Effect of the catechol‐<i>O</i>‐methyltransferase <i>val<sup>158</sup>met</i> genotype on children’s early phases of facial stimuli processing
Bibliographic record
Abstract
The ability to process and identify human faces matures early in life, is universal and is mediated by a distributed neural system. The temporal dynamics of this cognitive-emotional task can be studied by cerebral visual event-related potentials (ERPs) that are stable from midchildhood onwards. We hypothesized that part of individual variability in the parameters of the N170, a waveform that specifically marks the early, precategorical phases of human face processing, could be associated with genetic variation at the functional polymorphism of the catechol-O-methyltransferase (val(158)met) gene, which influences information processing, cognitive control tasks and patterns of brain activation during passive processing of human facial stimuli. Forty-nine third and fourth graders underwent a task of implicit processing of other children's facial expressions of emotions while ERPs were recorded. The N170 parameters (latency and amplitude) were insensitive to the type of expression, stimulus repetition, gender or school grade. Although limited by the absence of met- homozygotes among boys, data showed shorter N170 latency associated with the presence of 1-2 met158 alleles, and family-based association tests (as implemented in the PBAT version 2.6 software package) confirmed the association. These data were independent of the serotonin transporter promoter polymorphism and the N400 waveform investigated in the same group of children in a previous study. Some electrophysiological features of face processing may be stable from midchildhood onwards. Different waveforms generated by face processing may have at least partially independent genetic architectures and yield different implications toward the understanding of individual differences in cognition and emotions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".