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Early identification of individuals with clinical high risk (CHR) for psychosis relies heavily on subjective assessments, necessitating the exploration of objective markers to enhance diagnostic accuracy. This study aimed to evaluate the temporal integration window (TIW) of sensory processing in individuals with CHR, first-episode schizophrenia (FES), and healthy controls (HC) to assess its utility as an objective neuropsychological marker for identifying CHR individuals. Ninety participants (30 CHR, 30 FES, 30 HC) completed temporal order judgment of visual and auditory(TOJV and TOJA) and simultaneity judgment of the flash-beep (SJF) tasks. Unisensory (visual and auditory) thresholds and TIW were measured and compared across groups. Cognitive function was assessed using the MATRICS Consensus Cognitive Battery (MCCB). The associations between cognition with unisensory thresholds and TIW were analyzed. The TIW was significantly prolonged in both the CHR (336.95 ± 108.30 ms) and FES (413.15 ± 121.27 ms) groups compared to the HC group (229.95 ± 54.53 ms) (P < 0.05). Visual and auditory thresholds and TIW were negatively correlated with information processing speed and attention (both P < 0.05). Notably, TIW effectively discriminates across three groups. Compared to HC, each 50 ms increase in TIW was associated with a 2.3-fold increased risk of CHR (95% CI 1.27-4.28, P = 0.01; AUC = 0.81, 95% BCa CI 0.65-0.91). Similarly, it was associated with a 3.3-fold increased risk of FES (95% CI 1.78-6.34, P < 0.01; AUC = 0.94, 95% BCa CI 0.81-0.99). No correlations were observed between TIW and symptom severity in FES and CHR. Prolonged TIW in multisensory integration may serve as a promising objective neuropsychological marker for identifying individuals at CHR for psychosis.
Pubmed ID: 41198698
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Multi paradigm numerical computing environment and fourth generation programming language developed by MathWorks. Allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages, including C, C++, Java, Fortran and Python. Used to explore and visualize ideas and collaborate across disciplines including signal and image processing, communications, control systems, and computational finance.
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