Large language models in psychiatry: Opportunities and challenges.

The ability of Large Language Models (LLMs) to analyze and respond to freely written text is causing increasing excitement in the field of psychiatry; the application of such models presents unique opportunities and challenges for psychiatric applications. This review article seeks to offer a comprehensive overview of LLMs in psychiatry, their model architecture, potential use cases, and clinical considerations. LLM frameworks such as ChatGPT/GPT-4 are trained on huge amounts of text data that are sometimes fine-tuned for specific tasks. This opens up a wide range of possible psychiatric applications, such as accurately predicting individual patient risk factors for specific disorders, engaging in therapeutic intervention, and analyzing therapeutic material, to name a few. However, adoption in the psychiatric setting presents many challenges, including inherent limitations and biases in LLMs, concerns about explainability and privacy, and the potential damage resulting from produced misinformation. This review covers potential opportunities and limitations and highlights potential considerations when these models are applied in a real-world psychiatric context.

[Discharged, but where to? The Current Situation of Long Stay Patients in German Psychiatric Clinics]. / Entlassen, aber wohin? Zur aktuellen Situation der "Langlieger" in deutschen psychiatrischen Kliniken.

OBJECTIVE: The study analyses the number, characteristics and reasons for a length of stay of patients in German psychiatric clinics in excess of 6 months. METHODS: The study was implemented in the form of a nationwide online survey, which was addressed to chief physicians of psychiatric clinics. RESULTS: In the sample, 174 patients in 80 psychiatric clinics were identified who could not be discharged because no suitable follow-up services were available in the region. The majority of patients are male, often have an F2 diagnosis and exhibit aggressive behaviour during their hospital stay. CONCLUSION: To avoid inappropriate health care and prevent prolonged stays for a subgroup of mentally ill people, individual complex services should be implemented in community psychiatry.

Reactivation strength during cued recall is modulated by graph distance within cognitive maps.

Declarative memory retrieval is thought to involve reinstatement of neuronal activity patterns elicited and encoded during a prior learning episode. Furthermore, it is suggested that two mechanisms operate during reinstatement, dependent on task demands: individual memory items can be reactivated simultaneously as a clustered occurrence or, alternatively, replayed sequentially as temporally separate instances. In the current study, participants learned associations between images that were embedded in a directed graph network and retained this information over a brief 8 min consolidation period. During a subsequent cued recall session, participants retrieved the learned information while undergoing magnetoencephalographic recording. Using a trained stimulus decoder, we found evidence for clustered reactivation of learned material. Reactivation strength of individual items during clustered reactivation decreased as a function of increasing graph distance, an ordering present solely for successful retrieval but not for retrieval failure. In line with previous research, we found evidence that sequential replay was dependent on retrieval performance and was most evident in low performers. The results provide evidence for distinct performance-dependent retrieval mechanisms, with graded clustered reactivation emerging as a plausible mechanism to search within abstract cognitive maps.

Parkinsonism, Psychomotor Slowing, Negative and Depressive Symptoms in Schizophrenia Spectrum and Mood Disorders: Exploring Their Intricate Nexus Using a Network Analytic Approach.

BACKGROUND AND HYPOTHESIS: Parkinsonism, psychomotor slowing, negative and depressive symptoms show evident phenomenological similarities across different mental disorders. However, the extent to which they interact with each other is currently unclear. Here, we hypothesized that parkinsonism is an independent motor abnormality showing limited associations with psychomotor slowing, negative and depressive symptoms in schizophrenia spectrum (SSD), and mood disorders (MOD). STUDY DESIGN: We applied network analysis and community detection methods to examine the interplay and centrality (expected influence [EI] and strength) between parkinsonism, psychomotor slowing, negative and depressive symptoms in 245 SSD and 99 MOD patients. Parkinsonism was assessed with the Simpson-Angus Scale (SAS). We used the Positive and Negative Syndrome Scale (PANSS) to examine psychomotor slowing (item #G7), negative symptoms (PANSS-N), and depressive symptoms (item #G6). STUDY RESULTS: In SSD and MOD, PANSS item #G7 and PANSS-N showed the largest EI and strength as measures of centrality. Parkinsonism had small or no influence on psychomotor slowing, negative and depressive symptoms in SSD and MOD. In SSD and MOD, exploratory graph analysis identified one community, but parkinsonism showed a small influence on its occurrence. Network Comparison Test yielded no significant differences between the SSD and MOD networks (global strength p value: .396 and omnibus tests p value: .574). CONCLUSIONS: The relationships between the individual domains followed a similar pattern in both SSD and MOD highlighting their transdiagnostic relevance. Despite evident phenomenological similarities, our results suggested that parkinsonism is more independent of negative and depressive symptoms than psychomotor slowing in both SSD and MOD.

