Functioning of the Default Mode Network with and Without Methylphenidate Treatment in Patients with Attention Deficit Hyperactivity Disorder: A Systematic Review
Bibliographic record
Abstract
Recent evidence has suggested that patients with ADHD display enhanced functioning of the Default Mode Network (DMN), resulting in altered functioning with its antagonistic Task Positive Network (TPN).To conduct this systematic review on DMN and TPN function and connectivity in ADHD patients using neuroimaging approaches, one investigator independently screened all titles, abstracts, and full-text articles and extracted data from selected studies that met the inclusion and exclusion criteria.After performing the search and screening methodology, 30 studies were detected that met the criteria for this systematic review.There were mixed findings of DMN connectivity with 45.45% finding reduced, 27.27% finding increased, and 27.27% of studies finding both increased and decreased connectivity in DMN regions.In addition, 50% of studies found increased functional connectivity between the DMN and TPN, and majority of studies (77.78%) found reduced anticorrelation between the DMN and TPN, in other words, a reduced DMN suppression.Overall it was found that DMN function is altered in patients with ADHD.Furthermore, all studies demonstrated that methylphenidate treatment results in a suppression of the DMN, suggesting a potential mechanism of action for its treatment of ADHD.Despite mixed findings regarding DMN intraconnectivity and interconnectivity with the TPN, this systematic review supports the conclusion that ADHD is a disorder of DMN dysfunction including dopamine alterations which can be reversed and treated by methylphenidate.This research will assist in the development of potential neuroimaging-based diagnostic approaches for ADHD as well as the tracking of treatment responses (Mak et al., 2017).Further research is needed to fully understand the correlation between DMN activity and ADHD.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| 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".