Functional brain networks in clinical high-risk for bipolar disorder and psychosis.

Abnormal connectivity in the brain has been linked to the pathophysiology of severe mental illnesses, including bipolar disorder and schizophrenia. The current study aimed to investigate large-scale functional networks and global network metrics in clinical high-risk for bipolardisorder (CHR-BD, n = 25), clinical high-risk for psychosis (CHR-P, n = 30), and healthy controls (HCs, n = 19). Help-seeking youth at CHR-BD and CHR-P were recruited from the early intervention program at Dokuz Eylul University, Izmir, Turkey.

Retina in Clinical High-Risk and First-Episode Psychosis.

Background And Hypothesis: Abnormalities in the retina are observed in psychotic disorders, especially in schizophrenia.

Study Design: Using spectral-domain optical coherence tomography, we investigated structural retinal changes in relatively metabolic risk-free youth with clinical high-risk (CHR, n = 34) and first-episode psychosis (FEP, n = 30) compared with healthy controls (HCs, n = 28).

Study Results: Total retinal macular thickness/volume of the right eye increased in FEP (effect sizes, Cohen's d = 0.

Automated linguistic analysis in youth at clinical high risk for psychosis.

Identifying individuals at clinical high risk for psychosis (CHRP) is crucial for preventing psychosis and improving the prognosis for schizophrenia. Individuals at CHR-P may exhibit mild forms of formal thought disorder (FTD), making it possible to identify them using natural language processing (NLP) methods. In this study, speech samples of 62 CHR-P individuals and 45 healthy controls (HCs) were elicited using Thematic Apperception Test images.

Effort-based decision-making in ultra-high-risk for psychosis and bipolar disorder.

Background: Effort-based decision-making has been proposed as a potential mechanism contributing to transdiagnostic motivational deficits in psychotic disorder and bipolar disorder. However, very limited information is available about deficits in effort-cost-decision-making in the early stages of psychotic disorder and no study has investigated effort allocation deficits before the onset of bipolar disorder. Our aim was to investigate effort-based-decision-making in ultra-high-risk for psychosis (UHR-P) and bipolar disorder (UHR-BD).

Computational analysis of linguistic features in speech samples of first-episode bipolar disorder and psychosis.

Background: In recent years, automated analyses using novel NLP methods have been used to investigate language abnormalities in schizophrenia. In contrast, only a few studies used automated language analyses in bipolar disorder. To our knowledge, no previous research compared automated language characteristics of first-episode psychosis (FEP) and bipolar disorder (FEBD) using NLP methods.