Diseases associated with functional abnormalities of the central dopamine neurons include Parkinson’s disease, restless legs syndrome, Tourette syndrome, attention‐deficit hyperactivity disorder (ADHD) , dependence on stimulants and other substances, and psychosis due to using psychoactive substances. Accordingly, there are many other diseases besides schizophrenia. Here, we review previous animal experiments using symptom models of Parkinson’s disease, ADHD, substance dependence, and schizophrenia, and reconsider the dopamine hypothesis of schizophrenia. An overview of these dopamine‐related disorders reveals that the symptoms of each disorder are different and cannot be defined solely by dopamine activity level, which may prove the low disease specificity between dopamine neurons dysfunction and each dopamine‐related disorder.

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The classical biomedical research approach begins with modeling the etiology of a disease, such as a genomic mutation, in an animal model to elucidate the pathology, develop new diagnostic methods, and explore new therapeutic strategies. However, genomic studies of psychiatric disorders such as schizophrenia have revealed that they cannot be explained by a few genomic mutations, making it difficult to take this approach. Although clinical studies have identified a variety of environmental factors, the translation of those environmental factors into animal models is not straightforward. On the other hand, monoamines are targets of drug therapy and their importance and involvement in psychiatric disorders are clear. Yet, how the various monoamines act on the various receptors to regulate brain function are not well understood. In order to advance animal model research under these circumstances, I suggest an approach for psychiatric disorders in animal models by clarifying the monoaminergic functions on neural circuits and molecular synaptic cellular mechanisms, modeling symptoms of psychiatric disorders based on monoamine functions, and mapping such neural bases to etiological candidates.

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Despite recent advances in biological psychiatric research, antidepressants based on the monoamine hypothesis are still the mainstay of treatment for depression, despite their inadequate efficacy rates, and there are still no useful biomarkers for diagnosis, leading to frequent misdiagnosis. Therefore, it is desirable to develop new treatment and diagnostic methods for depression based on a new pathological hypothesis that can replace the monoamine hypothesis. One new pathological hypothesis that is attracting attention is the neurogenesis hypothesis, which proposes that treatment increases adult hippocampal neurogenesis, which has been reduced by depression. Although this hypothesis has been established by basic research, it is still unclear whether hippocampal neurogenesis is actually decreased in depressed patients because neurogenesis cannot be detected in living humans. In this article, we first provide an overview of adult hippocampal neurogenesis, and then introduce research findings that support the neurogenesis hypothesis of depression and point out some of its problems. Finally, we discuss ways to overcome the problems with the neurogenesis hypothesis.

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Schizophrenia has many pathological backgrounds with noted heterogeneity. One such pathological candidate is related to autoimmunity and autoantibodies. Discovery of autoantibodies against the nervous system in autoimmune encephalitis paved the way for the concept of autoimmune psychosis, and autoantibodies against the nervous system have been reported in schizophrenia. This study reviews novel autoantibodies in schizophrenia, including anti‐NCAM1 and anti‐NRXN1 autoantibodies, which are synaptic autoantibodies discovered by us and their discovery approaches. Moreover, we discuss how autoantibodies form the pathogenesis of schizophrenia. Clinical research to improve autoantibody pathologies is crucial for these autoantibody pathologies to move beyond hypotheses and be translated into actual clinical practice; furthermore, it is important to integrate these treatments into daily practice.

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Delirium is a common disorder encountered in psychiatric clinical practice, particularly prevalent among elderly patients in hospitals, associated with poor outcome. Early detection and intervention are crucial, yet often overlooked, leading to inadequate treatment. While delirium screening tools like the Confusion Assessment Method (CAM) are generally considered to have high sensitivity and specificity, their sensitivity significantly decreases in busy clinical settings. On the other hand, delirium has long been known to be detectable by EEG, with characteristic findings of low‐frequency waves known as diffuse slowing seen from all electrodes. However, specialized knowledge is required for electrode placement and interpretation, and the equipment itself is large, making it difficult to use as a screening tool. The authors developed their own algorithm, ”bispectral EEG (BSEEG) ,” focusing on distinctive features of delirium and using brain waves obtained from a limited number of electrodes to detect delirium and predict its outcomes. This paper introduces an overview of previous research, its development, and recent findings.