Deciphering the interplay between psychopathological symptoms, sensorimotor, cognitive and global functioning: a transdiagnostic network analysis.

BACKGROUND: Understanding the relationship between psychopathology and major domains of human neurobehavioral functioning may identify new transdiagnostic treatment targets. However, studies examining the interrelationship between psychopathological symptoms, sensorimotor, cognitive, and global functioning in a transdiagnostic sample are lacking. We hypothesized a close relationship between sensorimotor and cognitive functioning in a transdiagnostic patient sample. METHODS: We applied network analysis and community detection methods to examine the interplay and centrality [expected influence (EI) and strength] between psychopathological symptoms, sensorimotor, cognitive, and global functioning in a transdiagnostic sample consisting of 174 schizophrenia spectrum (SSD) and 38 mood disorder (MOD) patients. All patients (n = 212) were examined with the Positive and Negative Syndrome Scale (PANSS), the Heidelberg Neurological Soft Signs Scale (NSS), the Global Assessment of Functioning (GAF), and the Brief Cognitive Assessment Tool for Schizophrenia consisted of trail making test B (TMT-B), category fluency (CF) and digit symbol substitution test (DSST). RESULTS: NSS showed closer connections with TMT-B, CF, and DSST than with GAF and PANSS. DSST, PANSS general, and NSS motor coordination scores showed the highest EI. Sensory integration, DSST, and CF showed the highest strength. CONCLUSIONS: The close connection between sensorimotor and cognitive impairment as well as the high centrality of sensorimotor symptoms suggests that both domains share aspects of SSD and MOD pathophysiology. But, because the majority of the study population was diagnosed with SSD, the question as to whether sensorimotor symptoms are really a transdiagnostic therapeutic target needs to be examined in future studies including more balanced diagnostic groups.

Multimodal Associations of FKBP5 Methylation With Emotion-Regulatory Brain Circuits.

BACKGROUND: Understanding the biological processes that underlie individual differences in emotion regulation and stress responsivity is a key challenge for translational neuroscience. The gene FKBP5 is a core regulator in molecular stress signaling that is implicated in the development of psychiatric disorders. However, it remains unclear how FKBP5 DNA methylation in peripheral blood is related to individual differences in measures of neural structure and function and their relevance to daily-life stress responsivity. METHODS: Here, we characterized multimodal correlates of FKBP5 DNA methylation by combining epigenetic data with neuroimaging and ambulatory assessment in a sample of 395 healthy individuals. RESULTS: First, we showed that FKBP5 demethylation as a psychiatric risk factor was related to an anxiety-associated reduction of gray matter volume in the ventromedial prefrontal cortex, a brain area that is involved in emotion regulation and mental health risk and resilience. This effect of epigenetic upregulation of FKBP5 on neuronal structure is more pronounced where FKBP5 is epigenetically downregulated at baseline. Leveraging 208 functional magnetic resonance imaging scans during a well-established emotion-processing task, we found that FKBP5 DNA methylation in peripheral blood was associated with functional differences in prefrontal-limbic circuits that modulate affective responsivity to daily stressors, which we measured using ecological momentary assessment in daily life. CONCLUSIONS: Overall, we demonstrated how FKBP5 contributes to interindividual differences in neural and real-life affect regulation via structural and functional changes in prefrontal-limbic brain circuits.

[The German Center for Mental Health : Innovative translational research to promote prevention, targeted intervention and resilience]. / Das Deutsche Zentrum für Psychische Gesundheit : Innovative Translationsforschung zur Förderung von Prävention, zielgerichteter Intervention und Resilienz.

