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Combining TMS and EEG for Characterizing Motor Network Interactions and Improving Motor Recovery after Stroke.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Combining TMS and EEG for Characterizing Motor Network Interactions and Improving Motor Recovery after Stroke./
作者:	Johnson, Nessa.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2016,
面頁冊數:	121 p.
附註:	Source: Dissertations Abstracts International, Volume: 80-09, Section: B.
Contained By:	Dissertations Abstracts International80-09B.
標題:	Neurosciences. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10252835
ISBN:	9780438903821

Combining TMS and EEG for Characterizing Motor Network Interactions and Improving Motor Recovery after Stroke.
Johnson, Nessa.

Combining TMS and EEG for Characterizing Motor Network Interactions and Improving Motor Recovery after Stroke. - Ann Arbor : ProQuest Dissertations & Theses, 2016 - 121 p.

Source: Dissertations Abstracts International, Volume: 80-09, Section: B.

Thesis (Ph.D.)--University of Minnesota, 2016.

This item must not be added to any third party search indexes.

Imaging of electrophysiological activity within the brain is crucial to understanding function in both healthy and disease conditions. The overall goal of this dissertation is to use both non-invasive neuromodulation and non-invasive neuroimaging to characterize and manipulate underlying neurological network dynamics in both healthy and stroke affected subjects. The two main applications of work are for the evaluation of peripheral motor activity on motor network dynamics in healthy subjects, and as a brain-based treatment for motor recovery after stroke. Combined transcranial magnetic stimulation (TMS) and electroencephalography (EEG) imaging can be used to analyze cortical reactivity and connectivity of underlying brain networks. However, the effect of corticospinal and peripheral muscle activity on TMS-evoked potentials (TEPs), particularly in motor areas, is not well understood. One aim of the present dissertation is to evaluate the relationship between cortico-spinal activity, in the form of peripheral motor-evoked potentials (MEPs), and the TEPs from motor areas, along with the connectivity among activated brain areas. This research demonstrates that TMS-EEG, along with adaptive connectivity estimators, can be used to evaluate the cortical dynamics associated with sensorimotor integration and proprioceptive manipulation. Stroke is a devastating neurological disorder which can result in lasting impairment affecting quality-of-life. Combining contralesional repetitive TMS (rTMS) with EEG-based brain-computer interface (BCI) training can address motor impairment after stroke by down-regulating exaggerated inhibition from the contralesional hemisphere and encouraging ipsilesional activation. Another aim of this dissertation was to evaluate the efficacy of combined rTMS+BCI, compared to sham rTMS+BCI, and BCI alone, on motor recovery after stroke in subjects with lasting motor paresis. As evaluated in a series of stroke patients, such a brain-based neuromodulatory and imaging approach for rehabilitation could potentially lead to greater understanding of the influence of brain network dynamics in recovery and design of optimal treatment strategies for individual patients. Our findings demonstrate the feasibility and efficacy of not only combined rTMS+BCI but also BCI alone, as demonstrated by significant improvements over time in behavioral and electrophysiological measures. In summary, the present dissertation research developed and evaluated the combination of neuromodulation and neuroimaging for the non-invasive mapping of motor network activities in the diseased and normal brain. Evaluations were conducted in healthy controls to evaluate the influence of peripheral muscle activity on resulting neural network activity, as well as in stroke patients to provide a brain-based treatment for motor rehabilitation. The results obtained suggest the importance of non-invasive spatiotemporal neuroimaging, along with non-invasive neuromodulation, for providing insight into neuroscience questions and providing novel treatments for clinical problems in a brain-based manner.

ISBN: 9780438903821Subjects--Topical Terms:

588700
Neurosciences.
Subjects--Index Terms:

Eeg

Combining TMS and EEG for Characterizing Motor Network Interactions and Improving Motor Recovery after Stroke.
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506 $a This item must not be added to any third party search indexes.
506 $a This item must not be sold to any third party vendors.
520 $a Imaging of electrophysiological activity within the brain is crucial to understanding function in both healthy and disease conditions. The overall goal of this dissertation is to use both non-invasive neuromodulation and non-invasive neuroimaging to characterize and manipulate underlying neurological network dynamics in both healthy and stroke affected subjects. The two main applications of work are for the evaluation of peripheral motor activity on motor network dynamics in healthy subjects, and as a brain-based treatment for motor recovery after stroke. Combined transcranial magnetic stimulation (TMS) and electroencephalography (EEG) imaging can be used to analyze cortical reactivity and connectivity of underlying brain networks. However, the effect of corticospinal and peripheral muscle activity on TMS-evoked potentials (TEPs), particularly in motor areas, is not well understood. One aim of the present dissertation is to evaluate the relationship between cortico-spinal activity, in the form of peripheral motor-evoked potentials (MEPs), and the TEPs from motor areas, along with the connectivity among activated brain areas. This research demonstrates that TMS-EEG, along with adaptive connectivity estimators, can be used to evaluate the cortical dynamics associated with sensorimotor integration and proprioceptive manipulation. Stroke is a devastating neurological disorder which can result in lasting impairment affecting quality-of-life. Combining contralesional repetitive TMS (rTMS) with EEG-based brain-computer interface (BCI) training can address motor impairment after stroke by down-regulating exaggerated inhibition from the contralesional hemisphere and encouraging ipsilesional activation. Another aim of this dissertation was to evaluate the efficacy of combined rTMS+BCI, compared to sham rTMS+BCI, and BCI alone, on motor recovery after stroke in subjects with lasting motor paresis. As evaluated in a series of stroke patients, such a brain-based neuromodulatory and imaging approach for rehabilitation could potentially lead to greater understanding of the influence of brain network dynamics in recovery and design of optimal treatment strategies for individual patients. Our findings demonstrate the feasibility and efficacy of not only combined rTMS+BCI but also BCI alone, as demonstrated by significant improvements over time in behavioral and electrophysiological measures. In summary, the present dissertation research developed and evaluated the combination of neuromodulation and neuroimaging for the non-invasive mapping of motor network activities in the diseased and normal brain. Evaluations were conducted in healthy controls to evaluate the influence of peripheral muscle activity on resulting neural network activity, as well as in stroke patients to provide a brain-based treatment for motor rehabilitation. The results obtained suggest the importance of non-invasive spatiotemporal neuroimaging, along with non-invasive neuromodulation, for providing insight into neuroscience questions and providing novel treatments for clinical problems in a brain-based manner.
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