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Novel approaches to prevent delirium are needed. Metformin has been reported to improve age‐related disorders, including dementia, and to lower mortality. Furthermore, anti‐inflammatory drugs attenuate inflammation, which is thought to be a risk of delirium. Thus, we hypothesized that metformin or anti‐inflammatory drug exposure would be associated with reduced prevalence of delirium and lower risk of mortality. We conducted retrospective cohort studies using data from our previous studies. It was found that a history of metformin use reduced the risk of delirium and the risk of 3‐year mortality in patients with a type 2 diabetes mellitus. It was also found that a history of NSAIDs use tended to reduce the risk of delirium and decreased risk of one‐year mortality. These data showed the potential benefit of metformin and NSAIDs on delirium risk and mortality.

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Non‐pharmacologic interventions have taken the lead in terms of the level of evidence for intervention methods for delirium. However, they have limitations because delirium is a condition with a distinct biological basis. Evidence for pharmacological interventions is accumulating, with antipsychotics for treatment and approaches to melatonin neurotransmission and orexin neurotransmission for prevention. Delirium is a sign of poor prognosis, increases the risk of falls and the development of dementia, and increases the medical and economic burden, so the importance of its prevention is increasingly recognized. Pharmacological interventions evolve in this direction, and therapeutic strategies need to develop with the evolving hypothesis of the pathomechanism of delirium.

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This article aims to outline the hypothetical framework and empirical evidence in the epigenetic investigation of delirium pathophysiology. Delirium, prevalent in the elderly, remains poorly understood in terms of pathophysiology. Our research investigates how aging‐related epigenetic changes, particularly in DNA methylation, influence the pathophysiological mechanism of delirium. We initially used blood samples from Grady Trauma Project to examine the correlation between cytokine gene methylation and age, discovering a negative correlation with the TNF‐alpha gene methylation, together with an increase in RNA expression with age. Subsequent analysis of brain tissue obtained from resected brain tissue through the treatment of medication refractory epilepsy patients revealed this trend in glial components, not neurons, indicating an age‐related decrease in TNF‐alpha gene methylation in glia, facilitating increased inflammation in older brain. Further, comparisons between delirious and non‐delirious patients showed maintained methylation decline in the delirious group, indicating a potential role in delirium onset. Additionally, we found increased DNA methylation of neurotrophic factor genes such as BDNF in the elderly, implying a vulnerability to delirium due to reduced neurotrophic support. Finally, a genome‐wide approach identified differences in DNA methylation between delirious and non‐delirious groups, with significant pathways related to immune response and cell activation. These findings suggest a crucial role for epigenetic changes, especially in DNA methylation, in the pathophysiology of delirium.

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Mismatch negativity and gamma‐band oscillations are well known EEG indices that are expected to be useful in investigating the pathophysiology of schizophrenia. These EEG indices have been repeatedly reported to be impaired in patients with schizophrenia and have been shown to be associated with clinical symptoms. Since these EEG indices can also be measured in animals, they are being used in basic research using animal models. In addition, a series of large‐scale MRI studies have recently reported structural changes in gray matter and white matter in the cerebrum in patients with schizophrenia. In order to advance research to the next level, it is necessary to integrate the results of these large‐scale studies with the neurophysiological findings obtained to date to understand the pathophysiology of schizophrenia as a disorder of the global neural network. The clarification of dysfunction of the global neural network in patients with schizophrenia will make it possible to conduct animal experiments to study the pathophysiology for the disease, which is difficult to do in humans, and will serve as a basis for the development of new treatments.

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