Functional near infrared spectroscopy activation during an executive function task differs between healthy older and younger adults
Bibliographic record
Abstract
Background: Healthy aging can include declines in processing speed and executive function. Further research is needed to characterize the neurobiological underpinnings of these cognitive changes in older adulthood. The current study used functional near infrared spectroscopy (fNIRS), an optical neuroimaging technique, to examine differences in cerebral oxygenation between healthy older adults (OA) and younger adults (YA) during a measure of cognitive interference. Methods: Thirty-four participants were sampled from two age groups: YA (mean age = 28.1 years, SD = 2.8, F = 9) and OA (mean age = 70.9 years, SD = 5.4, F = 9). Participants completed the Multi-Source Interference Task (MSIT), a measure of executive function with high and low-demand conditions, while undergoing fNIRS recordings using a TechEn CW6 system with 34-source-detector channels, situated over the prefrontal cortex. Functional activation patterns, accuracy, and reaction time were compared between and within groups for each condition. Results: Behaviourally, during the control condition, OA and YA had comparable accuracy, although OA had significantly slower reaction times than YA. During the interference condition, OA had significantly lower accuracy and slower reaction times than YA. Results demonstrated a significant difference between groups with an age-related increase in HbO for OA in both conditions (p < 0.05). Within groups, OA showed greater activation during the control condition, while YA demonstrated greater activation during the interference condition. Conclusions: The findings suggest that OA recruit additional neural resources to achieve similar behavioural performance during low-level cognitive interference, but that compensation in OA may be insufficient to support behavioural performance at higher levels of interference.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".