Is Our Self Related to Personality? A Neuropsychodynamic Model
Bibliographic record
Abstract
The concept and the assessment of personality have been extensively discussed in psychoanalysis and in clinical psychology over the years. Nowadays there is large consensus in considering the constructs of self and relatedness as central criterions to assess personality and its disturbances. However the relation between the psychological organization of personality, the construct of self and its neuronal correlates remain unclear. Based on recent empirical data on the neural correlates of self (and others), on the importance of early relational and attachment experiences, and on the relation with the brain’s spontaneous/resting state activity (rest – self overlap/containment), we here propose a multilayered model of self with (i) relational alignment; (ii) self-constitution; (iii) self-manifestation; and (iv) self-expansion. Importantly, these different layers of self can be characterized by different neuronal correlates – this results in different neuronally grounded configurations or organizations of personality. These layers correspond to different levels of personality organization like psychotic (as related to the layer of self-constitution), borderline (as related to the layer of self-manifestation), and neurotic (as related to the layer of self-expansion). Taken together, we here provide for the first time a neurobiologically and clinically grounded model of personality organization, which carries major psychodynamic and neuroscientific implications. The study of the spontaneous activity of the brain, intrinsically related to the self (rest–self overlap/containment) and the interaction with stimuli (rest–stimulus interaction) may represent a further advance in understanding how our default state plays a crucial role in navigating through the internal world and the external reality.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".