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Background: Electroretinographic dysfunction is observed in psychosis, with a-wave and b-wave amplitudes potentially serving as biomarkers. Insulin resistance (IR) and childhood trauma (CT) have also been associated with psychosis-spectrum disorders, particularly schizophrenia. Electroretinographic dysfunction in early-course psychosis (EP) lacks exploration. This case-control exploratory study aimed to understand electroretinographic dysfunction in EP and its relationship with IR and CT. Methods: The study involved healthy controls (n=13) and EP individuals (n=14) and included photopic and scotopic flash-electroretinography (fERG), blood collection for IR assessment, and the Childhood Trauma Questionnaire (CTQ). Data were analyzed using SPSS v.29.0. Case-control differences across fERG conditions were explored using repeated-measures ANCOVA (3 flash conditions X 2 groups) adjusted for gender and age. Sub-analyses included Fisher’s, Mann-Whitney, partial correlations, and logistic and linear regressions. Results: Compared to controls, EP participants showed (1) lower photopic a-wave and b-wave amplitudes, specifically in the left eye and under the P1 condition, (2) greater odds for IR, and (3) higher CTQ scores. IR was associated with a higher CTQ score and a lower P2b amplitude. A higher CTQ score was associated with lower P2b amplitude in the left eye when adjusting for its interacting effect with IR. Conclusion: These findings suggest lower photopic a-wave and b-wave amplitudes, IR, and CT are explanatory markers in EP. CT may dysregulate the hypothalamic-pituitary-adrenal axis, increasing the risk of experiencing later-life psychosis. IR might be a biomarker in psychosis, contributing to electroretinographic dysfunction and neurodegeneration of cone post-synaptic cells. Further investigations are needed.

Clozapine, a drug effective in treatment resistant schizophrenia, can modulate the brain’s electrical activity as measured by an electroencephalogram (EEG). Past reviews have focused on synthesizing literature related to epileptiform activity or rate of seizures in clozapine treated individuals. The aim of this review was to determine whether clozapine’s mediated effects on measurements related to neural oscillations can inform its therapeutic effects. Here, literature pertaining to studies that implemented pre-post designed investigations of clozapine and measured frequency characteristics of neural oscillations in individuals with schizophrenia were reviewed. The synthesis of findings suggests that while clozapine is associated with alterations in all neural oscillations, slower waves (delta and theta) are consistently increased in power by clozapine. We then further discuss potential mechanisms that may underlie these effects of clozapine. Future research can implement the findings of this review to motivate hypothesis-driven investigations into clozapine responsiveness biomarkers.

Introduction: Optical coherence tomography (OCT) is used to study retinal structure in schizophrenia. Changes in retinal structure, especially the retinal nerve fiber layer (RNFL) has been correlated with psychotic disorders. Measurement variability is a concern since there are various generations of OCT devices. We investigated the inter- and intra-device agreement of macular thickness between spectral domain (SD−OCT) and swept source−OCT (SS−OCT), and compared macula and peripapillary group differences in schizophrenia using SS−OCT. Methods: Macular OCT thickness was obtained for schizophrenia (SZ, n = 30) and healthy controls (HC, n = 22) subjects using SD−OCT (Heidelberg Spectralis) and SS−OCT (DRI Topcon Triton). Peripapillary thickness was obtained using SS−OCT. RNFL, ganglion cell-inner plexiform complex (GCL+), RNFL plus GCL+ (GCL++), and macular thickness were collected. Clinical and cognitive data were gathered. All statistical analyses were performed using R software. Results: There was excellent inter-scanner agreement for GCL + and GCL++ with ICC’s between r = 0.92−0.99. Good-to-excellent intra-scanner (OD vs OS) agreement was present except for macular RNFL in the SS−OCT device. No significant peripapillary group differences were identified. Poorer GAF scores were correlated with thinner macular layers and thinner overall peripapillary retinal layer. Greater mania symptoms were associated with smaller peripapillary GCL + thickness (r=-0.43, p = 0.03). Poor overall cognition (Brief Assessment of Cognition in Schizophrenia) was associated with smaller overall peripapillary retinal thickness (r = 0.36, p = 0.02). Conclusion: While there is RNFL variability, GCL + and GCL++ are comparable between scanners SD−OCT and SS−OCT. Given that RNFL thinning is strongly implicated in psychotic disorders, the use of OCT scanners should not be interchanged due to increased RNFL measurement variability.

Instead of matching neuroimaging to static clinical targets, it is currently possible to use dynamic biobehavioral markers of cognition, functioning, behavior, and symptoms captured through a person’s smartphone. This paper reviews the published literature linking neuroimaging and smartphone data to understand the feasibility, methods, and potential of using smartphone sensing (often called digital phenotyping) as a target for neuroimaging. On June 30, 2020, a literature search was conducted on PubMed and PsycINFO for studies utilizing neuroimaging and smartphones tools. We excluded EEG focused studies, conference proceedings and abstracts. A snowball approach was applied to further locate papers. We utilized the NIMH’s Research Domain Criteria (RDoC) framework to organize results. 262 publications uncovered by the search were screened, and 14 papers were included in the final analysis. All studies differed in terms of the type of data collected from smartphones, type of neuroimaging used, areas of the brain measured, and population studied. The average duration before or after neuroimaging and smartphone assessments was 39 days. While it was not possible to directly compare studies, a majority of the included reports were classified under the Negative Valence Systems category in the RDoC framework. All studies reported statistically significant relationships between the information collected via the digital tool and the brain scans, and support feasibility of this method. The current literature connecting smartphone data and neuroimaging is nascent but holds the potential to better understand the ability of digital tools to inform brain structure and/or function. Although the protocols and studies from this search were heterogenous, results suggest feasibility and practicality of this work.