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Abstract:
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Pain is both a subjective and complex phenomenon. It is widely thought to emerge from distributed brain networks whose inputs include sensory, affective and evaluative processes. To properly understand pain, we must identify these networks and build models of their interactions that yield testable predictions about pain-related outcomes. In this talk we discuss several such models or ‘signatures’ of pain, that were developed by integrating activity across multiple systems, and using pattern-recognition to identify processes related to pain experience.
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