Evidence points toward a relationship between longer duration of untreated psychosis (DUP) and worse long-term outcomes in patients with first episode psychosis (FEP), but the underlying neurobiology remains poorly understood. Proton magnetic resonance spectroscopy studies have reported altered hippocampus glutamatergic neurotransmission, and structural MRI as reported hippocampal atrophy that may be associated with memory impairment in schizophrenia. Here, we quantify left hippocampus glutamate (Glx) and left hippocampus subfield volumes in 54 antipsychotic-naive FEP and 41 healthy controls (HC), matched on age, sex, and parental occupation. While there were no significant group difference in Glx levels, hippocampal Glx levels were significantly higher in those who underwent a long DUP (>12 months) compared to those with a short DUP, and compared to HC. Compared to HC, FEP had significantly reduced whole hippocampus volume, as well as of CA1, CA4, granule cell layer, subiculum, and presubiculum subfields. Smaller whole hippocampal volume, as well as CA1, molecular layer, subiculum, presubiculum, and hippocampal tail volumes were significantly associated with longer DUP. However, we found no significant association between hippocampal Glx levels and hippocampal volume or subfields, suggesting that these alterations are not related, or their relationship does not follow a linear pattern. However, our results strongly suggest that one or several pathophysiological processes underlie the DUP. Importantly, our data highlight the critical need for reducing the DUP and for early pharmacological intervention with the hope to prevent structural deficits and, hopefully, improve clinical outcomes.

Early identification of children on the autism spectrum is crucial for early intervention with long-term positive effects on symptoms and skills. The need for improved objective autism detection tools is emphasized by the poor diagnostic power in current tools. Here, we aim to evaluate the classification performance of acoustic features of the voice in children with autism spectrum disorder (ASD) with respect to a heterogeneous control group (composed of neurotypical children, children with Developmental Language Disorder [DLD] and children with sensorineural hearing loss with Cochlear Implant [CI]). This retrospective diagnostic study was conducted at the Child Psychiatry Unit of Tours University Hospital (France). A total of 108 children, including 38 diagnosed with ASD (8.5 ± 0.25 years), 24 typically developing (TD; 8.2 ± 0.32 years) and 46 children with atypical development (DLD and CI; 7.9 ± 0.36 years) were enrolled in our studies. The acoustic properties of speech samples produced by children in the context of a nonword repetition task were measured. We used a Monte Carlo cross-validation with an ROC (Receiving Operator Characteristic) supervised k-Means clustering algorithm to develop a classification model that can differentially classify a child with an unknown disorder. We showed that voice acoustics classified autism diagnosis with an overall accuracy of 91% [CI95%, 90.40%-91.65%] against TD children, and of 85% [CI95%, 84.5%–86.6%] against an heterogenous group of non-autistic children. Accuracy reported here with multivariate analysis combined with Monte Carlo cross-validation is higher than in previous studies. Our findings demonstrate that easy-to-measure voice acoustic parameters could be used as a diagnostic aid tool, specific to ASD.

Psychotic disorders are disabling clinical syndromes characterized by widespread alterations in cortical information processing. Disruption of frontoparietal network (FPN) connectivity has emerged as a common footprint across the psychosis spectrum. Our goal was to characterize the static and dynamic resting‐state functional connectivity (FC) of the FPN in antipsychotic‐naïve first‐episode psychosis (FEP) subjects. We compared the static FC of the FPN in 40 FEP and 40 healthy control (HC) subjects, matched on age, sex, and socioeconomic status. To study the dynamic FC, we measured quasiperiodic patterns (QPPs) that consist of infraslow spatioemporal patterns embedded in the blood oxygen level‐dependent signal that repeats over time, exhibiting alternation of high and low activity. Relative to HC, we found functional hypoconnectivity between the right middle frontal gyrus and the right middle temporal gyrus, as well as the left inferior temporal gyrus and the left inferior parietal gyrus in FEP (p < .05, false discovery rate corrected). The correlation of the QPP with all functional scans was significantly stronger for FEP compared to HC, suggesting a greater impact of the QPPs to intrinsic brain activity in psychotic population. Regressing the QPP from the functional scans erased all significant group differences in static FC, suggesting that abnormal connectivity in FEP could result from altered QPP. Our study supports that alterations of cortical information processing are not a function of psychotic chronicity or antipsychotic medication exposure and may be regarded as trait specific. In addition, static connectivity abnormality may be partly related to altered brain network temporal dynamics.