Brain networks predict placebo response in experimental and clinical models of placebo treatment

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Javeria Ali Hashmi

Harvard Medical School, USA

: Analg Resusc: Curr Res

Abstract

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The advent of new imaging methods and data modeling techniques has revolutionized our capacity to understand and utilize brain signals. With these techniques, the dynamic interactions between the complex elements of the brain can be used to effectively decode the neurological substrates of pain perception and modulation. The task to discover how intricately connected brain networks process and modulate pain is an important scientific challenge that can leeway into novel clinical tools and improved pain therapeutics. This talk will present evidence that brain network properties can be used to predict the time course of pain experiences. We have reported that synchronizations in specific brain networks in particular BOLD frequency bands forecast outcomes of placebo treatment in chronic back pain patients that were tested in clinical trial conditions. More recently we have discovered that computationally characterized whole brain network alignments predict subsequent induced placebo analgesia in a clinical population of knee pain patients. These findings indicate a role of network configurations in facilitating adaptive pain modulation.

Biography

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