Altered EEG spectral activity and attentional behavioral deficits following prolonged febrile seizures: a pilot study
Bibliographic record
Abstract
The consequences of febrile seizures (FSs) in infants are still a matter of debate. It is important to develop non-invasive tools to determine markers of brain function that could have predictive value for the outcome of FSs infants.Pattern visual evoked potentials (pVEPs) were recorded in 18 FS infants (mean age of seizure 15.97 months). Spectral density and coherence analyses were performed in infants evaluated at 1.1 month (n = 4), 5.75 months (n = 4) or 30.33 months (n = 6) following a prolonged FS and compared to age-matched healthy controls. The impact of severity of seizures was assessed by comparing the children who had prolonged FSs to 4 infants that had experienced a simple FS. Cognitive tests (Bayley, Stanford-Binet) were administered at the time of testing in FS and control children. Behavioural measures (Achenbach Child Behavior Check List) were administered two years after the FS. pVEP responses and coherence measures failed to yield significant differences between the FS groups and healthy controls. However, spectral density measures showed a significant increase in delta band activity in both FS groups and a reduced high frequency density only in the prolonged FS groups that was seen up to 39 months post-seizure. Behavioural and cognitive measures revealed cognitive development within average, but lower attentional capacities in the FS infants. The persistent changes in spectral density patterns seen in children with prolonged FS may reflect seizure induced alterations in the developing brain or a result of a complex mode of inheritance. Further studies are needed to determine whether these observations can be used as a marker to predict the vulnerability of the child in developing behavioral deficits or epilepsy.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".