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Brain activity predicts fear of pain

Neuroscientific approach may help reconcile self-reported emotions and their neural underpinnings

Society for Neuroscience

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IMAGE: The model performance (r, MSE) characterizes the strength of relationship between true and predicted labels. Condition and region weights show the predictive contribution of the two different conditions (harmful, harmless)... view more 

Credit: Meier et al., eNeuro (2018)

Researchers applied a machine learning technique that could potentially translate patterns of activity in fear-processing brain regions into scores on questionnaires used to assess a patient's fear of pain. This neuroscientific approach, reported in eNeuro, may help reconcile self-reported emotions and their neural underpinnings.

Pain-related fear is typically assessed with various questionnaires, often used interchangeably, that ask patients how they feel about their clinical pain. However, it is unclear 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 from Petra Schweinhardts' lab at the Balgrist University Hospital in Zurich, Switzerland, addressed this ambiguity by imaging the brains of patients with low back pain as they watched video clips evoking harmful (bending) and harmless (walking) activities for the back. Participants' brain activity was predictive of their scores on the various questionnaires. Importantly, different questionnaires were associated with distinct patterns of neural activity. These results suggest similar questionnaires may measure different emotional states.

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Article: Pain-related fear - Dissociable neural sources of different fear constructs

DOI: http://www.eneuro.org/lookup/doi/10.1523/ENEURO.0107-18.2018

Corresponding author: Michael Meier (University Hospital Balgrist, Zurich, Switzerland), michael.meier@balgrist.ch

About eNeuro

eNeuro, the Society for Neuroscience's open-access journal launched in 2014, publishes rigorous neuroscience research with double-blind peer review that masks the identity of both the authors and reviewers, minimizing the potential for implicit biases. eNeuro is distinguished by a broader scope and balanced perspective achieved by publishing negative results, failure to replicate or replication studies. New research, computational neuroscience, theories and methods are also published.

About The Society for Neuroscience

The Society for Neuroscience is the world's largest organization of scientists and physicians devoted to understanding the brain and nervous system. The nonprofit organization, founded in 1969, now has nearly 37,000 members in more than 90 countries and over 130 chapters worldwide.

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