@article {819, title = {Analytic programming with FMRI data: a quick-start guide for statisticians using R.}, journal = {PLoS One}, volume = {9}, year = {2014}, month = {2014}, pages = {e89470}, abstract = {

Functional magnetic resonance imaging (fMRI) is a thriving field that plays an important role in medical imaging analysis, biological and neuroscience research and practice. This manuscript gives a didactic introduction to the statistical analysis of fMRI data using the R project, along with the relevant R code. The goal is to give statisticians who would like to pursue research in this area a quick tutorial for programming with fMRI data. References of relevant packages and papers are provided for those interested in more advanced analysis.

}, keywords = {Brain, brain mapping, Humans, Magnetic Resonance Imaging, Programming Languages}, issn = {1932-6203}, doi = {10.1371/journal.pone.0089470}, author = {Eloyan, Ani and Li, Shanshan and Muschelli, John and Pekar, Jim J and Mostofsky, Stewart H and Caffo, Brian S} } @article {831, title = {Disruption of functional organization within the primary motor cortex in children with autism.}, journal = {Hum Brain Mapp}, volume = {35}, year = {2014}, month = {2014 Feb}, pages = {567-80}, abstract = {

Accumulating evidence suggests that motor impairments are prevalent in autism spectrum disorder (ASD), relate to the social and communicative deficits at the core of the diagnosis and may reflect abnormal connectivity within brain networks underlying motor control and learning. Parcellation of resting-state functional connectivity data using spectral clustering approaches has been shown to be an effective means of visualizing functional organization within the brain but has most commonly been applied to explorations of normal brain function. This article presents a parcellation of a key area of the motor network, the primary motor cortex (M1), a key area of the motor control network, in adults, typically developing (TD) children and children with ASD and introduces methods for selecting the number of parcels, matching parcels across groups and testing group differences. The parcellation is based solely on patterns of connectivity between individual M1 voxels and all voxels outside of M1, and within all groups, a gross dorsomedial to ventrolateral organization emerged within M1 which was left-right symmetric. Although this gross organizational scheme was present in both groups of children, statistically significant group differences in the size and segregation of M1 parcels within regions of the motor homunculus corresponding to the upper and lower limbs were observed. Qualitative comparison of the M1 parcellation for children with ASD with that of younger and older TD children suggests that these organizational differences, with a lack of differentiation between lower limb/trunk regions and upper limb/hand regions, may be due, at least in part, to a delay in functional specialization within the motor cortex.

}, keywords = {Adult, Autistic Disorder, brain mapping, Child, Developmental Disabilities, Female, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Middle Aged, Motor Cortex, Oxygen, Young Adult}, issn = {1097-0193}, doi = {10.1002/hbm.22188}, author = {Nebel, Mary Beth and Joel, Suresh E and Muschelli, John and Barber, Anita D and Caffo, Brian S and Pekar, James J and Mostofsky, Stewart H} } @article {822, title = {An evaluation of independent component analyses with an application to resting-state fMRI.}, journal = {Biometrics}, volume = {70}, year = {2014}, month = {2014 Mar}, pages = {224-36}, abstract = {

We examine differences between independent component analyses (ICAs) arising from different assumptions, measures of dependence, and starting points of the algorithms. ICA is a popular method with diverse applications including artifact removal in electrophysiology data, feature extraction in microarray data, and identifying brain networks in functional magnetic resonance imaging (fMRI). ICA can be viewed as a generalization of principal component analysis (PCA) that takes into account higher-order cross-correlations. Whereas the PCA solution is unique, there are many ICA methods-whose solutions may differ. Infomax, FastICA, and JADE are commonly applied to fMRI studies, with FastICA being arguably the most popular. Hastie and Tibshirani (2003) demonstrated that ProDenICA outperformed FastICA in simulations with two components. We introduce the application of ProDenICA to simulations with more components and to fMRI data. ProDenICA was more accurate in simulations, and we identified differences between biologically meaningful ICs from ProDenICA versus other methods in the fMRI analysis. ICA methods require nonconvex optimization, yet current practices do not recognize the importance of, nor adequately address sensitivity to, initial values. We found that local optima led to dramatically different estimates in both simulations and group ICA of fMRI, and we provide evidence that the global optimum from ProDenICA is the best estimate. We applied a modification of the Hungarian (Kuhn-Munkres) algorithm to match ICs from multiple estimates, thereby gaining novel insights into how brain networks vary in their sensitivity to initial values and ICA method.

