Assessment and treatment of pain with non-invasive cortical stimulation
| Autor: | Soroush Zaghi, Bruna Thiele, Felipe Fregni, Thais Spacov Camargo Pimentel, Daniel C. Pimentel |
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| Rok vydání: | 2011 |
| Předmět: |
Cerebral Cortex
Modalities Transcranial direct-current stimulation medicine.medical_treatment Chronic pain Pain Electric Stimulation Therapy Stimulation Pain scale medicine.disease Databases Bibliographic Transcranial Magnetic Stimulation Transcranial magnetic stimulation Developmental Neuroscience Neurology Brain stimulation medicine Humans Pain Management Neurology (clinical) Primary motor cortex Psychology Neuroscience Pain Measurement |
| Zdroj: | Restorative Neurology and Neuroscience. 29:439-451 |
| ISSN: | 0922-6028 |
| DOI: | 10.3233/rnn-2011-0615 |
| Popis: | Purpose: There remains an unmet clinical need for the development of new therapeutic approaches for the treatment of pain. Recent findings have confirmed significant changes in the pain-related neural networks among patients with chronic pain, opening novel possibilities for investigation. Two non-invasive techniques (transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS)) have emerged as interesting, effective, and promising modalities for pain relief. Methods: Here we review the clinical efficacy of these techniques for the treatment of pain through an updated systematic meta-analysis on the effects of primary motor cortex stimulation on pain and we discuss potential mechanisms of action based on insights from brain stimulation studies. Our meta-analysis includes 18 studies, which together show that non-invasive brain stimulation is associated with an effect size of −0.86 (95% C.I., −1.54, −0.19) on a standardized pain scale ranging from 0 (no pain) to 10 (worst pain possible). Results and Conclusions: Besides its use as a therapeutic tool, non-invasive brain stimulation can also be used to measure cortical reactivity and plasticity in chronic pain. Such measurements could potentially be used as biomarkers for the dysfunctional chronic pain-related neural network and might be helpful in measuring the efficacy of interventions designed for chronic pain. |
| Databáze: | OpenAIRE |
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