Precuneus functioning differentiates first-episode psychosis patients during the fantasy movie Alice in Wonderland.

BACKGROUND: While group-level functional alterations have been identified in many brain regions of psychotic patients, multivariate machine-learning methods provide a tool to test whether some of such alterations could be used to differentiate an individual patient. Earlier machine-learning studies have focused on data collected from chronic patients during rest or simple tasks. We set out to unravel brain activation patterns during naturalistic stimulation in first-episode psychosis (FEP). METHOD: We recorded brain activity from 46 FEP patients and 32 control subjects viewing scenes from the fantasy film Alice in Wonderland. Scenes with varying degrees of fantasy were selected based on the distortion of the 'sense of reality' in psychosis. After cleaning the data with a novel maxCorr method, we used machine learning to classify patients and healthy control subjects on the basis of voxel- and time-point patterns. RESULTS: Most (136/194) of the voxels that best classified the groups were clustered in a bilateral region of the precuneus. Classification accuracies were up to 79.5% (p = 5.69 × 10-8), and correct classification was more likely the higher the patient's positive-symptom score. Precuneus functioning was related to the fantasy content of the movie, and the relationship was stronger in control subjects than patients. CONCLUSIONS: These findings are the first to show abnormalities in precuneus functioning during naturalistic information processing in FEP patients. Correlational findings suggest that these alterations are associated with positive psychotic symptoms and processing of fantasy. The results may provide new insights into the neuronal basis of reality distortion in psychosis.

Anti-neuronal anti-bodies in patients with early psychosis.

It may be challenging to distinguish autoimmune encephalitis associated with anti-neuronal autoantibodies from primary psychiatric disorders. Here, serum was drawn from patients with a first-episode psychosis (n=70) or a clinical high-risk for psychosis (n=6) and controls (n=34). We investigated the serum prevalence of 24 anti-neuronal autoantibodies: IgG antibodies for anti-N-methyl-d-aspartate-type glutamate receptor (anti-NMDAR), glutamate and γ-aminobutyric acid alpha and beta receptors (GABA-a, GABA-b), alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPA), glycine receptor (GlyR), metabotropic glutamate receptor 1 and 5 (mGluR1, mGluR5), anti-Tr/Delta/notch-like epidermal growth factor-related receptor (DNER), contactin-associated protein-like 2 (CASPR2), myelin oligodendrocyte glycoprotein (MOG), glutamic acid decarboxylase-65 (GAD65), collapsin response mediator protein 5/crossveinless-2 (CV2), aquaporin-4 (AQP4), anti-dipeptidyl-peptidase-like protein-6 (DPPX), type 1 anti-neuronal nuclear antibody (ANNA-1, Hu), Ri, Yo, IgLON5, Ma2, zinc finger protein 4 (ZIC4), Rho GTPase-activating protein 26, amphiphysin, and recoverin, as well as IgA and IgM for dopamine-2-receptor (DRD2). Anti-NMDA IgG antibodies were positive with serum titer 1:320 in one patient with a clinical high risk for psychosis. He did not receive a diagnosis of encephalitis after comprehensive neurological evaluation. All other antineuronal autoantibodies were negative and there were no additional findings with immunohistochemistry of brain issues.