}, keywords = {Adolescent, Algorithms, Attention Deficit Disorder with Hyperactivity, brain mapping, Child, Child, Preschool, Computer Simulation, Humans, Magnetic Resonance Imaging, Models, Statistical, Principal Component Analysis}, issn = {1541-0420}, doi = {10.1111/biom.12111}, author = {Risk, Benjamin B and Matteson, David S and Ruppert, David and Eloyan, Ani and Caffo, Brian S} } @article {818, title = {Reduction of motion-related artifacts in resting state fMRI using aCompCor.}, journal = {Neuroimage}, volume = {96}, year = {2014}, month = {2014 Aug 1}, pages = {22-35}, abstract = {

Recent studies have illustrated that motion-related artifacts remain in resting-state fMRI (rs-fMRI) data even after common corrective processing procedures have been applied, but the extent to which head motion distorts the data may be modulated by the corrective approach taken. We compare two different methods for estimating nuisance signals from tissues not expected to exhibit BOLD fMRI signals of neuronal origin: 1) the more commonly used mean signal method and 2) the principal components analysis approach (aCompCor: Behzadi et al., 2007). Further, we investigate the added benefit of "scrubbing" (Power et al., 2012) following both methods. We demonstrate that the use of aCompCor removes motion artifacts more effectively than tissue-mean signal regression. In addition, inclusion of more components from anatomically defined regions of no interest better mitigates motion-related artifacts and improves the specificity of functional connectivity estimates. While scrubbing further attenuates motion-related artifacts when mean signals are used, scrubbing provides no additional benefit in terms of motion artifact reduction or connectivity specificity when using aCompCor.

}, issn = {1095-9572}, doi = {10.1016/j.neuroimage.2014.03.028}, author = {Muschelli, John and Nebel, Mary Beth and Caffo, Brian S and Barber, Anita D and Pekar, James J and Mostofsky, Stewart H} } @article {820, title = {Successful implementation of a unit-based quality nurse to reduce central line-associated bloodstream infections.}, journal = {Am J Infect Control}, volume = {42}, year = {2014}, month = {2014 Feb}, pages = {139-43}, abstract = {

BACKGROUND: Central line (CL)-associated bloodstream infections (CLABSI) are an important cause of patient morbidity and mortality. Novel strategies to prevent CLABSI are needed.

METHODS: We described a quasiexperimental study to examine the effect of the presence of a unit-based quality nurse (UQN) dedicated to perform patient safety and infection control activities with a focus on CLABSI prevention in a surgical intensive care unit (SICU).

RESULTS: From July 2008 to March 2012, there were 3,257 SICU admissions; CL utilization ratio was 0.74 (18,193 CL-days/24,576 patient-days). The UQN program began in July 2010; the nurse was present for 30\% (193/518) of the days of the intervention period of July 2010 to March 2012. The average CLABSI rate was 5.0 per 1,000 CL-days before the intervention and 1.5 after the intervention and decreased by 5.1\% (P = .005) for each additional 1\% of days of the month that the UQN was present, even after adjusting for CLABSI rates in other adult intensive care units, time, severity of illness, and Comprehensive Unit-based Safety Program participation (5.1\%, P = .004). Approximately 11.4 CLABSIs were prevented.

CONCLUSION: The presence of a UQN dedicated to perform infection control activities may be an effective strategy for CLABSI reduction.

}, keywords = {Adult, Catheter-Related Infections, Catheterization, Central Venous, Humans, Infection Control, Intensive Care Units, Nurses, Quality Control, Quality of Health Care}, issn = {1527-3296}, doi = {10.1016/j.ajic.2013.08.006}, author = {Thom, Kerri A and Li, Shanshan and Custer, Melissa and Preas, Michael Anne and Rew, Cindy D and Cafeo, Christina and Leekha, Surbhi and Caffo, Brian S and Scalea, Thomas M and Lissauer, Matthew E} } @article {788, title = {A unifying framework for marginalized random intercept models of correlated binary outcomes.}, journal = {Int Stat Rev}, volume = {82}, year = {2014}, month = {2014 Aug}, pages = {275-295}, abstract = {

We demonstrate that many current approaches for marginal modeling of correlated binary outcomes produce likelihoods that are equivalent to the copula-based models herein. These general copula models of underlying latent threshold random variables yield likelihood-based models for marginal fixed effects estimation and interpretation in the analysis of correlated binary data with exchangeable correlation structures. Moreover, we propose a nomenclature and set of model relationships that substantially elucidates the complex area of marginalized random intercept models for binary data. A diverse collection of didactic mathematical and numerical examples are given to illustrate concepts.

