Development of visual texture segregation during early childhood
Bibliographic record
Abstract
Most of the studies that have focused on the development of the visual system in children using visual evoked potentials (VEPs) have used stimuli soliciting only one level of visual processing. However, the perception of a visual scene requires a multitude of analytical processes ranging from the encoding of various characteristics of the visual stimuli, to the processing of top-down information and finally leading to segmentation of forms and recognition of stimuli. Numerous studies have shown that this more complex visual process can be objectively studied with specific VEPs, namely texture segregation visual evoked potentials (tsPEVs). Even though it has been demonstrated that texture segregation appears in the first few months of life and that it continues to develop within the first year, it is not known at what age texture segregation processes reach maturity. The purpose of the present study was to determine, using tsVEPs and high-density EEG, the normal development of higher-level visual processing during early childhood. We assessed typically developing children aged 12 months (n=15), 24 months (n=14) and 36 months of age (n=15). Four different stimuli, two low-level (lines homogeneously oriented to the right or left) and two higher-level (orientation-defined checkerboard composed of 90° line gradients oriented concentrically or outwards) were presented randomly on a screen in front of the child. The tsVEP was obtained by subtracting low-level from higher-level responses. Results show significant (p<.05) differences between the 12 months and 36 months groups, for both amplitude and latency of the N2 component. More specifically, there is a latency reduction and amplitude gain with increasing age. Furthermore, the electrophysiological response pattern obtained at 36 months is comparable to the one observed in adults. In conclusion, our data show that there is a clear maturation of texture-segregation processes taking place between 12 and 36 months of age. Meeting abstract presented at VSS 2012
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".