Neonatal ICU antibiotic use trends within an integrated delivery network.

BACKGROUND AND OBJECTIVES: There is a need for robust antibiotic stewardship programs (ASPs) in the neonatal population. This study's objectives were to assess neonatal antibiotic use practices over an extended period across an integrated delivery network (IDN), including six Neonatal Intensive Care Units (NICUs), to identify those most successful practices reducing use rates. METHODS: A retrospective cohort study was conducted, including 15,015 NICU admissions from an integrated delivery network, across six hospitals over eight years (50% Level III and 50% Level II) computing antibiotic use rates (AURs) stratified by usage: in the first few days of the stay vs. later in the stay and by gestational age. Several metrics were examined for assumptions of strong correlation with AUR: (1) the percentage of infants given antibiotics early in their stays and (2) durations of courses of antibiotics. RESULTS: Results conclude a wide variation in AURs and trends that these rates followed over time. However, there was a decrease in overall AUR from 15.7-16.6 to 10.1-10.8%, with four of the six NICUs recording statistically significant reductions in AUR vs. their first year of measurement. Specifically, the level III NICUs overall AUR decreases from 15.1-16.22 to 8.6-9.4%, and level II NICUs overall AUR 20.3-24.4 to 14.1-16.1%. A particularly successful level II NICU decreased its AUR from 22.9-30.6 to 5.9-9.4%. CONCLUSION: To our knowledge, this is the first study to utilize data analytics at an IDN level to identify trends in AUR, We have identified practices that allowed an institution to reduce NICU AURs significantly, and which, if done as a standard practice, could be replicated on a broader scale.

Ontological Dimensions of Cognitive-Neural Mappings.

The growing literature reporting results of cognitive-neural mappings has increased calls for an adequate organizing ontology, or taxonomy, of these mappings. This enterprise is non-trivial, as relevant dimensions that might contribute to such an ontology are not yet agreed upon. We propose that any candidate dimensions should be evaluated on their ability to explain observed differences in functional neuroimaging activation patterns. In this study, we use a large sample of task-based functional magnetic resonance imaging (task-fMRI) results and a data-driven strategy to identify these dimensions. First, using a data-driven dimension reduction approach and multivariate distance matrix regression (MDMR), we quantify the variance among activation maps that is explained by existing ontological dimensions. We find that 'task paradigm' categories explain more variance among task-activation maps than other dimensions, including latent cognitive categories. Surprisingly, 'study ID', or the study from which each activation map was reported, explained close to 50% of the variance in activation patterns. Using a clustering approach that allows for overlapping clusters, we derived data-driven latent activation states, associated with re-occurring configurations of the canonical frontoparietal, salience, sensory-motor, and default mode network activation patterns. Importantly, with only four data-driven latent dimensions, one can explain greater variance among activation maps than all conventional ontological dimensions combined. These latent dimensions may inform a data-driven cognitive ontology, and suggest that current descriptions of cognitive processes and the tasks used to elicit them do not accurately reflect activation patterns commonly observed in the human brain.

Aberrant functional connectivity of inhibitory control networks in children with autism spectrum disorder.

Development of inhibitory control is a core component of executive function processes and a key aspect of healthy development. Children with autism spectrum disorder (ASD) show impairments in performance on inhibitory control tasks. Nevertheless, the research on the neural correlates of these impairments is inconclusive. Here, we explore the integrity of inhibitory control networks in children with ASD and typically developing (TD) children using resting state functional Magnetic Resonance Imagaing (MRI). In a large multisite sample, we find evidence for significantly greater functional connectivity (FC) of the right inferior frontal junction (rIFJ) with the posterior cingulate gyrus, and left and right frontal poles in children with ASD compared with TD children. Additionally, TD children show greater FC of rIFJ with the superior parietal lobule (SPL) compared with children with ASD. Furthermore, although higher rIFJ-SPL and rIFJ-IPL FC was related to better inhibitory control behaviors in both ASD and TD children, rIFJ-dACC FC was only associated with inhibitory control behaviors in TD children. These results provide preliminary evidence of differences in intrinsic functional networks supporting inhibitory control in children with ASD, and provide a basis for further exploration of the development of inhibitory control in children with the disorder. Autism Research 2018, 11: 1468-1478. © 2018 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Inhibitory control is an important process in healthy cognitive development. Behavioral studies suggest that inhibitory control is impaired in autism spectrum disorder (ASD). However, research examining the neural correlates underlying inhibitory control differences in children with ASD is inconclusive. This study reveals differences in functional connectivity of brain networks important for inhibitory control in children with ASD compared with typically developing children. Furthermore, it relates brain network differences to parent-reported inhibitory control behaviors in children with ASD. These findings provide support for the hypothesis that differences in brain connectivity may underlie observable behavioral deficits in inhibitory control in children with the disorder.