}, issn = {0306-7734}, doi = {10.1111/insr.12035}, author = {Swihart, Bruce J and Caffo, Brian S and Crainiceanu, Ciprian M} } @article {810, title = {Combining hidden Markov models for comparing the dynamics of multiple sleep electroencephalograms.}, journal = {Stat Med}, volume = {32}, year = {2013}, month = {2013 Aug 30}, pages = {3342-56}, abstract = {

In this manuscript, we consider methods for the analysis of populations of electroencephalogram signals during sleep for the study of sleep disorders using hidden Markov models (HMMs). Notably, we propose an easily implemented method for simultaneously modeling multiple time series that involve large amounts of data. We apply these methods to study sleep-disordered breathing (SDB) in the Sleep Heart Health Study (SHHS), a landmark study of SDB and cardiovascular consequences. We use the entire, longitudinally collected, SHHS cohort to develop HMM population parameters, which we then apply to obtain subject-specific Markovian predictions. From these predictions, we create several indices of interest, such as transition frequencies between latent states. Our HMM analysis of electroencephalogram signals uncovers interesting findings regarding differences in brain activity during sleep between those with and without SDB. These findings include stability of the percent time spent in HMM latent states across matched diseased and non-diseased groups and differences in the rate of transitioning.

}, keywords = {Data Interpretation, Statistical, Electroencephalography, Female, Humans, Longitudinal Studies, Male, Markov Chains, Middle Aged, Models, Statistical, Sleep Apnea Syndromes}, issn = {1097-0258}, doi = {10.1002/sim.5747}, author = {Langrock, Roland and Swihart, Bruce J and Caffo, Brian S and Punjabi, Naresh M and Crainiceanu, Ciprian M} } @article {823, title = {Comparison of total hospital-acquired bloodstream infections to central line-associated bloodstream infections and implications for outcome measures in infection control.}, journal = {Infect Control Hosp Epidemiol}, volume = {34}, year = {2013}, month = {2013 Sep}, pages = {984-6}, abstract = {

The validity of the central line-associated bloodstream infection (CLABSI) measure is compromised by subjectivity. We observed significant decreases in both CLABSIs and total hospital-acquired bloodstream infections (BSIs) following a CLABSI prevention intervention in adult intensive care units. Total hospital-acquired BSIs could be explored as an adjunct, objective CLABSI measure.

}, keywords = {Adult, Catheter-Related Infections, Catheterization, Central Venous, Cross Infection, Humans, Intensive Care Units, Longitudinal Studies, Tertiary Care Centers}, issn = {1559-6834}, doi = {10.1086/671730}, author = {Leekha, Surbhi and Li, Shanshan and Thom, Kerri A and Preas, Michael Anne and Caffo, Brian S and Morgan, Daniel J and Harris, Anthony D} } @article {829, title = {Developmental changes in within- and between-network connectivity between late childhood and adulthood.}, journal = {Neuropsychologia}, volume = {51}, year = {2013}, month = {2013 Jan}, pages = {156-67}, abstract = {

A number of behavioral changes occur between late childhood and adulthood, including maturation of social cognition, reward receptivity, impulsiveness, risk-taking and cognitive control. Although some of these abilities show linear improvements with age, some abilities may temporarily worsen, reflecting both the restructuring and/or strengthening of connections within some brain systems. The current study uses resting state functional connectivity to examine developmental differences between late childhood and adulthood in task positive (TP) regions, which play a role in cognitive control functions, and task negative (TN) regions, which play a role in social cognition, self-referential, and internally-directed thought. Within the TP network, developmental differences in connectivity were found with the left dorsolateral prefrontal cortex. Within the TN network, developmental differences in connectivity were found with a broad area of the medial prefrontal cortex and the right parahippocampal gyrus. Connections between the two networks also showed significant developmental differences. Stronger anticorrelations were found in the TN maps of the adult group for the right anterior insula/inferior frontal gyrus, bilateral anterior inferior parietal lobule, bilateral superior parietal lobule and an anterior portion of the right posterior cingulate cortex. There was a significant brain-behavior relationship between the strength of anticorrelation in these regions and inhibitory control performance on two Go/No-go tasks suggesting that the development of anticorrelations between late childhood and adulthood supports mature inhibitory control. Overall, maturation of these networks occurred in specific regions which are associated with cognitive control of goal-directed behavior, including those involved in working memory, social cognition, and inhibitory control.

