Brain Topological Correlates of Motor Performance Changes After Repetitive Transcranial Magnetic Stimulation

Park, Chang-Hyun; Chang, Won Hyuk; Yoo, Woo-Kyoung; Shin, Yong‐Il; Kim, Sung Tae; Kim, Yun-Hee

doi:10.1089/brain.2013.0187

Cited by 10 publications

(18 citation statements)

References 30 publications

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“…Among the various mathematical models, we need to select the appropriate one for the question to be addressed, e.g., graph-theoretical analysis, dynamic causal modeling, and computational modeling (Hartwigsen et al, 2013, Park et al, 2014, Cocchi et al, 2016). …”

Section: Tms-fmrimentioning

confidence: 99%

Contribution of transcranial magnetic stimulation to assessment of brain connectivity and networks

Hallett

Iorio

Rossini

et al. 2017

Clinical Neurophysiology

119

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The goal of this review is to show how transcranial magnetic stimulation (TMS) techniques can make a contribution to the study of brain networks. Brain networks are fundamental in understanding how the brain operates. Effects on remote areas can be directly observed or identified after a period of stimulation, and each section of this review will discuss one method. EEG analyzed following TMS is called TMS-evoked potentials (TEPs). A conditioning TMS can influence the effect of a test TMS given over the motor cortex. A disynaptic connection can be tested also by assessing the effect of a pre-conditioning stimulus on the conditioning-test pair. Basal ganglia-cortical relationships can be assessed using electrodes placed in the process of deep brain stimulation therapy. Cerebellar-cortical relationships can be determined using TMS over the cerebellum. Remote effects of TMS on the brain can be found as well using neuroimaging, including both positron emission tomography (PET) and functional magnetic resonance imaging (fMRI). The methods complement each other since they give different views of brain networks, and it is often valuable to use more than one technique to achieve converging evidence. The final product of this type of work is to show how information is processed and transmitted in the brain.

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Section: Tms-fmrimentioning

confidence: 99%

Contribution of transcranial magnetic stimulation to assessment of brain connectivity and networks

Hallett

Iorio

Rossini

et al. 2017

Clinical Neurophysiology

119

View full text Add to dashboard Cite

show abstract

“…Resting-state functional MRI (rs-fMRI) measures spontaneous neuronal activity in human brain (Biswal et al, 1995) and has been commonly applied to explore the topological organization of brain functional networks (Wang et al, 2010). Park et al (2014) demonstrated that increased global efficiency and decreased local efficiency of the whole brain network was observed in participants who had greater motor performance changes after employing high-frequency rTMS (10 Hz) over the right M1. However, how different frequency rTMS over M1 modulates topological organization in the SMN remains unclear.…”

Section: Introductionmentioning

confidence: 99%

Altered Topological Organization in the Sensorimotor Network After Application of Different Frequency rTMS

et al. 2019

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The application of repetitive transcranial magnetic stimulation (rTMS) over the primary motor cortex (M1) could influence the intrinsic brain activity in the sensorimotor network (SMN). However, how rTMS modulates the topological organization of the SMN remains unclear. In this study, we employed resting-state fMRI to investigate the topological alterations in the functional SMN after application of different frequency rTMS over the left M1. To accomplish this, we collected MRI data from 45 healthy participants who were randomly divided into three groups based on rTMS frequency (HF, high-frequency 3 Hz; LF, low-frequency 1 Hz; and SHAM). Individual large-scale functional SMN was constructed by correlating the mean time series among 29 regions of interest (ROI) in the SMN and was fed into graph-based network analyses at multiple levels of global organization and nodal centrality. Our results showed that compared with the network metrics before rTMS stimulation, the left paracentral lobule (PCL) exhibited reduced nodal degree and betweenness centrality in the LF group after rTMS, while the right supplementary motor area (SMA) exhibited reduced nodal betweenness centrality in the HF group after rTMS. Moreover, rTMS-related alterations in nodal metrics might have been attributable to the changes in connectivity patterns and local activity of the affected nodes. These findings reflected the potential of using rTMS over M1 as an effective intervention to promote motor function rehabilitation.

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“…Vecchio et al (2018) performed source localization on EEG data recorded before and after transcranial direct current stimulation (tDCS) and showed that anodal tDCS over the motor cortex reduces small-worldness. Park et al (2014), Polanía et al (2011), andCocchi et al (2015) studied the effects of various stimulation techniques using task fMRI and rs-fMRI data. Park observed a correlation between the motor performance change and the increase and decrease in global and local efficiency respectively, induced by 10 Hz rTMS (Park et al, 2014).…”

mentioning

confidence: 99%

“…Park et al (2014), Polanía et al (2011), andCocchi et al (2015) studied the effects of various stimulation techniques using task fMRI and rs-fMRI data. Park observed a correlation between the motor performance change and the increase and decrease in global and local efficiency respectively, induced by 10 Hz rTMS (Park et al, 2014).…”

mentioning

confidence: 99%

Focal application of accelerated iTBS results in global changes in graph measures

Klooster

Franklin

Besseling

et al. 2018

Human Brain Mapping

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Graph analysis was used to study the effects of accelerated intermittent theta burst stimulation (aiTBS) on the brain's network topology in medication‐resistant depressed patients. Anatomical and resting‐state functional MRI (rs‐fMRI) was recorded at baseline and after sham and verum stimulation. Depression severity was assessed using the Hamilton Depression Rating Scale (HDRS). Using various graph measures, the different effects of sham and verum aiTBS were calculated. It was also investigated whether changes in graph measures were correlated to clinical responses. Furthermore, by correlating baseline graph measures with the changes in HDRS in terms of percentage, the potential of graph measures as biomarker was studied. Although no differences were observed between the effects of verum and sham stimulation on whole‐brain graph measures and changes in graph measures did not correlate with clinical response, the baseline values of clustering coefficient and global efficiency showed to be predictive of the clinical response to verum aiTBS. Nodal effects were found throughout the whole brain. The distribution of these effects could not be linked to the strength of the functional connectivity between the stimulation site and the node. This study showed that the effects of aiTBS on graph measures distribute beyond the actual stimulation site. However, additional research into the complex interactions between different areas in the brain is necessary to understand the effects of aiTBS in more detail.

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Brain Topological Correlates of Motor Performance Changes After Repetitive Transcranial Magnetic Stimulation

Cited by 10 publications

References 30 publications

Contribution of transcranial magnetic stimulation to assessment of brain connectivity and networks

Contribution of transcranial magnetic stimulation to assessment of brain connectivity and networks

Altered Topological Organization in the Sensorimotor Network After Application of Different Frequency rTMS

Focal application of accelerated iTBS results in global changes in graph measures

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