Empathy, culture and brain - proposal for a large-scaled cross-cultural study
Bibliographic record
Abstract
Our brains and minds are shaped by the experiences we make in the context of the culture in which we develop and live. Although psychologists have provided abundant evidence for the diversity of human cognition and behaviour across cultures, the question of whether the neural correlates of human cognition are also culture- dependent is often not taken into account by neuroscientists. This paper presents the current knowledge concerning the influence of culture on empathy as the basic emotion of the social brain, and a proposal for a cross-cultural neuroimaging study on this issue. INTRODUCTION While psychologists have shown abundant evidence for diversity of human cognition and behavior across cultures, current neuroimaging research still neglects the potential cultural sensitivity of the underlying neural correlates only targeting general neural mechanisms of human cognition. To resolve this discrepancy between psychology and neuroscience, neuroimaging studies need to take into account the cultural diversity of human cognition and behaviour. Cultural differences seem to modulate many neural activities at multiple-level functions. Transcultural neuroimaging research will provide a novel approach to distinguish culture-independent and culture-sensitive neural mechanisms of human cognition and behaviour. To collect data on this new and important issue, Georg Northoff, Research Unit Director at the Institute of Mental Health Research of the University of Ottawa and Thomas Stompe, head of the Vienna Research Group on Transcultural Psychiatry, have considered to organize a serial of large-scaled cross-cultural studies on basic human cognitive and affective functions. As a first step healthy subjects from different countries, ethnicities and cultures should be included in order to collect basic data on these issues. These data should provide a baseline of knowledge for the studies on various groups of mentally ill patients. The first topic under study will be empathy, followed by self-processing and Theory of Mind.
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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 | 0.014 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.002 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| 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".