Psychedelics, entropic brain theory, and the taxonomy of conscious states: a summary of debates and perspectives
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Given their recent success in counseling and psychiatry, the dialogue around psychedelics has mainly focused on their applications for mental health. Insights from psychedelic research, however, are not limited to treating mental health, but also have much to offer our current understanding of consciousness. The investigation of psychedelic states has offered new perspectives on how different aspects of conscious experience are mediated by brain activity; as such, much more has been learned about consciousness in terms of its phenomenology and potential mechanisms. One theory that describes how psychedelics influence brain activity is the "entropic brain theory" (EBT), which attempts to understand conscious states-normal and psychedelic-in terms of "brain entropy." Given its wide explanatory reach, this theory has several implications for current debates in consciousness research, namely the issue of whether consciousness exists in levels vs. dimensions; whether the psychedelic state is itself a "higher" level of consciousness; and if so, whether psychedelics could be used to treat disorders of consciousness. To understand how psychedelics could possibly treat a minimally conscious or vegetative patient, one must first understand EBT and how this theory intersects with these ongoing debates. Thus, this article offers a formal summary of EBT, distilling its core principles and their implications for a theoretical model of consciousness. In response to their proposed use in treating disorders of consciousness, we emphasize the importance of "set" and "setting" in ascertaining the therapeutic value of psychedelics for vegetative and/or minimally conscious patients.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.006 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it