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Diffusion tensor imaging (DTI) studies show widespread white matter abnormalities in schizophrenia, but it is difficult to directly relate these parameters to biological processes. Neurite orientation dispersion and density imaging (NODDI) is geared toward biophysical characterization of white matter microstructure, but only few studies have leveraged this technique to study white matter alterations. We recruited 42 schizophrenia patients (30 antipsychotic-naïve and 12 currently untreated) and 42 matched controls in this prospective study. We assessed the orientation dispersion index (ODI) and extracellular free water (FW) using singleshell DTI data before and after a 6-week trial of risperidone. Longitudinal data were available for 27 patients. Voxelwise analyses showed significantly increased ODI in the posterior limb of the internal capsule in unmedicated patients (242 voxels; x = −24; y = 6; z = 6; p < 0.01; α < 0.04), but no alterations in FW. Whole brain measures did not reveal alterations in ODI but a 6.3% trend-level increase in FW in unmedicated SZ (t = −1.873; p = 0.07). Baseline ODI was negatively correlated with subsequent response to antipsychotic treatment (r = −0.38; p = 0.049). Here, we demonstrated altered fiber complexity in medication-naïve and unmedicated patients with a schizophrenia spectrum illness. Lesser whole brain fiber uniformity was predictive of poor response to treatment, suggesting this measure may be a clinically relevant biomarker. Interestingly, we found no significant changes in NODDI indices after short-term treatment with risperidone. Our data show that biophysical diffusion models have promise for the in vivo evaluation of brain microstructure in this devastating neuropsychiatric syndrome.

We introduce DeepNash, an autonomous agent that plays the imperfect information game Stratego at a human expert level. Stratego is one of the few iconic board games that artificial intelligence (AI) has not yet mastered. It is a game characterized by a twin challenge: It requires long-term strategic thinking as in chess, but it also requires dealing with imperfect information as in poker. The technique underpinning DeepNash uses a game-theoretic, model-free deep reinforcement learning method, without search, that learns to master Stratego through self-play from scratch. DeepNash beat existing state-of-the-art AI methods in Stratego and achieved a year-to-date (2022) and all-time top-three ranking on the Gravon games platform, competing with human expert players.

BackgroundPathologic alterations in resting-state brain activity patterns exist among individuals with Parkinson’s disease (PD). Since physical exercise alters resting-state brain activity in non-PD populations and improves PD symptoms, we assessed the acute effect of exercise on resting-state brain activity in exercise-trained individuals with PD.Material/MethodsResting-state functional magnetic resonance imaging (fMRI) was collected twice for 17 PD participants at the conclusion of an exercise intervention. The acute effect of exercise was examined for PD participants using the amplitude of low frequency fluctuation (ALFF) before and after a single bout of exercise. Correlations of clinical variables (i.e., PDQ-39 quality of life and MDS-UPDRS) with ALFF values were examined for the exercise-trained PD participants.ResultsAn effect of acute exercise was observed as an increased ALFF signal within the right ventromedial prefrontal cortex (PFC), left ventrolateral PFC, and bilaterally within the substantia nigra (SN). Quality of life was positively correlated with ALFF values within the vmPFC and vlPFC.ConclusionsGiven the role of the SN and PFC in motor and non-motor symptoms in PD, the acute increases in brain activity within these regions, if repeated frequently over time (i.e., exercise training), may serve as a potential mechanism underlying exercise-induced PD-specific clinical benefits.