The “self-awareness–anosognosia” paradox explained: How can one process be associated with activation of, and damage to, opposite sides of the brain?
Bibliographic record
Abstract
Healthy volunteers engaged in self-referential tasks such as reflecting on their personality traits exhibit mostly left lateralized brain activation, yet patients with lack of awareness of their deficit suffer from predominantly right hemisphere damage. How can the same basic process of self-awareness be associated with opposite sides of the brain? Anosognosia and self-awareness substantially differ on important dimensions and thus should not be equated. It is proposed that (1) anosognosia does not actually result from uniquely right hemisphere damage; (2) self-awareness and anosognosia do not constitute unitary concepts and encompass multiple other related processes, most likely associated with activity in distinct anatomical networks; and (3) impaired awareness of deficit is mostly caused by problems with self-monitoring, pre-/post-brain damage comparisons of performance, and episodic memory, and is more passive, unintentional, and about the body. Self-awareness produced by inviting participants to intentionally and actively think about more mental aspects of the self relies on judgements, inferential reasoning, imagination, and semantic memory. Consequently, the "self-awareness-anosognosia" paradox is only apparent. Furthermore, the claim that healthy self-awareness is located in the right hemisphere because anosognosia results from damage to this side of the brain must be fallacious.
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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 | 0.002 | 0.007 |
| 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 | 0.005 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".