The Neuroscience of Hypo-Egoic Processes
Bibliographic record
Abstract
The term “hypo-egoic” can refer to a variety of cognitive states, ranging from internal experiences of meditation, hypnosis, or spirituality, to overt acts of forgiveness or altruism. This chapter reviews the nascent literature on the neuroscience supporting such states, aiming to provide a more unified neural account. For parsimony, research findings are framed in terms of implicated brain networks, with particular attention as to whether networks are modulated to directly inhibit of egoic processes, or to generate competing, experientially salient, hypo-egoic states. The chapter concludes that hypo-egoic processing is not purely inhibitory in its neural architecture but often incorporates generative neural representations, enhancing sensory awareness in meditation and hypnosis, the theory of another’s mind in love and forgiveness, and vicarious enjoyment in altruistic acts. These generative processes may anchor attention and attenuate prepotent tendencies toward egoic thinking, allowing for the transcendence of self-concern in favor of some greater good.
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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 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".