Pilot Project to Ascertain the Utility of Tower of London Test to Assess Outcomes of Neurofeedback in Clients with Asperger's Syndrome
Bibliographic record
Abstract
Introduction.Behavioral and cognitive improvements in clients with Asperger's Syndrome (AS), employing continuous performance tests (CPTs), intelligence and academic measures, and electroencephalographic data, have been reported following 40 sessions of neurofeedback (NFB) training combined with coaching in metacognitive strategies.However, measures of executive functions (EFs) in this population have not been commonly employed and NFB is still not commonly used as a treatment for AS.Therefore, this pilot project used Tower of London -Drexel University (ToL DX ), an individually administered test of EFs, in addition to the previously mentioned measures.The goal of the current study was to investigate the utility of ToL DX as an assessment tool for clients with AS as well as further study the effects of NFB and training in metacognitive strategies on executive functioning in clients with AS. Method.Nineteen consecutive clients at the ADD Centre, Toronto, Canada (M age ¼ 12 years 0 months) recruited over a 2½-year period all had full clinical assessment, completed age appropriate questionnaires, and were tested pre-and post-40 NFB sessions.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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".