Pain-Related Fear—Dissociable Neural Sources of Different Fear Constructs
| Autor: | Philipp Staempfli, Erich Seifritz, Petra Schweinhardt, Andrea Vrana, Michael L. Meier, Barry Kim Humphreys |
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| Přispěvatelé: | University of Zurich, Meier, Michael Lukas |
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
Adult
Male Multivariate analysis Adolescent Brain activity and meditation Pain 610 Medicine & health Anxiety Amygdala Machine Learning Young Adult Neuroimaging Surveys and Questionnaires medicine Image Processing Computer-Assisted Humans Correlation of Data low back pain Psychiatric Status Rating Scales Brain Mapping medicine.diagnostic_test General Neuroscience Chronic pain Brain 2800 General Neuroscience General Medicine Fear amygdala Middle Aged New Research medicine.disease Low back pain Magnetic Resonance Imaging fear network 1.1 Oxygen medicine.anatomical_structure multivariate analysis Cognition and Behavior 10054 Clinic for Psychiatry Psychotherapy and Psychosomatics Female Self Report medicine.symptom Psychology Functional magnetic resonance imaging chronic pain Cognitive psychology |
| Zdroj: | eNeuro |
| Popis: | Fear of pain demonstrates significant prognostic value regarding the development of persistent musculoskeletal pain and disability. Its assessment often relies on self-report measures of pain-related fear by a variety of questionnaires. However, based either on “fear of movement/(re)injury/kinesiophobia,” “fear avoidance beliefs,” or “pain anxiety,” pain-related fear constructs plausibly differ while it is unclear how specific the questionnaires are in assessing these different constructs. Furthermore, the relationship of pain-related fear to other anxiety measures such as state or trait anxiety remains ambiguous. Advances in neuroimaging such as machine learning on brain activity patterns recorded by functional magnetic resonance imaging might help to dissect commonalities or differences across pain-related fear constructs. We applied a pattern regression approach in 20 human patients with nonspecific chronic low back pain to reveal predictive relationships between fear-related neural pattern information and different pain-related fear questionnaires. More specifically, the applied multiple kernel learning approach allowed the generation of models to predict the questionnaire scores based on a hierarchical ranking of fear-related neural patterns induced by viewing videos of activities potentially harmful for the back. We sought to find evidence for or against overlapping pain-related fear constructs by comparing the questionnaire prediction models according to their predictive abilities and associated neural contributors. By demonstrating evidence of nonoverlapping neural predictors within fear-processing regions, the results underpin the diversity of pain-related fear constructs. This neuroscientific approach might ultimately help to further understand and dissect psychological pain-related fear constructs. |
| Databáze: | OpenAIRE |
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