Towards understanding rTMS mechanism of action: Stimulation of the DLPFC causes network-specific increase in functional connectivity

Tik, Martin; Hoffmann, André; Sladky, Ronald; Tomova, Livia; Hummer, Allan; Lara, Lucia I. Navarro de; Bukowski, Henryk; Pripfl, Jürgen; Biswal, Bharat B.; Lamm, Claus; Windischberger, Christian

doi:10.1016/j.neuroimage.2017.09.022

Cited by 183 publications

(148 citation statements)

References 37 publications

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“…Two studies showed coherent findings, i.e. increased FC within the frontal hub of the FPN after excitatory TMS [50], and reduced FPN after inhibitory TBS [54], while the others did not report differences in FPN connectivity after TMS/TBS [49, 51], or reported an inverted direction of effects (i.e., increased FC after inhibitory or decreased FC after excitatory TBS) [52, 53]. Similarly, Eldaief et al [60] using rs-fMRI at baseline to identify individual DMN parietal targets, reported opposite effects according to the frequency of TMS: low-frequency stimulation increased DMN FC, while high-frequency stimulation decreased it [60].…”

Section: Local and Distal Connectivity Effects Of Nibsmentioning

confidence: 99%

Non-Invasive Brain Stimulation in Dementia: A Complex Network Story

et al. 2018

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Non-invasive brain stimulation (NIBS) is emerging as a promising rehabilitation tool for a number of neurodegenerative diseases. However, the therapeutic mechanisms of NIBS are not completely understood. In this review, we will summarize NIBS results in the context of brain imaging studies of functional connectivity and metabolites to gain insight into the possible mechanisms underlying recovery. We will briefly discuss how the clinical manifestations of common neurodegenerative disorders may be related with aberrant connectivity within large-scale neural networks. We will then focus on recent studies combining resting-state functional magnetic resonance imaging with NIBS to delineate how stimulation of different brain regions induce complex network modifications, both at the local and distal level. Moreover, we will review studies combining magnetic resonance spectroscopy and NIBS to investigate how microscale changes are related to modifications of large-scale networks. Finally, we will re-examine previous NIBS studies in dementia in light of this network perspective. A better understanding of NIBS impact on the functionality of large-scale brain networks may be useful to design beneficial treatments for neurodegenerative disorders.

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Section: Local and Distal Connectivity Effects Of Nibsmentioning

confidence: 99%

Non-Invasive Brain Stimulation in Dementia: A Complex Network Story

et al. 2018

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“…Previous research has primarily focused on abnormal connectivity within and among large-scale functional brain networks. The default mode network (DMN) and the affective network (AN) are now considered central to the neurobiology of depression and the therapeutic effects of rTMS (Downar & Daskalakis, 2013;Kaiser, Andrews-Hanna, Wager, & Pizzagalli, 2015;Sheline, Price, Yan, & Mintun, 2010;Tik et al, 2017). DMN abnormalities are associated with excessive internal rumination, self-referential processing, and episodic memory retrieval and have been linked to illness duration and treatment response (Hamilton, Farmer, Fogelman, & Gotlib, 2015;Kaiser et al, 2015;Liston et al, 2014).…”

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confidence: 99%

A multivariate neuroimaging biomarker of individual outcome to transcranial magnetic stimulation in depression

Cash

Cocchi

Anderson

et al. 2019

Human Brain Mapping

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The neurobiology of major depressive disorder (MDD) remains incompletely understood, and many individuals fail to respond to standard treatments. Repetitive transcranial magnetic stimulation (rTMS) of the dorsolateral prefrontal cortex (DLPFC) has emerged as a promising antidepressant therapy. However, the heterogeneity of response underscores a pressing need for biomarkers of treatment outcome. We acquired resting state functional magnetic resonance imaging (rsfMRI) data in 47 MDD individuals prior to 5–8 weeks of rTMS treatment targeted using the F3 beam approach and in 29 healthy comparison subjects. The caudate, prefrontal cortex, and thalamus showed significantly lower blood oxygenation level‐dependent (BOLD) signal power in MDD individuals at baseline. Critically, individuals who responded best to treatment were associated with lower pre‐treatment BOLD power in these regions. Additionally, functional connectivity (FC) in the default mode and affective networks was associated with treatment response. We leveraged these findings to train support vector machines (SVMs) to predict individual treatment responses, based on learned patterns of baseline FC, BOLD signal power and clinical features. Treatment response (responder vs. nonresponder) was predicted with 85–95% accuracy. Reduction in symptoms was predicted to within a mean error of ±16% (r = .68, p < .001). These preliminary findings suggest that therapeutic outcome to DLPFC‐rTMS could be predicted at a clinically meaningful level using only a small number of core neurobiological features of MDD, warranting prospective testing to ascertain generalizability. This provides a novel, transparent and physiologically plausible multivariate approach for classification of individual response to what has become the most commonly employed rTMS treatment worldwide. This study utilizes data from a larger clinical study (Australian New Zealand Clinical Trials Registry: Investigating Predictors of Response to Transcranial Magnetic Stimulation for the Treatment of Depression; ACTRN12610001071011; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=336262).

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“…Furthermore, the sustainability of the effects of aiTBS, or any type of stimulation treatment, are not yet exactly known Pascual-Leone et al (1996). Also, changes might be specific over time, for example,Tik et al (2017) only showed increased functional connectivity after 15 min, but not after 30 min, of rTMS. Changes in functional connectivity are mostly reported on shorter time-scales.…”

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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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Towards understanding rTMS mechanism of action: Stimulation of the DLPFC causes network-specific increase in functional connectivity

Cited by 183 publications

References 37 publications

Non-Invasive Brain Stimulation in Dementia: A Complex Network Story

Non-Invasive Brain Stimulation in Dementia: A Complex Network Story

A multivariate neuroimaging biomarker of individual outcome to transcranial magnetic stimulation in depression

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

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