Introduction The concordance of the Montreal cognitive assessment (MoCA) with more comprehensive neuropsychological measures remains unclear. This study examined the individual MoCA domains with more comprehensive and commonly used neuropsychological measures to determine the degree of overlap. Methods Data included individuals seen in an outpatient neurology clinic specializing in neurodegenerative disease who were administered the MoCA and also underwent neuropsychological assessment (n = 471). A principal component analysis with varimax rotation was completed using the MoCA domain scores and comprehensive neuropsychological evaluation measures. Results Four factors emerged accounting for 55.6% of the variance: (1) visuospatial/executive functioning; (2) memory; (3) attention; and (4) language. The individual MoCA domain scores demonstrated high factor loadings with standard neuropsychological measures purported to measure similar cognitive constructs. Discussion These findings provide empirical validation for the MoCA domain classifications, lending further support for the use of the MoCA as a cognitive screen that reflects similar constructs as those measured by a comprehensive battery.

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There is increasing evidence that schizophrenia (SZ) and bipolar disorder (BD) share a number of cognitive, neurobiological, and genetic markers. Shared features may be most prevalent among SZ and BD with a history of psychosis. This study extended this literature by examining reinforcement learning (RL) performance in individuals with SZ (n = 29), BD with a history of psychosis (BD+; n = 24), BD without a history of psychosis (BD-; n = 23), and healthy controls (HC; n = 24). RL was assessed through a probabilistic stimulus selection task with acquisition and test phases. Computational modeling evaluated competing accounts of the data. Each participant's trial-by-trial decision-making behavior was fit to 3 computational models of RL: (a) a standard actor-critic model simulating pure basal ganglia-dependent learning, (b) a pure Q-learning model simulating action selection as a function of learned expected reward value, and (c) a hybrid model where an actor-critic is "augmented" by a Q-learning component, meant to capture the top-down influence of orbitofrontal cortex value representations on the striatum. The SZ group demonstrated greater reinforcement learning impairments at acquisition and test phases than the BD+, BD-, and HC groups. The BD+ and BD- groups displayed comparable performance at acquisition and test phases. Collapsing across diagnostic categories, greater severity of current psychosis was associated with poorer acquisition of the most rewarding stimuli as well as poor go/no-go learning at test. Model fits revealed that reinforcement learning in SZ was best characterized by a pure actor-critic model where learning is driven by prediction error signaling alone. In contrast, BD-, BD+, and HC were best fit by a hybrid model where prediction errors are influenced by top-down expected value representations that guide decision making. These findings suggest that abnormalities in the reward system are more prominent in SZ than BD; however, current psychotic symptoms may be associated with reinforcement learning deficits regardless of a Diagnostic and Statistical Manual of Mental Disorders (5th Edition; American Psychiatric Association, 2013) diagnosis.