BACKGROUND: Due to the high disease burden, the early onset and often long-term trajectories mental disorders are among the most widespread diseases with growing significance. The German Center for Mental Health (DZPG) was established to enhance research conditions and expedite the translation of clinically relevant findings into practice. OBJECTIVE: The aim of the DZPG is to optimize mental healthcare in Germany, influence modifiable social causes and to develop best practice models of care for vulnerable groups. It seeks to promote mental health and resilience, combat the stigmatization associated with mental disorders, and contribute to the enhancement of treatment across all age groups. MATERIAL AND METHODS: The DZPG employs a translational research program that accelerates the translation of basic research findings into clinical studies and general practice. University hospitals and outpatient departments, other university disciplines, and extramural research institutions are working together to establish a collaboratively coordinated infrastructure for accelerated translation and innovation. RESEARCH PRIORITIES: The research areas encompass 1) the interaction of somatic and mental risk and resilience factors and disorders across the lifespan, 2) influencing relevant modifiable environmental factors and 3) based on this personalized prevention and intervention. CONCLUSION: The DZPG aims to develop innovative preventive and therapeutic tools that enable an improvement in care for individuals with mental disorders. It involves a comprehensive integration of experts with experience at all levels of decision-making and employs trilogue and participatory approaches in all research projects.

Measuring interpersonal trauma: Development and validation of the German version of the victimization experience schedule (VES).

OBJECTIVE: Interpersonal victimization experiences (VEs) significantly affect mental and physical health, particularly in disorders associated with life-time adversities, like fibromyalgia syndrome (FMS) and major depressive disorder (MDD). However, assessing VEs comprehensively remains challenging due to limited tools that encompass sub-traumatic events, such as bullying or discrimination, and contextual dimensions. We aimed to address this gap by validating the Victimization Experience Schedule (VES) in German, examining its reliability, and assessing VEs in clinical populations with FMS and MDD. METHODS: We investigated the relationship between VEs and clinical symptoms in individuals with FMS, MDD and healthy controls (N = 105) in a case-control study. We also analyzed correlations between different types of VEs and categories of early childhood abuse and posttraumatic-stress-disorder instruments. Additionally, we validated our findings in an independent sample of individuals with FMS (N = 97) from a clinical study. RESULTS: We observed excellent inter-rater reliability (Kw = 0.90-0.99), and VEs assessed using the VES were in alignment with subcategories of early childhood abuse. The prevalence of VEs extended beyond the categories covered by traditional survey instruments and was higher in individuals with MDD (4.0 ± 2.6) and FMS (5.9 ± 3.1) compared to controls (1.5 ± 1.7). We consistently identified a significant association between the number of VEs, the associated subjective distress, and clinical scores. Furthermore, distinct correlation patterns between VEs and clinical outcomes emerged across different cohorts. CONCLUSION: Our study emphasizes the VES's value in understanding VEs within MDD and FMS. These experiences span from traumatic to sub-traumatic and correlate with posttraumatic-stress and clinical symptoms, underscoring the VES's importance as an assessment tool.

Predictors of adherence to exercise interventions in people with schizophrenia.

Exercise interventions are nowadays considered as effective add-on treatments in people with schizophrenia but are usually associated with high dropout rates. Therefore, the present study investigated potential predictors of adherence from a large multicenter study, encompassing two types of exercise training, conducted over a 6-month period with individuals with schizophrenia. First, we examined the role of multiple participants' characteristics, including levels of functioning, symptom severity, cognitive performance, quality of life, and physical fitness. Second, we used K-means clustering to identify clinical subgroups of participants that potentially exhibited superior adherence. Last, we explored if adherence could be predicted on the individual level using Random Forest, Logistic Regression, and Ridge Regression. We found that individuals with higher levels of functioning at baseline were more likely to adhere to the exercise interventions, while other factors such as symptom severity, cognitive performance, quality of life or physical fitness seemed to be less influential. Accordingly, the high-functioning group with low symptoms exhibited a greater likelihood of adhering to the interventions compared to the severely ill group. Despite incorporating various algorithms, it was not possible to predict adherence at the individual level. These findings add to the understanding of the factors that influence adherence to exercise interventions. They underscore the predictive importance of daily life functioning while indicating a lack of association between symptom severity and adherence. Future research should focus on developing targeted strategies to improve adherence, particularly for people with schizophrenia who suffer from impairments in daily functioning.Clinical trials registration The study of this manuscript which the manuscript is based was registered in the International Clinical Trials Database, ClinicalTrials.gov (NCT number: NCT03466112, https://clinicaltrials.gov/ct2/show/NCT03466112?term=NCT03466112&draw=2&rank=1 ) and in the German Clinical Trials Register (DRKS-ID: DRKS00009804.

