EEG Features in Young Patients with Syndromally Different Subtypes of Borderline Personality Disorder
Bibliographic record
Abstract
Introduction The study of the neurobiological characteristics of borderline personality disorder (BPD) in youth is actual due to its high prevalence, but quantitative EEG studies of BPD have yielded mixed results. Objectives The aim of the study was to assess the EEG features in patients with different clinical subtypes of borderline personality disorder (BPD). Methods Total of 52 patients aged 16-25 years (mean age 20.4±3.2 years) with BPD (F60.31 by ICD-10) were enrolled in the study. Three groups of patients with different subtypes of BPD (with predominance of “affective storm”, “addictive adrenalin mania” and “cognitive dissociation”) were identified based on clinical and psychopathological characteristics. A pre-treatment multichannel resting EEG was recorded with measurements of EEG spectral power and coherence in narrow frequency sub-bands. Between-group differences in clinical and neurophysiological parameters were identified using Mann-Whitney criteria. Results The groups did not differ in EEG spectral power values, but significant (p<0.05) differences between the groups were revealed in the spatial organization of the EEG namely in the number of “highly coherent” functional connections (with coherence coefficients above 0.9) that was the least in the group with “cognitive dissociation”. Low values of the number of such connections in the alpha2 EEG sub-band (9-11 Hz) in the frontal-central-temporal brain regions reflect a relatively poor functional state of the prefrontal cortex in this group. Conclusions The noted features of the spatial functional organization of brain activity in patients with different BPD subtypes may underlie differences in their clinical conditions, in control of emotions and behavior. Disclosure of Interest None Declared
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 | 0.000 | 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".