Personalized treatments have become a key focus in translational psychiatry and psychology. To provide individualized interventions for people suffering from mental health conditions, it is crucial to enhance our understanding of both the etiology and pathophysiology of psychiatric disorders. Identifying neural networks associated with mental illnesses and disordered psychological processes in each clinical situation is essential. A comprehensive understanding of mental disorders requires insight into both the underlying biological deficiencies and the maladaptive psychological processes and behavioral dysfunctions. This is achievable through translational research, which bridges fundamental research findings with clinical applications, thereby contributing to the overall improvement of healthcare and the industry.

The DSM-5 is expanding its classification system to include biological factors, which may help develop new comprehensive models to improve our understanding of the root causes of psychiatric illnesses and enhance treatment possibilities. To improve the effectiveness of prevention and intervention initiatives, it is essential to understand response variability, cognitive function, comorbidities, and treatment-resistant cases more deeply. While traditional psychiatric taxa remain useful for diagnostic purposes, transdiagnostic approaches to psychopathology are emerging that transcend standard diagnostic boundaries. Therefore, understanding the key biopsychosocial processes underlying psychiatric illnesses is crucial for driving advancements in treatment.

An example is the NIH`s Research Domain Criteria (RDoC) initiative, which has made significant progress in understanding mental health and illness by examining evidence from different levels of dysfunction in basic psychological and biological systems.

The RDoC system takes a whole-dimensional approach to analyzing human behavior, encompassing both typical and atypical functioning, and utilizes evidence from biological, behavioral, and self-report studies.

Despite notable breakthroughs in understanding mental health disorders in recent years, effective therapies with high response rates are still lacking. Addressing this gap requires continued research and innovation to translate these insights into practical, effective treatments.

Therefore, in this Research Topic, we aim to highlight studies that emphasize the pathophysiology of mental health disorders and the application of translational research to develop precise interventions. The primary goal is to identify behavioral and biological correlates of mental health conditions and explore how these correlates can predict disease risk with high sensitivity and specificity.

We highly encourage studies utilizing machine learning techniques with extensive datasets, as well as consensus papers, systematic reviews, and meta-analyses.

Research that utilizes behavioral data and investigates the neurological underpinnings of psychological processes, signs, and symptoms contributing to the comprehension of
mental health disorders is particularly welcome. Additionally, studies focusing on transdiagnostic approaches to mental health problems are also encouraged.

Through this collection of works, we hope to better define therapeutic approaches for mental health conditions based on both fundamental and translational research, thereby contributing to the advancement of clinical research.

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Frontiers in Human Neuroscience

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