Current Understanding of Religion, Spirituality, and Their Neurobiological Correlates
Bibliographic record
Abstract
Religion and spirituality (R/S) have been prominent aspects of most human cultures through the ages; however, scientific inquiry into this phenomenon has been limited. We conducted a systematic literature review of research on the neurobiological correlates of R/S, which resulted in 25 reports studying primarily R/S with electroencephalography, structural neuroimaging (MRI), and functional neuroimaging (fMRI, PET). These studies investigated a wide range of religions (e.g., Christianity, Buddhism, Islam) and R/S states and behaviors (e.g., resting state, prayer, judgments) and employed a wide range of methodologies, some of which (e.g., no control group, varying measures of religiosity, small sample sizes) raise concerns about the validity of the results. Despite these limitations, the findings of these studies collectively suggest that the experience of R/S has specific neurobiological correlates and that these correlates are distinct from non-R/S counterparts. The findings implicate several brain regions potentially associated with R/S development and behavior, including the medial frontal cortex, orbitofrontal cortex, precuneus, posterior cingulate cortex, default mode network, and caudate. This research may suggest future clinical applications and interventions related to R/S and various disorders, including mood, anxiety, psychotic, pain, and vertiginous disorders. Further studies with more rigorous study designs are warranted to elucidate the neurobiological mechanisms of R/S and their potential clinical applications.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".