Volatility-Level Inference Indexes Psychosis Spectrum Symptoms Independent of Age in Transdiagnostic Help-Seeking Youth
Soltanzadeh, M.; Ameis, S. H.; Charlton, C. E.; Cleverley, K.; Courtney, D. B.; Dickie, E. W.; Felsky, D.; Foussias, G.; Goldstein, B.; Griffiths, J. D.; Kozloff, N.; Lazar, D.; Narajos, A.; Nikolova, Y.; Ogundipe, O. A.; Phi, T.; Polillo, A.; Putterman, C.; Quilty, L. C.; Shah, D.; Voineskos, A. N.; Wang, W.; Wang, Z.; Diaconescu, A. O.; TAY Cohort Study Team,
Show abstract
Background. Psychosis spectrum symptoms (PSS) are prevalent in youth and are associated with increased risk for psychotic disorder, suicidality, and functional impairment. Computationally, PSS may stem from altered predictive coding of basic sensory surprises and environmental volatility. Formalized as hierarchical precision-weighted prediction errors (pwPEs), this altered processing is a proposed mechanistic substrate of aberrant perceptual inference across disorders, including psychosis-risk populations. While the auditory mismatch negativity (MMN) provides an electrophysiological index of pwPEs, it remains unknown if distinct hierarchical pwPE components distinguish youth who endorse PSS. Methods. A sample of 131 participants (PSS-=66, PSS+=65; ages 11-24) from the ongoing Toronto Adolescent and Youth (TAY-CAMH) Cohort study were stratified by PSS status using the PRIME Screen-Revised and were assessed for their psychosocial functioning. 64-channel EEG was recorded during an auditory oddball paradigm with stable and volatile phases. A hierarchical Bayesian model applied to the stimulus stream generated trajectories of low-level sensory and high-level volatility-related pwPEs. Alongside standard phase-averaged event-related potentials (ERPs), Bayesian trajectories derived model-based ERPs. Results. Replicating prior findings in non-clinical controls, stable-phase MMN significantly exceeds volatile-phase MMN and lower psychosocial functioning was associated with reduced volatile-phase MMN amplitude. Age significantly modulated oddball MMN and unweighted prediction errors ({delta}1, {delta}2). Group differences between PSS+ and PSS- were statistically significant for volatility-level pwPE ({epsilon}3), peaking at ~180 ms Peri-Stimulus Time (pFWE-peak =.024). Conclusions. Independent of age-related developmental effects, volatility-level pwPE learning ({epsilon}3) constitutes a more sensitive EEG marker associated with PSS status in help-seeking youth than low-level sensory pwPE.
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