LORETA Neurofeedback at precuneus in 3-year-old female with intrauterine drug exposure
Bibliographic record
Abstract
This case study presents data for operant conditioning of alpha current source density (CSD)in a 3-year-old female that completed 20 sessions of LNFB to address sequelae associated with intrauterine drug exposure (IUDE), including explosive reactions to unfavorable activities and siblings, deficits in self-care and self-direction and reducing social deficits. One of the more difficult processes is to assess children less than 6 years of age due to extreme variability in affect, interest and focus. However, IUDE increases the range of potential problems and diagnostic confounds. This individual showed improvements across ABAS-3 ratings by parents post-training and was able to complete the K-CPT post training and at 30-day follow-up. Her data demonstrated a general increase in the desired response (alpha CSD at precuneus) across time. Additional changes were evident in the default network (DMN) and a theorized mechanism of self-regulation (SRN) post training with a significant decrease at follow-up suggesting a learning effect over time. This case study demonstrates that LNFB may produce positive effects in children under the age of 4.
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 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".