Intensive Longitudinal Social Sensing in Patients With Psychosis Spectrum Disorders: An Exploratory Pilot Study.

BACKGROUND: Psychosis spectrum disorders are characterized by significant alterations in social functioning, which is a major factor for patient recovery. Despite its importance, objectively quantifying the complex day-to-day social behavior in real-life settings has rarely been attempted. Here, we conducted a pilot study with wearable sensors that passively and continuously register interactions with other participants. We hypothesized that the amount and pattern of social interaction was associated with the severity of psychotic symptoms. STUDY DESIGN: We recruited 7 patients with psychosis spectrum disorders and 18 team members from a Soteria-style ward. Each participant wore a radio frequency identification badge, sending and receiving signals from nearby badges, allowing passive quantification of social interactions. In addition, symptom severity was assessed weekly by the Positive and Negative Syndrome Scale (PANSS). STUDY RESULTS: During an 11-week period, we identified 17 970 interactions among patients and staff. On average, patients spent 2.6 h per day interacting, capturing relevant aspects of daily social life. Relative daily interaction time, average interaction duration, and clustering coefficient, a measure of local network integration, were significantly associated with lower PANSS scores. Self-reported interaction time did not correlate with measured interaction time or with PANSS, indicating the importance of objective markers. CONCLUSIONS: This pilot study demonstrates the feasibility of passively recording social interaction of patients and staff at high resolution and for a long observation period in a real-life setting in a psychiatric department. We show links between quantified social interaction and psychopathology that may facilitate development and personalization of targeted treatments.

[Diagnosis and admission center : Establishment and evaluation of an integrated translational infrastructure for clinical psychiatric research]. / Diagnose- und Aufnahmezentrum : Etablierung und Evaluation einer integrierten translationalen Infrastruktur für die klinisch-psychiatrische Forschung.

The routine in-depth characterization of patients with methods of clinical and scale-based examination, neuropsychology, based on biomaterials, and sensor-based information opens up transformative possibilities on the way to personalized diagnostics, treatment and prevention in psychiatry, psychotherapy, and psychosomatics. Effective integration of the additional temporal and logistical effort into everyday care as well as the acceptance by patients are critical to the success of such an approach but there is little evidence on this to date. We report here on the establishment of the Diagnosis and Admission Center (DAZ) at the Central Institute of Mental Health (ZI) in Mannheim. The DAZ is an outpatient unit upstream of other care structures for clinical and scientific phenotyping across diagnoses as a starting point for data-driven, individualized pathways to further treatment, diagnostics or research. We describe the functions, goals, and implementation of the newly created clinical scientific translational structure, provide an overview of the patient populations it has reached, and provide data on its acceptance. In this context, the close integration with downstream clinical processes enables a better coordinated and demand-oriented allocation. In addition, DAZ enables a faster start of disorder-specific diagnostics and treatment. Since its launch in April 2021 up to the end of 2022, 1021 patients underwent psychiatric evaluation at DAZ during a pilot phase. The patient sample corresponded to a representative sample from standard care and the newly established processes were regarded as helpful by patients. In summary, the DAZ uniquely combines the interests and needs of patient with the collection of scientifically relevant data.

A primer on the use of machine learning to distil knowledge from data in biological psychiatry.

Applications of machine learning in the biomedical sciences are growing rapidly. This growth has been spurred by diverse cross-institutional and interdisciplinary collaborations, public availability of large datasets, an increase in the accessibility of analytic routines, and the availability of powerful computing resources. With this increased access and exposure to machine learning comes a responsibility for education and a deeper understanding of its bases and bounds, borne equally by data scientists seeking to ply their analytic wares in medical research and by biomedical scientists seeking to harness such methods to glean knowledge from data. This article provides an accessible and critical review of machine learning for a biomedically informed audience, as well as its applications in psychiatry. The review covers definitions and expositions of commonly used machine learning methods, and historical trends of their use in psychiatry. We also provide a set of standards, namely Guidelines for REporting Machine Learning Investigations in Neuropsychiatry (GREMLIN), for designing and reporting studies that use machine learning as a primary data-analysis approach. Lastly, we propose the establishment of the Machine Learning in Psychiatry (MLPsych) Consortium, enumerate its objectives, and identify areas of opportunity for future applications of machine learning in biological psychiatry. This review serves as a cautiously optimistic primer on machine learning for those on the precipice as they prepare to dive into the field, either as methodological practitioners or well-informed consumers.

