Gregory A. Miller

We develop Adaptive Network Dynamics (AND) theory, positing that dynamic configurations of brain networks instantiate cognitive systems that interact in context-dependent ways, enabling complex response profiles. Responses to social exclusion unfold dynamically, yet existing stage-based models do not specify how neural systems support these temporal dynamics. Applying AND theory, we propose a falsifiable model of normative cognitive and brain responses to peer exclusion during adolescence, when the brain undergoes maturational reorganization amid social reorientation towards peers. We characterize three systems critical for adaptive responding to social exclusion: social threat response, threat regulation, and response selection, and identify connectivity patterns that support them. This model: (1) reinterprets multistage exclusion processing as interacting trajectories of cognitive subprocesses; (2) grounds these processes in testable predictions about neural function, accounting for individual differences in need to belong and rejection sensitivity; and (3) offers a framework for understanding how the brain navigates complex social interactions.

Hormonal fluctuations across the menstrual cycle exert broad influences on brain function and emotional regulation, and evidence linking these changes to anxiety remains inconsistent. This variability may reflect the frequent treatment of anxiety as a single construct, despite substantial evidence that it comprises multiple dimensions. The present study identified a specific relationship in how menstrual cycling status moderates the impact of several internalizing dimensions, including anxiety, depression, and negative affect, on amygdala–hippocampus functional connectivity during a 2-back working memory task. Using data from the Human Connectome Project (N = 389), participants were categorized into three groups based on self-reported menstrual status: follicular phase, luteal phase, or oral contraceptive users. Functional connectivity between the right amygdala and right hippocampus was estimated from fMRI data using the Yale Brain Atlas. Hierarchical regression analyses revealed an interaction between anxious arousal and cycling status. This effect persisted with other predictors already in the model, indicating specificity for that type of anxiety. Among naturally cycling participants, higher anxious arousal was associated with stronger amygdala–hippocampus connectivity. The relationship was reversed in oral contraceptive users, for whom higher anxious arousal predicted lower connectivity. These findings suggest that endogenous hormonal cycling modulates the neural coupling of limbic regions implicated in emotion and memory, with particular sensitivity to somatic anxiety. Understanding how menstrual cycle status shapes anxiety-related neural dynamics can clarify inconsistencies in the literature and advance precision approaches to studying internalizing disorders in women.

Within-disorder heterogeneity complicates mapping neurobiological features of psychopathology to DSM conceptualizations. The present study explored patterns of diagnostic classification errors among disorders with commonly co-occurring features to examine this heterogeneity. We conducted classification analyses with the UCLA Phenomics Study database using a support vector classifier to differentiate disorders via whole-brain task-based functional connectivity, predicting that model misclassifications would provide insight about brain connectivity characteristics shared across disorders. We also explored whether symptoms and specific brain networks could account for misclassification rates. The classification model performed better than chance (44% accuracy, p = .01) and revealed that misclassification of schizophrenia (SCZ) as bipolar disorder (BD; 38%) and BD as SCZ (36%) was symmetrical. Attention-deficit/hyperactivity disorder (ADHD) was misclassified as BD at the highest rate (46%) and higher than the converse (17%). SCZ and ADHD were misclassified least (SCZ as ADHD 15%; ADHD as SCZ 22%). Considerable variance in misclassification of SCZ as BD (R2 = .83) and BD as SCZ (R2 = .71) could be accounted for by symptoms of both SCZ and BD. Permutation testing revealed disorder- and network-specific effects, with certain networks improving classification accuracy and others hindering it for specific disorders. An approach focused on classification errors replicated known disorder overlap, producing errors in the expected configuration. Further, it identified clinical and neural features within and across diagnostic categories that contribute to disorder misclassification and within-disorder heterogeneity. This approach may facilitate neurobiologically informed phenotypic differentiation within diagnostic groups.

The Psychological Clinical Science Accreditation System (PCSAS) accredits PhD programs in clinical psychology that adhere to the clinical science training model. An evaluation of the psychometric properties of a key judgment in review of applicant programs was undertaken. Results show that program reviewers’ judgments of the career outcomes of program graduates, a fundamental criterion in evaluating the success of a program applying for PCSAS accreditation, demonstrate high reliability and validity, in turn providing evidence that PCSAS-accredited programs achieve what they claim to achieve. Their convergence on central features of successful clinical science training underscores what it means to function as a psychological clinical scientist. In turn, the expertise of psychological clinical scientists can be invaluable in a wide range of research and practice settings, providing diverse career choices for PCSAS-accredited program graduates.