The Effect of Cue Manipulations on Cognitive Control in Young and Older Adults
Bibliographic record
Abstract
Cognitive control requires both active maintenance of goal-relevant information over time and continuous adaptation to interference to regulate thoughts and behaviours to achieve a goal. According to the Dual Mechanisms of Control framework, there are two cognitive control modes: proactive (cue-focused) and reactive (probe-focused). With aging, there is a shift from proactive to reactive control from young adulthood into older age. A recent study from our lab found that when using a modified AX-CPT, male-female face cues were effective for improving older adults’ proactive control use to levels similar to that of younger adults (Truong, 2015). To determine the critical manipulation underlying this discovery, the present thesis project included two experiments testing both young (18-29 years) and older (65+ years) adults. In both experiments, baseline cognitive control performance was tested with a standard AX-Continuous Performance Task (AX-CPT), along with a modified cue salient version of the AX-CPT. The modified task adopted a dichotomous cue option (O and Z) in Experiment 1 and distinctive colour-coded cues and probes in Experiment 2 to enhance the cue salience and determine, using a bottom-up approach, what basic cue characteristics facilitated the observed proactive control shifts in Truong (2015). Both experiments were expected to improve older adults’ cue-focused proactive control use and thus ameliorate age differences in cognitive control performance. The results supported previous literature showing an age-related shift from proactive to reactive control mode use, but neither dichotomous letter cues nor distinctly coloured letter cues and probes were sufficient for inducing a proactive control bias in the older adult sample. When collapsing across age, the Dichotomous AX-CPT counterintuitively reduced participants’ reliance on proactive control strategies, which lead to a reactive control bias. These results contribute solid evidence to the growing literature on cognitive control mode use that cue dichotomization and cue-probe distinction alone are insufficient for ameliorating age differences in cognitive control performance in a modified AX-CPT. These findings also highlight the unique role of Truong’s (2015) male-female face cues for inducing greater proactive control use in older adults and encourages further investigation into the specific mechanisms that facilitated this shift.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".