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Record W2735995517 · doi:10.11575/prism/27193

On the Malleability of Human Cognition: Working Memory Training and Transfer

2017· dissertation· en· W2735995517 on OpenAlexfundno aff
Cameron M. Clark

Bibliographic record

VenuePRISM (University of Calgary) · 2017
Typedissertation
Languageen
FieldPsychology
TopicCognitive Abilities and Testing
Canadian institutionsnot available
FundersAlberta Innovates
KeywordsMalleabilityCognitionWorking memory trainingWorking memoryCognitive psychologyPsychologyCognitive scienceComputer scienceNeuroscienceComputer security

Abstract

fetched live from OpenAlex

Training working memory (WM) to increase WM capacity and fluid intelligence (Gf) has received much experimental attention in recent years, though its efficacy remains highly controversial. The current study investigated the effect of a randomized six-week online WM intervention on cognitive abilities and patterns of neural activation in a community-recruited sample of healthy young adults, in relation to both a processing speed training active control condition, as well as a no-contact control condition. Results of this randomized trial are discussed in three parts: Chapter 2 examines group-level fMRI activation patterns for tasks of WM and Gf before the training intervention. Consistent with previous research, results indicate large areas of fronto-parietal activation in response to increasing task demands for our WM task, which largely subsume more circumscribed regions of activation for our Gf task. These results are discussed in terms of a task-general central network which may underlie performance of WM, Gf, and perhaps even goal-directed behaviour more generally. Chapter 3 investigates potential differences in a wide range of cognitive test scores before and after WM training, processing speed training, or no-contact. Results revealed support for the null hypothesis across all cognitive tests administered. Because these results are consistent with experimental trials of equal or greater methodological rigor, we suggest that future research re-focus on promising interventions known to increase memory performance in healthy young adults; and/or examine alternative populations in which WM training may be efficacious. Chapter 4 examines potential differences in pre- and post-training patterns of neural activation for WM and Gf tasks in our WM training, and processing speed training groups. Results indicated significant post-training reductions in activation for the WM trained group in relation to the processing speed group for the WM task, but not the Gf task. These results suggest that WM training does not affect patterns of neural activation for Gf tasks. We suggest that future research investigate neural correlates of WM training in populations for which WM itself is impaired; and/or WM training interventions in populations that have returned more promising results compared to those with healthy young adults.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.893
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0020.000

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 head0.057
GPT teacher head0.274
Teacher spread0.217 · 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 teacher head, not a consensus.

Study designOther design
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
Published2017
Admission routes1
Has abstractyes

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