Dopamine (DA) has been implicated in modulating multiple cognitive control processes, including the robust maintenance of task sets and memoranda in the face of distractors (cognitive stability) and, conversely, the ability to switch task sets or update the contents of working memory when it is advantageous to do so (cognitive flexibility). In humans, the limited specificity of available pharmacological probes has posed a challenge for understanding the mechanisms by which DA, acting on multiple receptor families across the PFC and striatum, differentially influences these cognitive processes. Using a within-subject, placebo-controlled design, we contrasted the impact of two mechanistically distinct DA drugs, tolcapone (an inhibitor of catechol- O-methyltransferase [COMT], a catecholamine inactivator) and bromocriptine (a DA agonist with preferential affinity for the D2 receptor), on the maintenance and switching of task rules. Given previous work demonstrating that drug effects on behavior are dependent on baseline DA tone, participants were stratified according to genetic polymorphisms associated with cortical (COMT Val158Met) and striatal (Taq1A) DA system function. Our results were partially consistent with an inverted-U-shaped relationship between tolcapone and robust rule maintenance (interaction with COMT genotype) and between bromocriptine and cued rule switching (interaction with Taq1A genotype). However, when task instructions were ambiguous, a third relationship emerged to explain drug effects on spontaneous task switching (interaction of COMT genotype and bromocriptine). Together, this pattern of results suggests that the effects of DA drugs vary not only as a function of the DA system component upon which they act but also on subtle differences in task demands and context.

Aberrant brain dynamics putatively characterize bipolar disorder (BD) and schizophrenia (SCZ). Previous studies often adopted a state discretization approach when investigating how individuals recruited recurring brain states. Since multiple brain states are likely engaged simultaneously at any given moment, focusing on the dominant state can obscure changes in less prominent but critical brain states in clinical populations. To address this limitation, we introduced a novel framework to simultaneously assess brain state engagement for multiple rain states, and we examined how brain state engagement differs in patients with BD or SCZ compared to healthy controls (HC). Using task-based data from the Human Connectome Project, we applied nonlinear manifold learning and K-means clustering to identify four recurring brain states. We then examined how the engagement and transition variability of these four states differed between patients with BD, SCZ, and HC across two other international, open-source datasets. Comparing these measures across groups revealed significantly altered state transition variability, but not engagement, across all four states in individuals with BD and SCZ during both resting-state and task-based fMRI. In our post hoc and exploratory analysis, we also observed associations between state transition variability and age as well as avolition. Our results suggest that disrupted state transition variability affects multiple brain states in BD and SCZ. By studying several brain states simultaneously, our framework more comprehensively reveals how brain dynamics differ across individuals and in psychiatric disorders.

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Citation metrics influence academic reputation and career trajectories. Recent works have highlighted flaws in citation practices in the Neurosciences, such as the under-citation of women. However, self-citation rates—or how much authors cite themselves—have not yet been comprehensively investigated in the Neurosciences. This work characterizes self-citation rates in basic, translational, and clinical Neuroscience literature by collating 157,001 articles from 63 journals between the years 2000-2020. In analyzing over eight million citations, we demonstrate four key findings: 1) since 2000, self-citation rates of Last Authors are increasing relative to those of First Authors, 2) the odds of “highly self-citing” articles from authors in the Americas are 2.65, 2.17, 1.35, and 1.43 times those of authors affiliated with Africa, Asia, Europe, and Oceania, 3) men tend to cite themselves more than women early in their careers but less later in their careers, and 4) self-citation rates vary across three major fields (Neurology, Neuroscience, Psychiatry) and 13 subfields. Our characterization of self-citation provides insight into citation practices that shape the perceived influence of authors in the Neurosciences, which in turn may impact what type of scientific research is done and who gets the opportunity to do it.