MétaCan
Menu
Back to cohort
Record W4210307866 · doi:10.1002/alz.057447

Differences in cerebral oxygenation between healthy older and younger adults during the Multi‐Source Interference Task

2021· article· en· W4210307866 on OpenAlexaff
Heather Kwan, Vanessa Scarapicchia, Drew Halliday, Stuart MacDonald, Jodie R. Gawryluk

Bibliographic record

VenueAlzheimer s & Dementia · 2021
Typearticle
Languageen
FieldMedicine
TopicOptical Imaging and Spectroscopy Techniques
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsFunctional near-infrared spectroscopyCognitionAudiologyOxygenationEffects of sleep deprivation on cognitive performanceFunctional neuroimagingPsychologyNeuroimagingMedicinePhysical medicine and rehabilitationNeuroscienceInternal medicinePrefrontal cortex

Abstract

fetched live from OpenAlex

Abstract Background Cognitive changes that accompany normal aging 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), a neuroimaging technique that measures oxygenated hemoglobin (HbO), to examine differences in cerebral oxygenation between healthy younger adults (YA) and older adults (OA) during a measure of cognitive interference. Method There were 34 participants sampled from two age group: YA (Mean age =28.1 years, SD=2.8, F=9) and OA (Mean age =70.9 years, SD=5.4, F=9). All participants were native English speakers, neurologically healthy, and had normal or corrected to normal vision. Participants completed the Multi‐Source Interference Task, a measure of cognitive interference with high and low‐demand conditions, while undergoing fNIRS recordings by a TechEn CW6 system with 34‐source‐detector channels over the PFC. The functional activation patterns, accuracy, and reaction time were compared between groups for each condition. Result The functional results demonstrated a significant age‐related increase in HbO for OA in both conditions (p < 0.05). In the control condition, OA demonstrated increased HbO in 10 channels covering the left and mid‐anterior PFC in comparison to YA. In the interference condition, OA demonstrated increased HbO in 6 channels covering the mid‐anterior PFC in comparison to YA. During the control condition, OA and YA had the same accuracy (YA Mean= 0.99, OA Mean= 0.99, p>0.33), but OA were significantly slower (YA Mean= 545.63, OA Mean= 768.04, p<0.0001). During the interference condition, OA had lower accuracy (YA Mean=0.97, OA Mean=0.9, p< 0.0001) and were significantly slower (YA Mean=891.31, OA Mean=1114.5, p< 0.0001) than YA. Conclusion The results from this study show that OA require greater activation in mid‐PFC regions, across both low and high‐demand conditions, relative to YA. These results are consistent with cognitive aging theories such as the compensation‐related utilization of neural circuits hypothesis (CRUNCH). Specifically, the findings suggest that OA recruit additional neural resources to achieve similar behavioural performance during low‐levels of cognitive interference, but that this same compensation may be insufficient to support behavioural performance at higher levels of interference.

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 score0.002
Threshold uncertainty score0.004

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 communication0.0000.000
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 head0.023
GPT teacher head0.296
Teacher spread0.273 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueAlzheimer s & DementiaSame topicOptical Imaging and Spectroscopy TechniquesFrench-language works237,207