Effect of mind on brain activity: Evidence from neuroimaging studies of psychotherapy and placebo effect
Bibliographic record
Abstract
Mentalistic variables must be considered to reach a correct understanding of the neurophysiological basis of behavior in humans. Confusion regarding the relative importance of neurophysiological and mentalistic variables can lead to important misconceptions about causes and effects in the study of human behavior. In this article, we review neuroimaging studies of the effect of psychotherapy in patients suffering from diverse forms of psychopathology (obsessive-compulsive disorder, panic disorder, unipolar major depressive disorder, spider phobia). We also review neuroimaging studies of the placebo effect in healthy individuals (placebo analgesia, psychostimulant expectation) and patients with Parkinson's disease or unipolar major depressive disorder. Mental functions and processes involved in diverse forms of psychotherapy exert a significant influence on brain activity. With regard to the placebo effect, beliefs and expectations can markedly modulate neurophysiological and neurochemical activity in brain regions involved in perception, movement, pain and various aspects of emotion processing. The findings of the neuroimaging studies reviewed here strongly support the view that the subjective nature and the intentional content of mental processes significantly influence the various levels of brain functioning (e.g. molecular, cellular, neural circuit) and brain plasticity.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".