Neurocomputational modelling for predicting outcomes and characterizing neurocognitive pathophysiology in youth at clinical high risk for psychosis

COEX 

Schizophrenia is a debilitating psychiatric disorder that imposes significant socio-economic burdens on individuals and society. Thus, early identification of those at "clinical high risk" (CHR) of developing schizophrenia is imperative. While interventions at this stage can potentially thwart the onset of schizophrenia or related psychotic disorders, even those CHR patients who do not go on to develop schizophrenia frequently continue to experience high symptom burden and functional impairment. Thus, there is a compelling need to elucidate additional prognostic indicators for this cohort to prioritize treatments.

Rationale and Study Aims: A promising avenue is employing neurophysiological measures, specifically, event-related brain potentials (ERPs). Two particular ERPs, the mismatch negativity (MMN) and the N400 semantic priming effect, have been shown to predict conversion to psychosis (1) and decline in psychosocial functioning 1-year later (2), respectively in CHR individuals. Despite the potential of these ERP biomarkers, their neural mechanisms remain largely unknown, thus limiting their clinical utility.

Methods: In this study, we address this by fitting a connectome-based neural mass model (CNMM) (3) to both auditory MMN and N400 datasets in a group of N=47 CHR individuals, whose symptoms and general social and role functioning was assessed at baseline and 1-year later (4,5). In this CNMM model, neural dynamics at each source are described by Jansen-Rit (JR) equations (6,7), which encapsulate neural dynamics across three populations: pyramidal neurons, excitatory, and inhibitory interneurons, forming a circuit with one positive and one negative feedback loop. After fitting the CNMM model to participants’ grand averaged ERPs across the two datasets, we extracted the local gain parameters (C1-C4) and used them to predict changes in symptoms and psychosocial functioning.

Results: In the MMN task, we found that increased excitation via increased excitatory-to-pyramidal connectivity, was observed in the primary auditory, middle cingulate, and inferior frontal areas, and was associated with an increase in positive symptoms one year later (r= 0.53, p = 0.019). In the N400 priming dataset, heightened disinhibition characterized by a decrease in inhibitory-to-pyramidal and an increase in pyramidal-to-excitatory connectivity—across the occipital, precuneus, middle cingulate, and inferior frontal regions was linked to diminished social and role functioning after one year (r= 0.42, p = 0.031; r= 0.48, p = 0.012), respectively. These results provide support for a neurophysiological model of the psychosis prodrome, linking excitatory-inhibitory mechanisms, brain connectivity, clinical symptoms, and long-term functional outcomes.

References:

1. Hamilton HK, Roach BJ, Bachman PM, Belger A, Carrión RE, Duncan E, et al. Mismatch Negativity in Response to Auditory Deviance and Risk for Future Psychosis in Youth at Clinical High Risk for Psychosis. JAMA Psychiatry. 2022 Aug 1;79(8):780–9.
2. Lepock JR, Ahmed S, Mizrahi R, Gerritsen CJ, Maheandiran M, Drvaric L, et al. Relationships between cognitive event-related brain potential measures in patients at clinical high risk for psychosis. Schizophr Res. 2020 Dec;226:84–94.
3. Momi D, Wang Z, Griffiths JD. TMS-evoked responses are driven by recurrent large-scale network dynamics. eLife. 2023 Apr 21;12:e83232.
4. Charlton CE, Lepock JR, Hauke DJ, Mizrahi R, Kiang M, Diaconescu AO. Atypical prediction error learning is associated with prodromal symptoms in individuals at clinical high risk for psychosis. Schizophrenia. 2022 Nov 25;8(1):1–10.
5. Lepock JR, Sanches M, Ahmed S, Gerritsen CJ, Korostil M, Mizrahi R, et al. N400 event-related brain potential index of semantic processing and two-year clinical outcomes in persons at high risk for psychosis: A longitudinal study. Eur J Neurosci. 2023 Jun 29;
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