactions Between Cognitive Control, Aging, and Emotion

2021· preprint· en· W4232603341 on OpenAlexaff
Linda Truong

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicAging and Gerontology Research
Canadian institutionsToronto Metropolitan UniversityUniversity of Toronto
Fundersnot available
KeywordsSocioemotional selectivity theoryPsychologyMoodCognitionAffect (linguistics)Developmental psychologyCognitive resource theoryYoung adultTask (project management)Control (management)Cognitive psychologyClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

The dual mechanisms of control framework proposes that age-related declines in cognitive control are due to deficits with continuous goal maintenance (proactive control). Older adults default instead to another form of control (reactive control). In contrast to these declines, older adults demonstrate preserved emotional processing. According to the socioemotional selectivity theory, perceived time constraints related to advancing age results in emotional regulation goals in which older adults prioritize positive well-being or mood. To achieve this, they devote more cognitive resources and pay greater attention to positive versus negative information (“positivity effects”) than younger adults. Research on the interactions between cognitive control and emotion is increasing but work focused on the interactions in older adults is limited. Thus, it is unknown how older adults' emotional goals may influence their goal maintenance deficits. This study manipulated mood and emotional face stimuli to examine whether these factors affect age differences in cognitive control between younger (ages 18-30) and older adults (ages 65+). Experiment 1 induced neutral or negative moods prior to a cognitive control task (the standard letter AX-CPT task). Results indicated typical patterns of proactive control in younger adults and reactive control in older adults that did not vary substantially by mood. Experiment 2 examined the effects of neutral, negative, and positive mood inductions on a less cognitively demanding version of the AX-CPT (with face cues as contextual information). Results showed evidence of enhanced proactive control in older adults that was comparable to that of younger adults across all mood conditions, although this was limited to response time data. Additionally, there was evidence of small mood effects on cognitive control. Finally, Experiment 3 examined the effect of positive, negative, and neutral contextual information (face cues) on older adults' cognitive control performance using a different variant of the AX-CPT (face AX-CPT). Results indicated strong engagement in reactive control that did not vary by the emotionality of the contextual information. Together, the results of this study suggest that older adults’ proactive control patterns are affected by the task demands of the AX-CPT, but there is less evidence of mood or emotional stimuli effects.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.072
GPT teacher head0.431
Teacher spread0.360 · 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 source (direct Gemma or distilled Codex), 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

Citations2
Published2021
Admission routes1
Has abstractyes

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