Meta-analysis of brain functional images under N-back and DMTS paradigm in human working memory
Bibliographic record
Abstract
Objective To study the similarities and differences in brain activation under N-back and DMTS paradigms of working memory. Methods Through searching of BrainMap function database by the combination keywords, a total of 122 articles with 122 experiments (N-back: 67 experiments, 937 subjects, 900 foci; Delayed Matched to Sample: 55 experiments, 806 subjects, 872 foci). Maps were analyzed using the FDR PN (P<0.0001) method based coordinates of the Montreal Neurological Institute (MNI) space. Results In the combine of the N-back and DMTS paradigms, these regions were activated including the bilateral inferior parietal lobe (Left: -36, -52, 44; Right: 38, -52, 48) and insula(Left: -34, 22, 0; Right: 34, 24, 2), the superior frontal gyrus (2, 16, 50) and inferior frontal gyrus (-44, 8, 30)of the left brain, and the middle frontal (46, 36, 24) and sub-gyral (30, 4, 56)of the right brain. The N-back paradigm was similar to the above results, whereas the DMTS paradigm only activated the precentral gyrus (-50, 8, 34) of the left brain and the right insula (34, 24, 4). Conclusion The neural circuit of working memory is the frontal-parietal networks. N-back paradigm with the brain activation consists to the neural circuit of working memory.However, DMTS paradigm activates less brain regions and is inconsistent to the neurons of working memory. Key words: Health controls; Working memory; N-back paradigm; Delayed matched to sample paradigm; Meta-analysis; Brain functional images
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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 | 0.010 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.020 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".