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Record W7132963379

From Structure to Function: Social and Cognitive Networks in Children Born Very Low Birth Weight

2022· dissertation· W7132963379 on OpenAlexaff
Julie Sato

Bibliographic record

VenueTSpace · 2022
Typedissertation
Language
FieldMedicine
TopicAdvanced Neuroimaging Techniques and Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFractional anisotropyWhite matterLow birth weightDiffusion MRICognitionAffect (linguistics)
DOInot available

Abstract

fetched live from OpenAlex

Infants born very low birth weight (VLBW, <1500 g) have an increased risk of social and cognitive impairments, which can affect their social and academic success at school. However, little is known about the functional and structural underpinnings of these impairments at preschool-age, an important transitional period in development, as well as the early modifiable predictors of outcome, such as postnatal nutrition. The present thesis used a multi-modal approach to investigate altered white matter microstructure and functional connectivity in five-year-old VLBW children. Using multi-shell diffusion imaging, studies 1 & 2 assessed white matter microstructure in VLBW compared to full-term (FT) children and associations with early nutrition (during postnatal days 9-29) and developmental outcome. Fractional anisotropy (FA), radial diffusivity (RD), neurite orientation dispersion index (ODI) and density index (NDI) were estimated using diffusion tensor and NODDI models. Using magnetoencephalography, social and cognitive networks were assessed during a resting-state (Study 3) and an emotional face processing task (Study 4). Studies 1 & 2 demonstrated disrupted white matter maturation in VLBW compared to FT children. These findings suggest that lower FA in VLBW children may be partly due to increases in axon dispersion, reflecting less coherent organization of axons. We also found that among the macronutrients studied, greater protein intake contributed most to the beneficial effect of nutrition, showing increases in FA and reductions in RD at preschool-age. Study 3 demonstrated increased resting-state functional connectivity in VLBW compared to FT children in the gamma (65-80 Hz) frequency band, anchored in frontal regions known to underlie social-cognitive functions. Further, significant associations between macronutrient/energy intakes with functional connectivity at preschool-age were found. Study 4 demonstrated that VLBW compared to FT children show atypical recruitment of emotional face processing networks in theta (4–7 Hz), specific to angry faces. This hypo-connected network involved key emotion face processing regions with links to inhibitory control. In conclusion, VLBW children showed alterations in structural and functional connectivity underlying social and cognitive functioning at preschool-age. Most importantly, our study relates these findings to early postnatal nutrition, demonstrating the long-term impacts of nutrition on preterm brain development.

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)0.001
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 score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.017
GPT teacher head0.346
Teacher spread0.330 · 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
Published2022
Admission routes1
Has abstractyes

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