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Transcranial direct current stimulation (tDCS) is an emerging therapeutic tool for treating posttraumatic stress disorder (PTSD). Prior studies have shown that tDCS responses are highly individualized, thus necessitating the individualized optimization of treatment configurations. To date, an effective tool for predicting tDCS treatment outcomes in patients with PTSD has not yet been proposed. Therefore, we aimed to build and validate a tool for predicting tDCS treatment outcomes in patients with PTSD. Forty-eight patients with PTSD received 20 min of 2 mA tDCS stimulation in position of the anode over the F3 and cathode over the F4 region. Non-responders were defined as those with less than 50% improvement after reviewing clinical symptoms based on the Clinician-Administered DSM-5 PTSD Scale (before and after stimulation). Resting-state electroencephalograms were recorded for 3 min before and after stimulation. We extracted power spectral densities (PSDs) for five frequency bands. A support vector machine (SVM) model was used to predict responders and non-responders using PSDs obtained before stimulation. We investigated statistical differences in PSDs before and after stimulation and found statistically significant differences in the F8 channel in the theta band (p = 0.01). The SVM model had an area under the ROC curve (AUC) of 0.93 for predicting responders and non-responders using PSDs. To our knowledge, this study provides the first empirical evidence that PSDs can be useful biomarkers for predicting the tDCS treatment response, and that a machine learning model can provide robust prediction performance. Machine learning models based on PSDs can be useful for informing treatment decisions in tDCS treatment for patients with PTSD.

Brain electrical stimulation, particularly non-invasive brain stimulation (NIBS) techniques such as transcranial electrical stimulation (tES), have emerged as a promising treatment for various psychiatric disorders, including depression, anxiety, and post-traumatic stress disorder. tES techniques, such as transcranial direct current stimulation (tDCS), transcranial alternating current stimulation (tACS), and transcranial random noise stimulation (tRNS), are cost-effective and safe interventions that are designed to affect neuronal circuits in the brain using various modalities. Although tES has shown effectiveness in the treatment of psychiatric disorders, there is a lack of comprehensive papers that consider its clinical implications. Therefore, this review aims to evaluate the clinical implications of tES and provide practical guidance for the treatment of psychiatric illnesses. Moreover, this review provides an overview of tES techniques and their mechanisms of action and summarizes recent clinical studies that have examined the use of tES for psychiatric disorders. [ABSTRACT FROM AUTHOR]

Vagus nerve stimulation (VNS) has been approved as an adjunctive treatment for epilepsy and depression. As the progress of VNS treatment for these neuropsychiatric disorders continues, its applications have expanded to a wide range of conditions, including inflammatory diseases to cognitive dysfunctions. The branches of the vagal nerves directly or indirectly innervate the anatomical structures implicated in these neuropsychiatric conditions, which has led to promising results regarding the effectiveness of VNS. Previous studies investigating the effectiveness of VNS have mostly utilized invasive forms of stimulation. However, current preclinical and clinical research indicates that non-invasive forms of VNS, such as transcutaneous vagus nerve stimulation, hold the promise for treating various neuropsychiatric conditions. This review aims to delve into relevant clinical studies of VNS in various illness states, different methods of VNS, and the potential mechanisms underlying the therapeutic effects in these neuropsychiatric conditions. [ABSTRACT FROM AUTHOR]