Effects of Exercise on Structural and Functional Brain Patterns in Schizophrenia-Data From a Multicenter Randomized-Controlled Study.

BACKGROUND AND HYPOTHESIS: Aerobic exercise interventions in people with schizophrenia have been demonstrated to improve clinical outcomes, but findings regarding the underlying neural mechanisms are limited and mainly focus on the hippocampal formation. Therefore, we conducted a global exploratory analysis of structural and functional neural adaptations after exercise and explored their clinical implications. STUDY DESIGN: In this randomized controlled trial, structural and functional MRI data were available for 91 patients with schizophrenia who performed either aerobic exercise on a bicycle ergometer or underwent a flexibility, strengthening, and balance training as control group. We analyzed clinical and neuroimaging data before and after 6 months of regular exercise. Bayesian linear mixed models and Bayesian logistic regressions were calculated to evaluate effects of exercise on multiple neural outcomes and their potential clinical relevance. STUDY RESULTS: Our results indicated that aerobic exercise in people with schizophrenia led to structural and functional adaptations mainly within the default-mode network, the cortico-striato-pallido-thalamo-cortical loop, and the cerebello-thalamo-cortical pathway. We further observed that volume increases in the right posterior cingulate gyrus as a central node of the default-mode network were linked to improvements in disorder severity. CONCLUSIONS: These exploratory findings suggest a positive impact of aerobic exercise on 3 cerebral networks that are involved in the pathophysiology of schizophrenia. CLINICAL TRIALS REGISTRATION: The underlying study of this manuscript was registered in the International Clinical Trials Database, ClinicalTrials.gov (NCT number: NCT03466112, https://clinicaltrials.gov/ct2/show/NCT03466112?term=NCT03466112&draw=2&rank=1) and in the German Clinical Trials Register (DRKS-ID: DRKS00009804).

Microstructural white matter biomarkers of symptom severity and therapy outcome in catatonia: Rationale, study design and preliminary clinical data of the whiteCAT study.

The number of magnetic resonance imaging (MRI) studies on neuronal correlates of catatonia has dramatically increased in the last 10 years, but conclusive findings on white matter (WM) tracts alterations underlying catatonic symptoms are still lacking. Therefore, we conduct an interdisciplinary longitudinal MRI study (whiteCAT) with two main objectives: First, we aim to enroll 100 psychiatric patients with and 50 psychiatric patients without catatonia according to ICD-11 who will undergo a deep phenotyping approach with an extensive battery of demographic, psychopathological, psychometric, neuropsychological, instrumental and diffusion MRI assessments at baseline and 12 weeks follow-up. So far, 28 catatonia patients and 40 patients with schizophrenia or other primary psychotic disorders or mood disorders without catatonia have been studied cross-sectionally. 49 out of 68 patients have completed longitudinal assessment, so far. Second, we seek to develop and implement a new method for semi-automatic fiber tract delineation using active learning. By training supportive machine learning algorithms on the fly that are custom tailored to the respective analysis pipeline used to obtain the tractogram as well as the WM tract of interest, we plan to streamline and speed up this tedious and error-prone task while at the same time increasing reproducibility and robustness of the extraction process. The goal is to develop robust neuroimaging biomarkers of symptom severity and therapy outcome based on WM tracts underlying catatonia. If our MRI study is successful, it will be the largest longitudinal study to date that has investigated WM tracts in catatonia patients.

Extension, translation and preliminary validation of the Northoff Scale for Subjective Experience in Catatonia (NSSC).

BACKGROUND: In the last two decades, much neuroscientific research has been done on the pathomechanisms of catatonia. However, catatonic symptoms have mainly been assessed with clinical rating scales based on observer ratings. Although catatonia is often associated with strong affective reactions, the subjective domain of catatonia has simply been neglected in scientific research. METHODS: The main objective of this study was to modify, extend and translate the original German version of the Northoff Scale for Subjective Experience in Catatonia (NSSC) and to examine its preliminary validity and reliability. Data were collected from 28 patients diagnosed with catatonia associated with another mental disorder (6A40) according to ICD-11. Descriptive statistics, correlation coefficients, internal consistency and principal component analysis were employed to address preliminary validity and reliability of the NSSC. RESULTS: NSSC showed high internal consistency (Cronbach's alpha = 0.92). NSSC total scores were significantly associated with Northoff Catatonia Rating Scale (r = 0.50, p < .01) and Bush Francis Catatonia Rating Scale (r = 0.41, p < .05) thus supporting its concurrent validity. There was no significant association between NSSC total score and Positive and Negative Symptoms Scale total (r = 0.26, p = .09), Brief Psychiatric Rating Scale (r = 0.29, p = .07) and GAF (r = 0.03, p = .43) scores. CONCLUSION: The extended version of the NSSC consists of 26 items and was developed to assess the subjective experience of catatonia patients. Preliminary validation of the NSSC revealed good psychometric properties. NSSC is a useful tool for everyday clinical work to assess the subjective experience of catatonia patients.

