Mood disorders are diseases with a social and economic burden. On the other hand, the remission rate is insufficient, even with the different types of treatment available. Therefore, the elucidation of biological treatment mechanisms and recovery processes, as well as the development of treatment optimization methods leading to precision medicine for mood disorders, is an urgent issue in psychiatry. We conducted the clinical study : Longitudinal MRI study identifying the neural substrates of remission/recovery in mood disorders (L/R study) . In this prospective study, we evaluated structural and functional MRI at three time points (before and after each treatment and follow‐up period) , individuals with major depressive disorder undergoing psychopharmacotherapy, cognitive behavioral therapy, electroconvulsive therapy, and repeated transcranial magnetic stimulation, and with healthy control. The L/R study aim to elucidate the neural circuitry associated with remission and recovery and to develop treatment optimization techniques leading to precision medicine. This paper provides an overview of the L/R study and the machine learning model for mood disorders.

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Depressed patients are highly prevalent and their social and economic losses are enormous. In recent years, brain imaging studies have made remarkable progress, and various approaches have been attempted to elucidate the pathophysiology of depressed patients and to explore new possibilities for their treatment. In Japan, a large‐scale multicenter longitudinal brain imaging study was conducted. We collected brain MRI data before and after typical treatments for depression : pharmacotherapy, cognitive‐behavioral therapy, electroconvulsive therapy, and repeated transcranial magnetic stimulation to elucidate the treatment effects and mechanisms. In this paper, we reviewed the effects of cognitive‐behavioral therapy and brain imaging alterations in depressed patients, focusing mainly on alterations in functional connectivity and dynamic functional connectivity. In the treatment of depressed patients with various symptoms, we hope that the findings of the large brain imaging study will contribute to the establishment of effective treatment methods and therapeutic strategies based on the assumption of alterations in the brain.

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Depression requires a long time for remission and recovery, and is the representative disease that causes a lot of social and financial loss. In the clinical settings, objective indices that are useful for diagnosis or the evaluation of therapeutic effectiveness are not available, and not a few non‐remission or treatment‐resistant cases exist. Therefore, it is crucial to elucidate the neural substrate of depression in the biological research of neuropsychiatry. One of the brain regions that has been drawing attention is the habenula. The habenula is assumed to be involved in the anti‐reward system as the hub adjusting the monoamine system. In recent years, it is possible to evaluate the human habenula thanks to the improvement of hardware and software in non‐invasive imaging techniques. This paper would describe the findings of the habenula in depression mainly from the human brain research. No potential conflicts of interest were disclosed.

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Transcranial direct current stimulation (tDCS) is a non‐invasive brain stimulation method that modifies neural activity in the brain by applying weak currents through electrodes placed on the scalp, and attempts are being made to develop treatments for a variety of psychiatric disorders. In such cases, it is important to select the electrode placement site based on the pathological hypothesis of the target psychiatric disorder. In addition, the integration of tDCS and digital technology has been explored in recent years. This review provides an overview of tDCS research, including expectations and notes on these trends.

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With the introduction of pulsed‐wave therapy devices, electroconvulsive therapy (ECT) has become widely practised and is now widely used in the elderly due to its high safety profile. However, the increased use of ECT in elderly patients with low pulsed‐wave therapy output and high seizure thresholds has led to an increase in the number of non‐seizure cases, which poses a major challenge in clinical practice. In addition, although many basic studies have been conducted to elucidate the mechanism of ECT’s superior immediate efficacy and effectiveness, the action mechanism of ECT remains to be elucidated. In recent years, evidence on the response to non‐seizure cases has been accumulating. We have also conducted a mechanistic study of the mechanism of action of ECT focusing on astrocytes and obtained very interesting results. In this paper, we first discuss the current most desirable response to ECT for seizure failure. We then introduce our astrocyte‐focused mechanistic studies of ECT and discuss the possibility of developing new therapeutic agents that can mimic the excellent rapid and effective effects of ECT.

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Recent advances in neuroimaging techniques have contributed to the understanding of psychiatric disorders by identifying brain activity related to symptoms and mental states. However, to elucidate causality in identified associations, intervention in brain activity is essential. Neurofeedback analyzes brain activity measured by EEG or MRI in real‐time and provides feedback to participants, promoting self‐regulation of brain activity. This not only contributes to inferring the causality but also holds promise for therapeutic applications. Unlike conventional neurofeedback, which provides one‐dimensional feedback such as the activity level of specific brain regions, decoded neurofeedback provides feedback on brain activity patterns. This allows manipulation of brain activity patterns corresponding to various mental states, greatly increasing flexibility. In this paper, we discuss the potential medical applications of this technique, using our efforts to develop decoded neurofeedback for the treatment of post‐traumatic stress disorder (PTSD) as an example.

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