Event-Related Potential (ERP) Measures in Auditory Development Research
Bibliographic record
Abstract
INTRODUCTION Between birth and 2 years of age, the human cortex undergoes tremendous development, with region-specific and layer-specific patterns of synaptic maturation, overgrowth, and pruning that are undoubtedly influenced by environmental input and complex patterns of neurotransmitter expression (e.g., Huttenlocher & Dabholkar, 1997; Moore & Guan, 2001). During this period, the newborn, who is totally dependent on caregivers for survival, turns into a walking, talking, thinking, self-aware being. These anatomical and functional changes across development should be reflected in vivo in the electrical brain activity that can be measured at the scalp. In practice, collecting data from infants can be rather difficult. While studies that condition a behavioral response, such as sucking or looking, are probably the most advanced of the techniques available, there remain considerable problems in the type and amount of data that can be collected from preverbal infants with short attention spans and immature motor response systems, especially in the first months after birth. Postmortem studies of brain development can also be problematic because death in infancy is usually associated with abnormalities that may invalidate generalizations to normal development. Many of the imaging techniques available for the study of adult brain responses are difficult to apply to human infants. For example, fMRI and MEG require that the subject remain very still throughout the testing period. It is thus possible to test sleeping infants, but rather difficult to test awake infants (Anderson et al., 2001; Hattori et al., 2001; Souweidane et al., 1999).
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".