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Record W4390192481 · doi:10.1002/alz.076961

An 8‐week program of computerized cognitive training with exercise impacts cortical grey matter in older adults: Secondary findings of a randomized controlled trial

2023· article· en· W4390192481 on OpenAlexaffabout
Ryan G Stein, Lisanne F. ten Brinke, Nárlon Cássio Boa Sorte Silva, Todd C. Handy, Ging‐Yuek Robin Hsiung, Teresa Liu‐Ambrose

Bibliographic record

VenueAlzheimer s & Dementia · 2023
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsCenter for Diagnosis and Research on Alzheimer's DiseaseVancouver Coastal Health Research InstituteUniversity of British ColumbiaVancouver Coastal Health
Fundersnot available
KeywordsMontreal Cognitive AssessmentCognitionRandomized controlled trialCognitive declineMedicineBrain Structure and FunctionEffects of sleep deprivation on cognitive performancePhysical therapyLingual gyrusGrey matterPsychologyCognitive reservePhysical medicine and rehabilitationMagnetic resonance imagingInternal medicineNeuroscienceCognitive impairmentWhite matterDementiaRadiology

Abstract

fetched live from OpenAlex

Abstract Background The world’s population is aging and thus, it is important that we find strategies to reduce the rate of age‐related cognitive decline. Lifestyle interventions can play an important role in delaying the onset of cognitive decline. Evidence shows both computerized cognitive training (CCT) or exercise can improve cognitive function. However, the effect of CCT on cortical structure is not well understood. This study examines the effect of 8‐weeks of CCT, with or without a preceding exercise bout, on cortical structure in community‐dwelling older adults. Method Structural magnetic resonance imaging (MRI) data acquired from an 8‐week, 3‐arm, proof of concept randomized controlled trial was used. Participants (N = 125) aged 65 – 85 were randomized (1:1:1) to either 8 weeks of 3x/week: 1) Balance and Toned (BAT; active control); 2) CCT; or 3) Exercise + CCT (Ex‐CCT). Measurement occurred at baseline and trial completion (i.e., 8‐weeks). Fifty‐three participants with baseline and trial completion MRI data were included in this analysis. Freesurfer was used to assess BAT vs. CCT, BAT vs. Ex‐CCT, and CCT vs. Ex‐CCT differences in cortical thickness and volume at trial completion, adjusting for age, sex, and Montreal Cognitive Assessment (MoCA) score. Result At trial completion, CCT vs. BAT decreased left rostral middle frontal gyrus volume (cluster size = 553.51 mm2, cluster‐wise p = .027) and left superior temporal gyrus thickness (cluster size = 525.58 mm2, cluster‐wise p = .039). Ex‐CCT vs. BAT increased cortical thickness in the left (cluster size = 900.23 mm2, cluster‐wise p = .001) and right (cluster size = 681.95 mm2, cluster‐wise p = .020) superior parietal gyri. Finally, Ex‐CCT vs. CCT increased left cuneus thickness (cluster size = 1062.12 mm2, cluster‐wise p < .001) as well as right post central gyrus thickness (cluster size = 714.85 mm2, cluster‐wise p = .005) and volume (cluster size = 1030.08 mm2, cluster‐wise p < .001). Conclusion Eight weeks of CCT with exercise is of sufficient duration to induce structural change in the brain. Moreover, exercise may enhance the effect of CCT on cortical grey matter structure vs. CCT alone.

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)0.004
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.021
GPT teacher head0.320
Teacher spread0.299 · 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 designRandomized trial
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
Published2023
Admission routes2
Has abstractyes

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