Inter-subject phase synchronization for exploratory analysis of task-fMRI.

Analysis of task-based fMRI data is conventionally carried out using a hypothesis-driven approach, where blood-oxygen-level dependent (BOLD) time courses are correlated with a hypothesized temporal structure. In some experimental designs, this temporal structure can be difficult to define. In other cases, experimenters may wish to take a more exploratory, data-driven approach to detecting task-driven BOLD activity. In this study, we demonstrate the efficiency and power of an inter-subject synchronization approach for exploratory analysis of task-based fMRI data. Combining the tools of instantaneous phase synchronization and independent component analysis, we characterize whole-brain task-driven responses in terms of group-wise similarity in temporal signal dynamics of brain networks. We applied this framework to fMRI data collected during performance of a simple motor task and a social cognitive task. Analyses using an inter-subject phase synchronization approach revealed a large number of brain networks that dynamically synchronized to various features of the task, often not predicted by the hypothesized temporal structure of the task. We suggest that this methodological framework, along with readily available tools in the fMRI community, provides a powerful exploratory, data-driven approach for analysis of task-driven BOLD activity.

Evolution of spatial and temporal features of functional brain networks across the lifespan.

Development and aging are associated with functional changes in the brain across the lifespan. These changes manifest in a variety of spatial and temporal features of resting state functional MRI (rs-fMRI) but have seldom been explored exhaustively. We present a comprehensive study assessing age-related changes in spatial and temporal features of blind-source separated components identified by independent vector analysis (IVA) in a cross-sectional lifespan sample (ages 6-85 years). We show that while large-scale network configurations remain consistent throughout the lifespan, changes persist in both local and global organization of these networks. We show that the spatial extent of the majority of functional networks exhibits linear decreases and both positive and negative quadratic trajectories across the lifespan. Network connectivity revealed nuanced patterns of linear and quadratic relationships with age, primarily in higher order cognitive networks. We also show divergent age-related patterns across the frequency spectrum in lower and higher frequencies. Taken together, these results point to the presence of sophisticated patterns of age-related changes that have previously not been considered collectively. We suggest that established patterns of lifespan changes in rs-fMRI features may be driven by changes in the spectral composition of BOLD signals.

Chronnectomic patterns and neural flexibility underlie executive function.

Despite extensive research into executive function (EF), the precise relationship between brain dynamics and flexible cognition remains unknown. Using a large, publicly available dataset (189 participants), we find that functional connections measured throughout 56min of resting state fMRI data comprise five distinct connectivity states. Elevated EF performance as measured outside of the scanner was associated with greater episodes of more frequently occurring connectivity states, and fewer episodes of less frequently occurring connectivity states. Frequently occurring states displayed metastable properties, where cognitive flexibility may be facilitated by attenuated correlations and greater functional connection variability. Less frequently occurring states displayed properties consistent with low arousal and low vigilance. These findings suggest that elevated EF performance may be associated with the propensity to occupy more frequently occurring brain configurations that enable cognitive flexibility, while avoiding less frequently occurring brain configurations related to low arousal/vigilance states. The current findings offer a novel framework for identifying neural processes related to individual differences in executive function.