Neuroscientific approach can help reconcile self-reported emotions and their neural foundations
Researchers applied a machine-learning technique that could potentially translate patterns of activity into brain regions of fear processing into scores on questionnaires used to assess a patient's fear of pain. This neuroscientific approach, reported in eNeuro, can help reconcile self-reported emotions and their neural foundations.
Pain-related fear is typically assessed with several questionnaires, often used interchangeably, that ask patients how they feel about their clinical pain. However, it is not clear to what extent these self-reports measure fear and anxiety, which are known to involve different brain regions and perhaps other psychological constructs.
Michael Meier and colleagues at Petra Schweinhardts Laboratory at Balgrist University Hospital in Zurich, Switzerland, addressed this ambiguity by imagining the brains of patients with low back pain while watching video clips evoking harmful (bending) and harmless (walking) activities. The participants' brain activity was predictive of their scores in the various questionnaires. It is important to note that different questionnaires were associated with distinct patterns of neural activity. These results suggest that similar questionnaires can measure different emotional states.
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