Network modeling of dynamic brain interactions predicts emergence of neural information that supports human cognitive behavior.

How cognitive task behavior is generated by brain network interactions is a central question in neuroscience. Answering this question calls for the development of novel analysis tools that can firstly capture neural signatures of task information with high spatial and temporal precision (the "where and when") and then allow for empirical testing of alternative network models of brain function that link information to behavior (the "how"). We outline a novel network modeling approach suited to this purpose that is applied to noninvasive functional neuroimaging data in humans. We first dynamically decoded the spatiotemporal signatures of task information in the human brain by combining MRI-individualized source electroencephalography (EEG) with multivariate pattern analysis (MVPA). A newly developed network modeling approach-dynamic activity flow modeling-then simulated the flow of task-evoked activity over more causally interpretable (relative to standard functional connectivity [FC] approaches) resting-state functional connections (dynamic, lagged, direct, and directional). We demonstrate the utility of this modeling approach by applying it to elucidate network processes underlying sensory-motor information flow in the brain, revealing accurate predictions of empirical response information dynamics underlying behavior. Extending the model toward simulating network lesions suggested a role for the cognitive control networks (CCNs) as primary drivers of response information flow, transitioning from early dorsal attention network-dominated sensory-to-response transformation to later collaborative CCN engagement during response selection. These results demonstrate the utility of the dynamic activity flow modeling approach in identifying the generative network processes underlying neurocognitive phenomena.

Polypharmacy is predictive of postoperative complications in older adults undergoing ventral hernia repair.

BACKGROUND: Ventral hernias are common in older adults, and may be repaired via a transversus abdominus release (TAR). Older adults undergoing surgery have unique age-related risk factors, including polypharmacy. Polypharmacy is highly prevalent in older adults and is associated with adverse postoperative outcomes. Our aim was to examine the prevalence and association of polypharmacy with clinical outcomes in older adults undergoing a TAR. METHODS: Patients 60 years and older who underwent elective open or robotic bilateral TAR were included in the study. Average daily medications taken preoperatively was collected and stratified by tertiles. Baseline demographic data, peri- and postoperative outcomes, and 30-day outcomes were collected. RESULTS: There were 132 total patients with an average age of 67.8 years. The number of daily medications ranged from 0 to 28, with an overall mean of 11.2 medications. Patients in tertile 1 took an average of 5.3 medications, tertile 2 10.5 medications, and tertile 3 17.9 medications. Patients in tertile 3 had more than double the rate of in-hospital complications (0.7) compared to tertiles 1 and 2 (0.3 and 0.3, respectively; p = 0.03). A greater number of daily medications was independently associated with postoperative delirium [odds ratio (OR) 1.2, 95% confidence interval (CI) 1.0-1.3], cardiac events (OR 1.2, 95% CI 1.0-1.3), ICU stay (OR 1.2, 95% CI 1.0-1.3), and discharge to a skilled nursing facility (SNF) (OR 1.2, 95% CI 1.0-1.5). CONCLUSIONS: Polypharmacy was very common in older adults undergoing a TAR, and was associated with in-hospital complications, postoperative delirium, cardiac events, ICU stay, length of stay, and discharge to a SNF. Additional study is needed to assess if preoperative interventions to limit polypharmacy will improve outcomes for older adults undergoing a TAR.