The psychology of neurofeedback: Clinical intervention even if applied placebo.
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
Advocates of neurofeedback make bold claims concerning brain regulation, treatment of disorders, and mental health. Decades of research and thousands of peer-reviewed publications support neurofeedback using electroencephalography (EEG-nf); yet, few experiments isolate the act of receiving feedback from a specific brain signal as a necessary precursor to obtain the purported benefits. Moreover, while psychosocial parameters including participant motivation and expectation, rather than neurobiological substrates, seem to fuel clinical improvement across a wide range of disorders, for-profit clinics continue to sprout across North America and Europe. Here, we highlight the tenuous evidence supporting EEG-nf and sketch out the weaknesses of this approach. We challenge classic arguments often articulated by proponents of EEG-nf and underscore how psychologists and mental health professionals stand to benefit from studying the ubiquitous placebo influences that likely drive these treatment outcomes. (PsycINFO Database Record
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 | 0.007 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it