Non-linear EEG analyses predict non-response to rTMS treatment in major depressive disorder

Arns, Martijn; Cerquera, Alexander; Gutiérrez, Rafael; Hasselman, Fred; Freund, Jan A.

doi:10.1016/j.clinph.2013.11.022

Cited by 54 publications

(48 citation statements)

References 50 publications

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“…[35] Also, another type of study focused on nonlinear EEG metrics in alpha band indicated that responders to rTMS treatment showed significant increase in Lempel-Ziv Complexity (LZC), whereas nonresponders showed opposite change. [58] A higher prefrontal beta cordance and anterior individual alpha peak frequency (iAPF) led to larger percent improvements on the BDI scale, after HFL or LFR-rTMS. [30] With respect to the theta band (4-7Hz), a higher baseline theta power was associated with a weaker decline in BDI score and higher BDI scores at the end of HFL or LFR-rTMS.…”

Section: Neurophysiological Factors That Predict Response To Rtmsmentioning

confidence: 98%

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Neurobiological Predictors of Response to Dorsolateral Prefrontal Cortex Repetitive Transcranial Magnetic Stimulation in Depression: A Systematic Review

et al. 2015

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Significant methodological variability in rTMS treatment protocols limits the ability to generalize conclusions. However, response to treatment may be predicted by baseline frontal lobe blood flow, and presence of polymorphisms of the 5-hydroxytryptamine (5-HT) -1a gene, the LL genotype of the serotonin transporter linked polymorphic region (5-HTTLPR) gene, and Val/Val homozygotes of the brain-derived neurotrophic factor (BDNF) gene.

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Section: Neurophysiological Factors That Predict Response To Rtmsmentioning

confidence: 98%

“…Of the 1,278 articles, 41 articles met the full inclusion criteria (Fig. [15,19,23,26,30,46,51,58] The remaining 29 studies examined the effects of HFL-rTMS alone. There were 12 studies that included a control condition [13, 14, 16-23, 47, 58] and 29 that did not.…”

Section: Characteristics Of Included Studiesmentioning

confidence: 99%

Neurobiological Predictors of Response to Dorsolateral Prefrontal Cortex Repetitive Transcranial Magnetic Stimulation in Depression: A Systematic Review

et al. 2015

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“…The tools to directly map functional connectivity and to develop network measures in studying their changes under various conditions (healthy, diseased and/or TMS stimulated) would be of both theoretical and eventual practical utility. It has been suggested that network measures are more sensitive clinical biomarkers for dysconnectivity diseases [34], that they can better predict stimulation outcomes [38], [39], and that network-guided stimulation treatments lead to better outcomes [40]. Recent studies using resting-state fMRI (rsfMRI) [17]–[19], [21] have shown different excitatory/inhibitory effects of rTMS between the stimulated and functionally connected regions.…”

Section: Introductionmentioning

confidence: 99%

Lasting Modulation Effects of rTMS on Neural Activity and Connectivity as Revealed by Resting-State EEG

Ding

Shou

Yuan

et al. 2014

IEEE Trans. Biomed. Eng.

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The long-lasting neuromodulatory effects of repetitive transcranial magnetic stimulation (rTMS) are of great interest for therapeutic applications in various neurological and psychiatric disorders, due to which functional connectivity among brain regions is profoundly disturbed. Classic TMS studies selectively alter neural activity in specific brain regions and observe neural activity changes on nonperturbed areas to infer underlying connectivity and its changes. Less has been indicated in direct measures of functional connectivity and/or neural network and on how connectivity/network alterations occur. Here, we developed a novel analysis framework to directly investigate both neural activity and connectivity changes induced by rTMS from resting-state EEG (rsEEG) acquired in a group of subjects with a chronic disorder of imbalance, known as the mal de debarquement syndrome (MdDS). Resting-state activity in multiple functional brain areas was identified through a data-driven blind source separation analysis on rsEEG data, and the connectivity among them was characterized using a phase synchronization measure. Our study revealed that there were significant long-lasting changes in resting-state neural activity, in theta, low alpha, and high alpha bands and neural networks in theta, low alpha, high alpha and beta bands, over broad cortical areas 4 to 5 h after the last application of rTMS in a consecutive five-day protocol. Our results of rsEEG connectivity further indicated that the changes, mainly in the alpha band, over the parietal and occipital cortices from pre- to post-TMS sessions were significantly correlated, in both magnitude and direction, to symptom changes in this group of subjects with MdDS. This connectivity measure not only suggested that rTMS can generate positive treatment effects in MdDS patients, but also revealed new potential targets for future therapeutic trials to improve treatment effects. It is promising that the new connectivity measure from rsEEG can be used to understand the variability in treatment response to rTMS in brain disorders with impaired functional connectivity and, eventually, to determine individually tailored stimulation parameters and treatment procedures in rTMS.

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“…A study reviewed above suggests that frontal cordance with EEG after 1 week of right frontal (1hz) rTMS predicted clinical response similar to that seen for venlafaxine [28]. Arns et al [38] also used an EEG measure based on three different non-linear metrics at baseline as a predictor of response to rTMS (either left DLPFC 10 Hz or right DLPFC 1 Hz). This was applied concurrently with psychotherapy, and 32 % of patients were also receiving medication.…”

Section: Repetitive Transcranial Magnetic Stimulationmentioning

confidence: 99%

“…This involved correlation with EEG power in multiple bands as well as early 1-week change in EEG response (as defined above; see Cook et al [27]), but not the non-linear methods described by Arns et al [38]. This represents a large-scale study in an independent research group, and therefore is a cautionary note for the ability to predict rTMS efficacy from baseline and early changes in EEG.…”

Section: Repetitive Transcranial Magnetic Stimulationmentioning

confidence: 99%

Neural Predictors of Treatment Response in Depression

Harmer

2014

Curr Behav Neurosci Rep

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Depression is a leading cause of disability and treatment response is highly variable between patients. The current review focuses on recent findings from studies exploring neural predictors of treatment response to conventional antidepressant drugs, psychological treatment, and novel candidate interventions. Structural markers of response have revealed that decreased volume of key substrates such as the hippocampus and orbitofrontal cortex are predictive of poor response to antidepressant drug treatment, and diffusion tensor imaging offers potentially relevant information for future studies. Pretreatment measures of rostral anterior cingulate activity (from functional magnetic resonance imaging-and electroencephalogram-based approaches) have also been highlighted as a biomarker for antidepressant drug response. The relative utility of measurements taken at baseline versus early change for refining treatment in individual patients is considered. The response to novel treatments such as scopolamine, ketamine, and deep brain stimulation also offer promise for understanding targets of treatment and predictors for tailoring treatment. There is considerable overlap between neural biomarkers for different treatments although positron emission tomography metabolism in the anterior insula may offer a differential predictor of response to pharmacotherapy versus psychotherapy in depression. These insights provide important information about the potential targets and mechanisms underlying the prediction of treatment effects in depression. Future work needs to explore these different predictors between treatment arms in prospectively defined studies to evaluate whether these markers may have utility in the clinic.

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Non-linear EEG analyses predict non-response to rTMS treatment in major depressive disorder

Cited by 54 publications

References 50 publications

Neurobiological Predictors of Response to Dorsolateral Prefrontal Cortex Repetitive Transcranial Magnetic Stimulation in Depression: A Systematic Review

Neurobiological Predictors of Response to Dorsolateral Prefrontal Cortex Repetitive Transcranial Magnetic Stimulation in Depression: A Systematic Review

Lasting Modulation Effects of rTMS on Neural Activity and Connectivity as Revealed by Resting-State EEG

Neural Predictors of Treatment Response in Depression

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