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Zhong M, Cywiak C, Metto AC, Liu X, Qian C, Pelled G. Multi-session delivery of synchronous rTMS and sensory stimulation induces long-term plasticity. Brain Stimul 2021; 14:884-894. [PMID: 34029768 DOI: 10.1016/j.brs.2021.05.005] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 04/17/2021] [Accepted: 05/12/2021] [Indexed: 10/21/2022] Open
Abstract
BACKGROUND Combining training or sensory stimulation with non-invasive brain stimulation has shown to improve performance in healthy subjects and improve brain function in patients after brain injury. However, the plasticity mechanisms and the optimal parameters to induce long-term and sustainable enhanced performance remain unknown. OBJECTIVE This work was designed to identify the protocols of which combining sensory stimulation with repetitive transcranial magnetic stimulation (rTMS) will facilitate the greatest changes in fMRI activation maps in the rat's primary somatosensory cortex (S1). METHODS Several protocols of combining forepaw electrical stimulation with rTMS were tested, including a single stimulation session compared to multiple, daily stimulation sessions, as well as synchronous and asynchronous delivery of both modalities. High-resolution fMRI was used to determine how pairing sensory stimulation with rTMS induced short and long-term plasticity in the rat S1. RESULTS All groups that received a single session of rTMS showed short-term increases in S1 activity, but these increases did not last three days after the session. The group that received a stimulation protocol of 10 Hz forepaw stimulation that was delivered simultaneously with 10 Hz rTMS for five consecutive days demonstrated the greatest increases in the extent of the evoked fMRI responses compared to groups that received other stimulation protocols. CONCLUSIONS Our results provide direct indication that pairing peripheral stimulation with rTMS induces long-term plasticity, and this phenomenon appears to follow a time-dependent plasticity mechanism. These results will be important to lead the design of new training and rehabilitation paradigms and training towards achieving maximal performance in healthy subjects.
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Affiliation(s)
- Ming Zhong
- Neuroengineering Division, The Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, MI, USA
| | - Carolina Cywiak
- Neuroengineering Division, The Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, MI, USA; Department of Biomedical Engineering, Michigan State University, East Lansing, MI, USA
| | - Abigael C Metto
- Neuroengineering Division, The Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, MI, USA; Department of Biomedical Engineering, Michigan State University, East Lansing, MI, USA
| | - Xiang Liu
- Neuroengineering Division, The Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, MI, USA
| | - Chunqi Qian
- Department of Radiology, Michigan State University, East Lansing, MI, USA
| | - Galit Pelled
- Neuroengineering Division, The Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, MI, USA; Department of Biomedical Engineering, Michigan State University, East Lansing, MI, USA; Department of Radiology, Michigan State University, East Lansing, MI, USA.
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Gerber MB, McLean AC, Stephen SJ, Chalco AG, Arshad UM, Thickbroom GW, Silverstein J, Tsagaris KZ, Kuceyeski A, Friel K, Santos TEG, Edwards DJ. NeuroMeasure: A Software Package for Quantification of Cortical Motor Maps Using Frameless Stereotaxic Transcranial Magnetic Stimulation. Front Neuroinform 2019; 13:23. [PMID: 31105546 PMCID: PMC6499165 DOI: 10.3389/fninf.2019.00023] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2018] [Accepted: 03/15/2019] [Indexed: 12/02/2022] Open
Abstract
The recent enhanced sophistication of non-invasive mapping of the human motor cortex using MRI-guided Transcranial Magnetic Stimulation (TMS) techniques, has not been matched by refinement of methods for generating maps from motor evoked potential (MEP) data, or in quantifying map features. This is despite continued interest in understanding cortical reorganization for natural adaptive processes such as skill learning, or in the case of motor recovery, such as after lesion affecting the corticospinal system. With the observation that TMS-MEP map calculation and quantification methods vary, and that no readily available commercial or free software exists, we sought to establish and make freely available a comprehensive software package that advances existing methods, and could be helpful to scientists and clinician-researchers. Therefore, we developed NeuroMeasure, an open source interactive software application for the analysis of TMS motor cortex mapping data collected from Nexstim® and BrainSight®, two commonly used neuronavigation platforms. NeuroMeasure features four key innovations designed to improve motor mapping analysis: de-dimensionalization of the mapping data, fitting a predictive model, reporting measurements to characterize the motor map, and comparing those measurements between datasets. This software provides a powerful and easy to use workflow for characterizing and comparing motor maps generated with neuronavigated TMS. The software can be downloaded on our github page: https://github.com/EdwardsLabNeuroSci/NeuroMeasure
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Affiliation(s)
- Michael B Gerber
- Biomedical Engineering Department, The City College of New York, New York, NY, United States
| | - Alasdair C McLean
- Biomedical Engineering Department, The City College of New York, New York, NY, United States
| | - Samuel J Stephen
- Biomedical Engineering Department, The City College of New York, New York, NY, United States
| | - Alex G Chalco
- Biomedical Engineering Department, The City College of New York, New York, NY, United States
| | - Usman M Arshad
- Biomedical Engineering Department, The City College of New York, New York, NY, United States
| | | | | | - K Zoe Tsagaris
- Burke Neurological Institute, White Plains, NY, United States
| | - Amy Kuceyeski
- Department of Radiology, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, United States
| | - Kathleen Friel
- Brain Mind Research Institute, Weill Cornell Medicine, New York, NY, United States.,Blythedale Children's Hospital, Valhalla, NY, United States
| | - Taiza E G Santos
- Department of Neurosciences and Behavioral Sciences, Ribeirao Preto Medical School, University of São Paulo, Ribeirao Preto, São Paulo, Brazil
| | - Dylan J Edwards
- Moss Rehabilitation Research Institute, Elkins Park, PA, United States.,Edith Cowan University, Joondalup, WA, Australia
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