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Record W3137355289 · doi:10.1161/str.52.suppl_1.53

Abstract 53: Frontal Functional Connectivity Networks and Executive Function Following Perinatal Stroke

2021· article· en· W3137355289 on OpenAlexaff
Suraya Meghji, Alicia Hilderley, Adam Kirton, Helen L. Carlson

Bibliographic record

VenueStroke · 2021
Typearticle
Languageen
FieldMedicine
TopicNeonatal and fetal brain pathology
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineDefault mode networkStroke (engine)Functional magnetic resonance imagingResting state fMRICognitionPopulationNeuroscienceNeuroimagingRating scaleExecutive dysfunctionPhysical medicine and rehabilitationPsychiatryPsychologyNeuropsychologyDevelopmental psychologyRadiology

Abstract

fetched live from OpenAlex

Perinatal stroke causes most hemiparetic cerebral palsy and a lifetime of disability with no known prevention strategies. Two types of perinatal stroke predominate, arterial ischemic stroke (AIS) and periventricular venous infarction (PVI), dictating lesion-specific differences in outcomes. Executive functioning challenges and attention deficit hyperactivity disorder (ADHD) are more common in children with perinatal stroke (19-35%) than peers (5-7%). Resting state (RS) functional magnetic resonance imaging (fMRI) measures fluctuations in the blood-oxygen level dependent (BOLD) signal that may estimate network functional connectivity (FC). We evaluated relationships between FC in relevant frontal circuits, ADHD and executive function in children with perinatal stroke compared to typically developing controls (TDC). Participant recruitment was from a population-based research cohort (AIS N=32; PVI N=30; TDC N=59). MRI imaging included T1-weighted anatomical and resting state fMRI sequences. Subsequent seed-to-seed analyses quantified FC within frontoparietal (FPN), dorsal attention (DAN) and default mode networks (DMN). Parent questionnaires quantified executive function (Behavior Rating Inventory of Executive Function (BRIEF)) and ADHD symptoms (ADHD Rating Scale-5). Large group FC differences were observed within FPN, DAN and DMN networks where AIS had lower FC compared to both PVI and TDC. For stroke participants, higher FC within the DAN and FPN was associated with poorer cognitive function (BRIEF). By contrast, higher FC within the DMN was associated with better ADHD ratings. Differences within frontal functional networks appear to be related to poorer cognitive function such that increased FC between the lesioned and nonlesioned hemisphere is associated with symptoms of executive dysfunction and ADHD suggesting that developmental plasticity leads to complex network changes following early unilateral brain injury.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.013
GPT teacher head0.237
Teacher spread0.224 · 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 designObservational
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
Published2021
Admission routes1
Has abstractyes

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