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Record W4408377778 · doi:10.1002/cns3.20108

Coordinate Network Mapping of Focal Brain Volume Differences in ADHD Reveals Common Patterns That Lack Specificity: A Systematic Review

2025· review· en· W4408377778 on OpenAlexaff
Juliana Wall, Gillian N. Miller, Joseph J. Taylor, Jacob L. Stubbs, Simon K. Warfield, Alexander L. Cohen

Bibliographic record

VenueAnnals of the Child Neurology Society · 2025
Typereview
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsBrain sizePsychologyNeuroscienceMedicineMagnetic resonance imagingRadiology

Abstract

fetched live from OpenAlex

Objective: Attention-deficit/hyperactivity disorder (ADHD) has been associated with decreased regional brain volume, yet no consistent localization has emerged across studies. This discrepancy has been attributed to ADHD's diagnostic heterogeneity; however, one alternative is that ADHD is associated with alterations of brain networks, not individual regions. To test this hypothesis, we compared a traditional anatomic likelihood estimate (ALE) with a "coordinate network mapping" (CNM) approach using data from 38 studies comparing regional brain volumes in ADHD versus healthy controls. Methods: We performed an ALE analysis, determining above-chance convergence between experiments. Next, we calculated the overlap with the putamen and default mode network, defined a priori. We then applied CNM, generating connectivity maps for each study and statistically comparing these maps to identify common areas of connectivity across studies. Finally, we compared the network map of ADHD with several control groups of neuropsychiatric disorders and with randomly generated coordinates. Results: ALE identified no significant spatial convergence between experiments. We also found only limited spatial overlap with the default mode network and weak functional connectivity with the putamen. Conversely, CNM revealed that the heterogenous coordinates fell within a consistent brain network characterized by connectivity with the reward and cingulo-opercular "action mode" networks. However, we could not differentiate this network from the CNM-derived networks in control groups. Interpretation: Although this network is biologically plausible and consistent with ADHD symptoms, the findings suggest that this network is not specific to ADHD and may reflect large-scale brain networks. Although this meta-analysis adds to the literature on the neurobiology of ADHD, the nonspecific findings convey the importance of studying ADHD at the symptom level.

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)0.006
metaresearch head score (Gemma)0.030
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.015
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.030
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.006
Bibliometrics0.0150.013
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0010.001
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 head0.175
GPT teacher head0.385
Teacher spread0.210 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations3
Published2025
Admission routes1
Has abstractyes

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Same venueAnnals of the Child Neurology SocietySame topicAttention Deficit Hyperactivity DisorderFrench-language works237,207