Synchronized transcranial magnetic stimulation for posttraumatic stress disorder and comorbid major depression

Philip, Noah S.; Aiken, Emily; Kelley, Mary E.; Burch, William John Nobbs; Waterman, Laurie A.; Holtzheimer, Paul E.

doi:10.1016/j.brs.2019.06.010

Cited by 22 publications

(34 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Panel c shows how the classifier assigned pretreatment recordings. Note that 19 out of 28 cases of pretreatment were assigned to the "sham" group studies to date have primarily focused on comparing patients with healthy controls (reviewed in [2], and integration of EEG into TMS studies is in its earliest stages [18]. Thus, prospective replication of our results will be required before they can be implemented more broadly.…”

Section: Discussionmentioning

confidence: 99%

Changes in functional connectivity after theta-burst transcranial magnetic stimulation for post-traumatic stress disorder: a machine-learning study

Zandvakili

Swearingen

Philip

2020

Eur Arch Psychiatry Clin Neurosci

Self Cite

View full text Add to dashboard Cite

Intermittent theta burst stimulation (iTBS) is a novel treatment approach for post-traumatic stress disorder (PTSD), and recent neuroimaging work indicates that functional connectivity profiles may be able to identify those most likely to respond. However, prior work has relied on functional magnetic resonance imaging, which is expensive and difficult to scale. Alternatively, electroencephalography (EEG) represents a different approach that may be easier to implement in clinical practice. To this end, we acquired an 8-channel resting-state EEG signal on participants before (n = 47) and after (n = 43) randomized controlled trial of iTBS for PTSD (ten sessions, delivered at 80% of motor threshold, 1,800 pulses, to the right dorsolateral prefrontal cortex). We used a cross-validated support vector machine (SVM) to track changes in EEG functional connectivity after verum iTBS stimulation. We found that an SVM classifier was able to successfully separate patients who received active treatment vs. sham treatment, with statistically significant findings in the Delta band (1-4 Hz, p = 0.002). Using Delta coherence, the classifier was 75.0% accurate in detecting sham vs. active iTBS, and observed changes represented an increase in functional connectivity between midline central/occipital and a decrease between frontal and central regions. The primary limitations of this work are the sparse electrode system and a modest sample size. Our findings raise the possibility that EEG and machine learning may be combined to provide a window into mechanisms of action of TMS, with the potential that these approaches can inform the development of individualized treatment methods.

show abstract

Section: Discussionmentioning

confidence: 99%

Changes in functional connectivity after theta-burst transcranial magnetic stimulation for post-traumatic stress disorder: a machine-learning study

Zandvakili

Swearingen

Philip

2020

Eur Arch Psychiatry Clin Neurosci

Self Cite

View full text Add to dashboard Cite

show abstract

“…[10,11]). Studies using varied stimulation frequencies, sites of stimulation, and stimulation approaches (e.g., combination with symptom provocation or psychotherapy) have consistently indicated efficacy [12][13][14][15][16].…”

Section: Introductionmentioning

confidence: 99%

One-year clinical outcomes following theta burst stimulation for post-traumatic stress disorder

Petrosino

Wout-Frank

Aiken

et al. 2019

Neuropsychopharmacol.

Self Cite

View full text Add to dashboard Cite

Theta burst transcranial magnetic stimulation (TBS) is a potential new treatment for post-traumatic stress disorder (PTSD). We previously reported active intermittent TBS (iTBS) was associated with superior clinical outcomes for up to 1-month, in a sample of fifty veterans with PTSD, using a crossover design. In that study, participants randomized to the active group received a total of 4weeks of active iTBS, or 2-weeks if randomized to sham. Results were superior with greater exposure to active iTBS, which raised the question of whether observed effects persisted over the longer-term. This study reviewed naturalistic outcomes up to 1-year from study endpoint, to test the hypothesis that greater exposure to active iTBS would be associated with superior outcomes. The primary outcome measure was clinical relapse, defined as any serious adverse event (e.g., suicide, psychiatric hospitalization, etc.,) or need for retreatment with repetitive transcranial magnetic stimulation (rTMS). Forty-six (92%) of the initial study's intent-to-treat participants were included. Mean age was 51.0 ± 12.3 years and seven (15.2%) were female. The group originally randomized to active iTBS (4-weeks active iTBS) demonstrated superior outcomes at one year compared to those originally randomized to sham (2-weeks active iTBS); log-rank ChiSq = 5.871, df = 1, p = 0.015; OR = 3.50, 95% CI = 1.04-11.79. Mean days to relapse were 296.0 ± 22.1 in the 4-week group, and 182.0 ± 31.9 in the 2-week group. When used, rTMS retreatment was generally effective. Exploratory neuroimaging revealed default mode network connectivity was predictive of 1-year outcomes (corrected p < 0.05). In summary, greater accumulated exposure to active iTBS demonstrated clinically meaningful improvements in the year following stimulation, and default mode connectivity could be used to predict longer-term outcomes.

show abstract

“…Nowadays, TMS has been widely used in clinical experiments and research in the fields of neurology, neuroscience, psychiatry, rehabilitation, psychocognitive science, and sports medicine [81]. It has a good therapeutic effect in depression, obsessive-compulsive disorder, schizophrenia, and peripheral nerve rehabilitation [82].…”

Section: Transcranial Magnetic Stimulation (Tms)mentioning

confidence: 99%

Biomedical Applications of Electromagnetic Detection: A Brief Review

Huang

Xie

2021

Biosensors

View full text Add to dashboard Cite

This paper presents a review on the biomedical applications of electromagnetic detection in recent years. First of all, the thermal, non-thermal, and cumulative thermal effects of electromagnetic field on organism and their biological mechanisms are introduced. According to the electromagnetic biological theory, the main parameters affecting electromagnetic biological effects are frequency and intensity. This review subsequently makes a brief review about the related biomedical application of electromagnetic detection and biosensors using frequency as a clue, such as health monitoring, food preservation, and disease treatment. In addition, electromagnetic detection in combination with machine learning (ML) technology has been used in clinical diagnosis because of its powerful feature extraction capabilities. Therefore, the relevant research involving the application of ML technology to electromagnetic medical images are summarized. Finally, the future development to electromagnetic detection for biomedical applications are presented.

show abstract

Synchronized transcranial magnetic stimulation for posttraumatic stress disorder and comorbid major depression

Cited by 22 publications

References 15 publications

Changes in functional connectivity after theta-burst transcranial magnetic stimulation for post-traumatic stress disorder: a machine-learning study

Changes in functional connectivity after theta-burst transcranial magnetic stimulation for post-traumatic stress disorder: a machine-learning study

One-year clinical outcomes following theta burst stimulation for post-traumatic stress disorder

Biomedical Applications of Electromagnetic Detection: A Brief Review

Contact Info

Product

Resources

About