Attempts to image brain function began in the 19th century, even before the beginnings of psychoanalysis, through the now famous work of the Sardinian Angelo Mosso.1 He selected patients with partial cranial bone loss from trauma and measured their brain temperature and pulsation amplitudes during various activities. He invented the plethysmograph, which demonstrated blood flow changes to the brain during certain functions. Over a century ago, Sigmund Freud (“Jenseits des Lustprinzips,” 1920) recognized the limitations of contemporary biology in explaining psychic phenomena but hoped future biological advances, especially in neuroscience. Such advances began to emerge only in the 1960s with the analysis of human brain perfusion through scintillation.2 Since then, human body imaging has evolved, allowing analysis of cortical activation through blood flow and metabolism with methods like PET-CT and functional MRI (fMRI).

Nowadays, neuroimaging plays a central role in neuroscience, enabling detailed in vivo studies of brain function with high anatomical resolution. These methods, associated with the evolution of neuroanatomy, neurophysiology, and computer science, now allow for precise anatomical reference of specific cortical functions across behavioral domains.3 Thus, in the same regions of structural changes associated with dementia found by Alois Alzheimer4 or Arnold Pick,5 functional changes can now be seen in vivo and much earlier than the anatomical findings. These techniques have transformed the concepts of functional segregation and integration from theoretical constructs into empirically demonstrable phenomena. The evolution of functional imaging not only involves the representation of cortical activity in behavioral domains, during activation, or the predominance of the default-mode network (DMN). Advances in neuropharmacology and radiopharmacy currently allow the analysis of the presence of different molecular targets such as amyloid and tau deposits, in addition to the pharmacodynamics of receptors, in daily practice and clinical research, such as pre and postsynaptic dopaminergic receptors, dopamine (DA) transporters (DAT), GABA and serotonin receptors, and even amino acid metabolism.

In general, the primary objective of molecular neuroimaging and nuclear medicine exams is to confirm or exclude the presence of a degenerative condition. When this is present, the secondary objective is to direct a syndromic and pathological diagnosis. However, what is the secondary objective when the degenerative condition is excluded? Can nuclear medicine help further? Due to the evolution of diagnostic definitions in psychiatry, different deficits in neurotransmitter systems have begun to be observed in subpopulations within the same diagnosis and the opposite: deficits in the same neurotransmitter systems in different nosological entities. This gave rise to a discussion on nosological classifications in psychiatry, with criticism to the DSM, with Van Praag's publications since the 1990s standing out.6 These advances in neuroscience have led us to a paradox: the previously well-defined organic-functional dilemma, central to psychiatric debates in the 20th century, has become a simplistic dichotomy with imprecise boundaries. Psychiatry evolved from a discipline divided by technological and conceptual limitations to an integrative approach that recognizes the interaction between biological, psychological, and social factors. The term has lost practical relevance due to the modern understanding that all mental disorders have a neurobiological basis, even if not consistently detectable with current methods.

It may be an illusion to imagine that biomarkers will be specifically linked to a heterogeneous diagnostic group created from different observations of symptoms or complaints. Biological disorders, such as serotonin dysregulation, are not linked to complete syndromes (eg, major depression), but to specific symptoms or phenotypes, such as aggression or anxiety. The clinical application of psychoradiology is sometimes possible for differential diagnosis, for example, separating bipolar disorder from unipolar depression, but its leading utility may involve other aspects, such as monitoring the progression of the disease, assessing, for example, brain changes over time in schizophrenia. It can also be used to identify which patients will respond to medications or therapies, leading to personalized treatment based on individualized neuroimaging patterns, which can be called "precision psychiatry" The main challenges of psychoradiology are accessibility, cost, and the lack of standardization for routine clinical integration. Advances in artificial intelligence and machine learning are expected to enhance psychoradiology by enabling predictive analyses based on large neuroimaging data sets, ultimately translating research findings into routine clinical practice.

Particular attention has been directed toward the frontal lobes, especially the prefrontal cortex, which is critically involved in executive functioning, decision-making, and goal-directed behavior. This region acts as a hub, integrating exteroceptive and interoceptive inputs with emotional and motivational states mediated by the limbic system. It enables flexible behavioral responses tailored to contextual demands, supports future-oriented planning independent of immediate environmental stimuli, and facilitates adaptation to novel or unpredictable conditions. The psychological processes governed by the prefrontal cortex represent the final stage of neurodevelopment, maturing fully only during adolescence. Additionally, circuit-based frameworks have become central to understanding the pathophysiology of major psychiatric disorders. Within a given syndrome, one or more components of a functional circuit may be impaired.

Severe conditions such as schizophrenia are better explained by disruptions in cortico-subcortical circuits than by damage to discrete cortical regions. A key clinical insight is that circuit-based disorders tend to be more amenable to pharmacological intervention than neurological disorders resulting from focal lesions. This is because circuits involve neurotransmitter pathways, receptor subtypes, and second-messenger systems that are accessible to pharmacological modulation. Also, rather than seeking a pathognomonic imaging fingerprint for DSM diagnoses, neuroimaging should be valued as a complementary tool to identify potential organic contributors, support differential diagnosis, and inform more individualized treatment planning. Incorporating SPECT or PET findings into clinical decision-making may be beneficial in selected cases, particularly those that are diagnostically complex or refractory to standard treatment approaches. While additional research is needed to further establish its role, nuclear and molecular neuroimaging represents a promising avenue for supporting more personalized and biologically informed psychiatric care. The following sections will approach these themes in an individualized manner regarding the most prevalent psychiatric syndromes.

Many psychiatric disorders are linked to disrupted glucose metabolism, and early dysregulation can occur at the initial disease stages.7 Thus, imaging glucose uptake holds the potential for early diagnosis and describing the course of various mental illnesses. FDG-PET has revealed metabolic alterations in disorders like schizophrenia and depression.8, 9, 10 However, most studies have focused on the static baseline levels of glucose uptake, overlooking the metabolic dynamics following stimuli or interventions, which are essential for understanding neuronal circuitry and cognitive symptoms.11

Functional PET (fPET) with [18F]FDG is a recent advancement that tracks stimulus-driven metabolic dynamics in a single scan. By infusing the [18F]FDG radiotracer at a constant rate, changes in glucose uptake are reflected as altered slopes in time-activity curves (TACs).12 This innovation enhances sensitivity by minimizing intersession variability.13 Studies have shown the ability of FDG-fPET to detect minute-scale metabolic activations during sensory12,14,15 and higher-cognitive tasks,16, 17, 18 with a potential for tracking rapid dynamics close to fMRI.19