[German version of the Northoff scale for subjective experience in catatonia (NSSC-dv) : A validated instrument for examination of the subjective experience in catatonia]. / Deutsche Version der Northoff Skala für subjektives Erleben bei Katatonie (NSSC-dv) : Ein validiertes Messinstrument zur Erfassung des subjektiven Erlebens bei Katatonie.

Patients with catatonia often show serious motor, affective and behavioral symptoms, behind which the subjective experience often remains hidden. Therefore, this study disseminates our own systematic empirical investigation of the subjective experience of catatonia patients to a German-speaking audience of clinicians and researchers. Based on current evidence and the clinical experience of the authors, the self-report questionnaire Northoff Scale for Subjective Experience in Catatonia (NSSC) was modified, extended and validated and now consists of 26 items capturing the subjective experience of catatonia in its clinical diversity. A total of 46 patients with catatonia according to the International Classification of Diseases (11th revision, ICD-11) were asked about their subjective experience during the acute phase of the disease using the NSSC. The NSSC showed high internal consistency (Cronbach's alpha = 0.91). The NSSC total score was significantly associated with the Northoff Catatonia Rating Scale (NCRS; r = 0.46; p < 0.05), the total score of the Positive and Negative Syndrome Scale (PANSS; r = 0.30; p < 0.05), the Brief Psychiatric Rating Scale (BPRS; r = 0.33; p < 0.05), and Trait Anxiety (STAI; r = 0.64; p < 0.01), supporting its validity. Preliminary validation of the NSSC revealed good psychometric properties. The NSSC is a useful instrument for routine clinical use to assess the subjective experience of patients with catatonia in order to provide tailored psychotherapeutic interventions.

The schizophrenia syndrome, circa 2024: What we know and how that informs its nature.

With new data about different aspects of schizophrenia being continually generated, it becomes necessary to periodically revisit exactly what we know. Along with a need to review what we currently know about schizophrenia, there is an equal imperative to evaluate the construct itself. With these objectives, we undertook an iterative, multi-phase process involving fifty international experts in the field, with each step building on learnings from the prior one. This review assembles currently established findings about schizophrenia (construct, etiology, pathophysiology, clinical expression, treatment) and posits what they reveal about its nature. Schizophrenia is a heritable, complex, multi-dimensional syndrome with varying degrees of psychotic, negative, cognitive, mood, and motor manifestations. The illness exhibits a remitting and relapsing course, with varying degrees of recovery among affected individuals with most experiencing significant social and functional impairment. Genetic risk factors likely include thousands of common genetic variants that each have a small impact on an individual's risk and a plethora of rare gene variants that have a larger individual impact on risk. Their biological effects are concentrated in the brain and many of the same variants also increase the risk of other psychiatric disorders such as bipolar disorder, autism, and other neurodevelopmental conditions. Environmental risk factors include but are not limited to urban residence in childhood, migration, older paternal age at birth, cannabis use, childhood trauma, antenatal maternal infection, and perinatal hypoxia. Structural, functional, and neurochemical brain alterations implicate multiple regions and functional circuits. Dopamine D-2 receptor antagonists and partial agonists improve psychotic symptoms and reduce risk of relapse. Certain psychological and psychosocial interventions are beneficial. Early intervention can reduce treatment delay and improve outcomes. Schizophrenia is increasingly considered to be a heterogeneous syndrome and not a singular disease entity. There is no necessary or sufficient etiology, pathology, set of clinical features, or treatment that fully circumscribes this syndrome. A single, common pathophysiological pathway appears unlikely. The boundaries of schizophrenia remain fuzzy, suggesting the absence of a categorical fit and need to reconceptualize it as a broader, multi-dimensional and/or spectrum construct.