Electroencephalographic markers of alexithymia in patients with moderate depression
Bibliographic record
Abstract
OBJECTIVE: To search for electroencephalographic markers of alexithymia in patients with moderate depression. MATERIAL AND METHODS: Sixty-four right-handed inpatients (20 men and 44 women, mean age 29.3+10.7 years), were studied. The level of alexithymia was assessed by the Russian version of the Toronto Alexithymia Scale (TAS-20-R). Patients were stratified into 4 groups by TAS-20-R scores. Two main groups of 22 patients each included people with high (>60 scores) and low (20-51 scores) levels of alexithymia. Control groups included 10 patients with 60-85 scores and 10 patients with 52-54 scores. Current methods of electroencephalographic analysis were used. RESULTS: Alexithymia in patients with moderate depression is characterized by a restructuring of the integrative activity of the brain detected by electroencephalography at rest. Patients with high alexithymia differ from those with low alexithymia by (1) lower values of the real part of the coherence between the frontal and anterior temporal leads of the left hemisphere in the band 28-30 Hz; (2) lower values of the imaginary part of coherence in the band 11-12 Hz between the posterior temporal and parietal as well as the posterior temporal and occipital cortical zones of the right hemisphere; (3) higher rates of the real part of the coherence between the right frontal and central leads in the frequency ranges 12-14 and 6-7 Hz; (4) large values of the imaginary part of the coherence between the left parietal and right posterior temporal cortex in the band 24-26 Hz; (5) higher values of the square of the coherence modulus between the left frontal and anterior temporal cortical zones in the band 17-18 Hz. CONCLUSION: Large cortical representations with involvement of theta, alpha, beta-1 and beta-2 rhythms can contribute to the pathogenesis of alexithymia.
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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 | 0.001 |
| 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 | 0.000 | 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".