Author Archives: samweiss

Dynamic functional network connectivity (dFNC) analysis is a widely used approach for studying brain function and offering insight into how brain networks evolve over time. Functional dysconnectivity between different brain regions has been reported in schizophrenia, yet the neural mechanisms behind it remain elusive. This manuscript presents a complementary novel...

Post-traumatic stress disorder (PTSD) and alcohol use disorder (AUD) are highly comorbid and individual differences in response to stress suggest resilient and susceptible populations. The current review discusses the advantages of using predator odor stressors to better understand PTSD pathophysiology and neurobiological mechanisms associated with stress reactivity and subsequent increases...

Control over internal representations requires the prioritization of relevant information and suppression of irrelevant information. We used TMS while participants either prioritized or suppressed information during a working memory task. We found evidence to support the idea that the frontoparietal theta network prioritizes internally maintained representations and alpha oscillations in...

This review emphasizes the significant therapeutic potential of neuroactive steroids in modulating TLR signaling pathways, particularly in addressing inflammatory processes associated with neuropsychiatric disorders. It advances our understanding of the complex interplay between neuroactive steroids and immune responses, paving the way for personalized treatment strategies tailored to individual needs and...

This study explored how PTSD symptoms impact future substance use, including tobacco, alcohol, and cannabis, utilizing causal forests to identify what factors are most important in stratifying this relationship. Findings revealed a significant association between PTSD symptoms and heightened tobacco and alcohol use, and that variables for lifetime cigarette use,...

The ALICBCT tool offers an open-source, fully automated method for accurately placing landmarks in cone-beam CT scans, leveraging a novel AI approach for landmark detection with high precision and swift processing times, validated for clinical and research use.

This study developed and tested a novel, interpretable AI-based classifier for assessing the severity of alveolar bone defects in CLP patients using 3D surface models and 2D CNNs, achieving high accuracy and providing visual explanations for its decisions.