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Neural Plasticity
Volume 2016, Article ID 4071620, 17 pages
http://dx.doi.org/10.1155/2016/4071620
Review Article

Models to Tailor Brain Stimulation Therapies in Stroke

1Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH 44195, USA
2School of Biomedical Sciences, Kent State University, Kent, OH 44242, USA
3Human Cortical Physiology and Stroke Neurorehabilitation Section, National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD 20892, USA
4University of Surrey, Guildford, Surrey GU2 7XH, UK
5Neurology Clinical Division, Neurology Department, Hospital das Clinicas, Sao Paulo University, 05508-090 Sao Paulo, SP, Brazil
6Hospital Israelita Albert Einstein, 05652-900 Sao Paulo, SP, Brazil
7Center for Neurological Restoration, Neurosurgery, Neurological Institute, Cleveland Clinic Foundation, Cleveland Clinic, Cleveland, OH 44195, USA

Received 1 August 2015; Revised 30 December 2015; Accepted 4 January 2016

Academic Editor: Bruno Poucet

Copyright © 2016 E. B. Plow et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

A great challenge facing stroke rehabilitation is the lack of information on how to derive targeted therapies. As such, techniques once considered promising, such as brain stimulation, have demonstrated mixed efficacy across heterogeneous samples in clinical studies. Here, we explain reasons, citing its one-type-suits-all approach as the primary cause of variable efficacy. We present evidence supporting the role of alternate substrates, which can be targeted instead in patients with greater damage and deficit. Building on this groundwork, this review will also discuss different frameworks on how to tailor brain stimulation therapies. To the best of our knowledge, our report is the first instance that enumerates and compares across theoretical models from upper limb recovery and conditions like aphasia and depression. Here, we explain how different models capture heterogeneity across patients and how they can be used to predict which patients would best respond to what treatments to develop targeted, individualized brain stimulation therapies. Our intent is to weigh pros and cons of testing each type of model so brain stimulation is successfully tailored to maximize upper limb recovery in stroke.