Neuroimaging has been a mainstay of psychiatric research for three decades, but in recent years, there is a growing sense among investigators that the field is approaching an inflection point, with the potential for generating fundamental new insights into the biological mechanisms underlying depression, schizophrenia, autism spectrum disorders, and other conditions. The past decade has seen a dramatic change in the sophistication of tools and approaches to map the molecular, cellular, and systems-level components of the brain in animal models, with novel tools providing insights that might not have been imagined 20 years ago. Further, the human brain, once viewed as an enigmatic black box, is now being mapped in increasingly fine detail, thanks to rapid advancements in neuroimaging techniques. These innovations, ranging from precision functional mapping to the burgeoning fields of microglial imaging, connectome fingerprinting, and in vivo assessments of synapse function, are providing us with tools that not only enhance our ability to visualize the brain’s complex architecture but also offer new insights into the neurobiological underpinnings of psychiatric disorders. As the techniques available for both animal and human studies continue to evolve, they are shedding light on the intricate web of neural circuits, cellular interactions, and molecular processes that drive both typical and atypical behavior, including brain and behavior variations that are associated with risk for mental health challenges.

In this Special Issue of Neuropsychopharmacology Reviews, we sought to capture this excitement by providing a snapshot of how recent advances in neuroimaging are on the cusp of transforming our understanding of the biological mechanisms underlying psychiatric disease states, providing an overview of the current state of the field, the challenges it faces, and future opportunities. Advances in precision functional mapping—enabled in part by a new approach to dense sampling and serial imaging in longitudinal studies—have revealed previously underappreciated, functionally relevant individual idiosyncrasies in the organization of functional networks in the healthy brain and are beginning to do the same for individuals with psychiatric diagnoses. In parallel, the Adolescent Brain Cognitive Development Study, the Human Connectome Project, UK Biobank, and other “big data” consortium studies are generating new insights into the neurobiological correlates of psychiatric disorders across the lifespan.

Rather than attempt to review the current state of the field for each major psychiatric disorder—and mindful of the fact that excellent reviews of this kind are available elsewhere—contributors to this Special Issue were invited to focus instead on one of three broad thematic areas. The first of these themes considers how recent technical and methodological innovations in human research are redefining psychiatric neuroimaging. Precision functional mapping, for example, has enabled researchers to delineate the topography of functional networks within individual human brains with unprecedented precision, and is beginning to integrate task and resting-state fMRI data to uncover trait-like features of brain organization relevant to psychiatric conditions.

Neuroimaging continues to advance our understanding of developmental processes in psychiatry, particularly the importance of plasticity early in life and its implications for mental health interventions. By mapping out how environmental factors influence brain development, this research offers new insights into windows of opportunity for optimizing treatments and for preventing psychiatric disorders before they emerge. Other contributions review recent advances in diffusion-weighted imaging of structural connectivity, microglial imaging, synaptic imaging, and computational psychiatry, among others.

This section also highlights how big data approaches are transforming neuroimaging, enabling the analysis of vast datasets to uncover subtle patterns that would be undetectable in smaller studies. However, analyzing large-scale multi-site datasets poses special challenges—especially those related to the integration of data acquired from multiple scanners and correcting for associated artifacts. At the same time, large-scale studies also present unique opportunities to address novel questions that are not possible in smaller datasets. Nonetheless, there is a significant role to be played in psychiatric neuroimaging for many different kinds of studies, both big and wide, and smaller and deep. As such, several reviews in this issue consider the relative strengths and weaknesses of different types of data, how to optimize analyses of both large and smaller datasets, how to generate reproducible findings using large-scale datasets, and provide practical recommendations for leveraging these datasets effectively, emphasizing the challenges of data harmonization and the importance of working with diverse, multisite cohorts.

A second major theme of this issue focuses on clinical applications of neuroimaging, particularly how these technologies are being employed to rethink how we diagnose psychiatric conditions and develop new approaches to selecting treatments. SV2A PET and pharmacological imaging approaches are now being used to characterize brain responses to specific drugs and to measure synaptic density in vivo, offering a direct assessment of synapse function in conditions such as depression, schizophrenia, autism, and other disorders. Multiple contributions in this issue provide a comprehensive overview of these techniques, including their development, technical challenges, and clinical applications, such as in the context of ketamine treatment for depression.

Neuroimaging is also playing an increasingly central role in the development and optimization of neuromodulation therapies. These techniques are being used together to refine treatments such as deep brain stimulation (DBS) and transcranial magnetic stimulation (TMS) for treatment-resistant depression and obsessive-compulsive disorder. By integrating neuroimaging with neuromodulation, researchers are beginning to uncover the circuit mechanisms underlying these disorders and their treatments, paving the way for more targeted and effective therapies.

Computational neuroimaging is another area of significant clinical potential. Computational models are now being used to understand how varied treatments engage not just symptoms but specific behaviors and the computational processes that give rise to them. Others are developing computational models to predict treatment outcomes and guide clinical decision-making, offering new avenues for personalizing psychiatric care. This section on clinical applications also includes perspectives from the National Institutes of Health (NIH), educators, and industry leaders, providing a broad view of the current landscape and future directions for clinical neuroimaging in psychiatry.

A third and final theme of this issue highlights the indispensable role of animal models in advancing neuroimaging research in psychiatry. These models are crucial for understanding the neural mechanisms underlying psychiatric disorders and for developing and testing new treatments. Two-photon imaging and open-source tools for endoscopic calcium imaging in mice are being used to study neuronal activity in real-time, providing insights into the neural circuits involved in psychiatric conditions. New optical toolkits for neurotransmitter and G-protein-coupled receptor (GPCR) imaging are also discussed, showcasing their potential to revolutionize our understanding of neurotransmission in psychiatric disorders. Additionally, non-human primate studies are revealing new insights into the mechanisms underlying therapeutic neuromodulation such as DBS and TMS, bridging the gap between basic research and clinical applications.

Together, the reviews featured in this issue provide a timely overview of the current state of the field and offer a glimpse into the future of psychiatric neuroimaging. They chart a course for future innovations that could fundamentally change the way we diagnose and treat psychiatric disorders. We hope this Special Issue will inspire continued progress in this rapidly evolving field, ultimately leading to more effective and personalized treatment approaches for the individuals who suffer from these conditions.