}, keywords = {Adolescent, Adult, Age Factors, Analysis of Variance, Brain, brain mapping, Child, Child Development, Cognition, Female, Humans, Image Processing, Computer-Assisted, Inhibition (Psychology), Magnetic Resonance Imaging, Male, Middle Aged, Neural Pathways, Neuropsychological Tests, Oxygen, Reaction Time, Young Adult}, issn = {1873-3514}, doi = {10.1016/j.neuropsychologia.2012.11.011}, author = {Barber, Anita D and Caffo, Brian S and Pekar, James J and Mostofsky, Stewart H} } @article {826, title = {Effects of working memory demand on neural mechanisms of motor response selection and control.}, journal = {J Cogn Neurosci}, volume = {25}, year = {2013}, month = {2013 Aug}, pages = {1235-48}, abstract = {

Inhibitory control commonly recruits a number of frontal regions: pre-supplementary motor area (pre-SMA), frontal eye fields (FEFs), and right-lateralized posterior inferior frontal gyrus (IFG), dorsal anterior insula (DAI), dorsolateral prefrontal cortex (DLPFC), and inferior frontal junction (IFJ). These regions may directly implement inhibitory motor control or may be more generally involved in executive control functions. Two go/no-go tasks were used to distinguish regions specifically recruited for inhibition from those that additionally show increased activity with working memory demand. The pre-SMA and IFG were recruited for inhibition in both tasks and did not have greater activation for working memory demand on no-go trials, consistent with a role in inhibitory control. Activation in pre-SMA also responded to response selection demand and was increased with working memory on go trials specifically. The bilateral FEF and right DAI were commonly active for no-go trials. The FEF was also recruited to a greater degree with working memory demand on go trials and may bias top-down information when stimulus-response mappings change. The DAI, additionally responded to increased working memory demand on both go and no-go trials and may be involved in accessing sustained task information, alerting, or autonomic changes when cognitive demands increase. DLPFC activation was consistent with a role in working memory retrieval on both go and no-go trials. The inferior frontal junction, on the other hand, had greater activation with working memory specifically for no-go trials and may detect salient stimuli when the task requires frequent updating of working memory representations.

}, keywords = {Adult, Brain, brain mapping, Choice Behavior, Female, Humans, Image Processing, Computer-Assisted, Inhibition (Psychology), Magnetic Resonance Imaging, Male, Memory, Short-Term, Motor Activity, Neuropsychological Tests, Oxygen, Reaction Time, Young Adult}, issn = {1530-8898}, doi = {10.1162/jocn_a_00394}, author = {Barber, Anita D and Caffo, Brian S and Pekar, James J and Mostofsky, Stewart H} } @article {825, title = {Isoosmolar enemas demonstrate preferential gastrointestinal distribution, safety, and acceptability compared with hyperosmolar and hypoosmolar enemas as a potential delivery vehicle for rectal microbicides.}, journal = {AIDS Res Hum Retroviruses}, volume = {29}, year = {2013}, month = {2013 Nov}, pages = {1487-95}, abstract = {

Rectally applied antiretroviral microbicides for preexposure prophylaxis (PrEP) of HIV infection are currently in development. Since enemas (rectal douches) are commonly used by men who have sex with men prior to receptive anal intercourse, a microbicide enema could enhance PrEP adherence by fitting seamlessly within the usual sexual practices. We assessed the distribution, safety, and acceptability of three enema types-hyperosmolar (Fleet), hypoosmolar (distilled water), and isoosmolar (Normosol-R)-in a crossover design. Nine men received each enema type in random order. Enemas were radiolabeled [(99m)Tc-diethylene triamine pentaacetic acid (DTPA)] to assess enema distribution in the colon using single photon emission computed tomography/computed tomography (SPECT/CT) imaging. Plasma (99m)Tc-DTPA indicated mucosal permeability. Sigmoidoscopic colon tissue biopsies were taken to assess injury as well as tissue penetration of the (99m)Tc-DTPA. Acceptability was assessed after each product use and at the end of the study. SPECT/CT imaging showed that the isoosmolar enema had greater proximal colonic distribution (up to the splenic flexure) and greater luminal and colon tissue concentrations of (99m)Tc-DTPA when compared to the other enemas (p<0.01). Colon biopsies also showed that only the hyperosmolar enema caused sloughing of the colonic epithelium (p<0.05). In permeability testing, the hypoosmolar enema had higher plasma (99m)Tc-DTPA 24-h area under the concentration-time curve and peak concentration compared to the hyperosmolar and isoosmolar enemas, respectively. Acceptability was generally good with no clear preferences among the three enema types. The isoosmolar enema was superior or similar to the other enemas in all categories and is a good candidate for further development as a rectal microbicide vehicle.

}, keywords = {Anti-Infective Agents, Biopsy, Colon, Sigmoid, Enema, HIV Infections, Humans, Intestinal Mucosa, Male, Patient Acceptance of Health Care, Solutions, Tomography, Emission-Computed, Single-Photon}, issn = {1931-8405}, doi = {10.1089/AID.2013.0189}, author = {Leyva, Francisco J and Bakshi, Rahul P and Fuchs, Edward J and Li, Liye and Caffo, Brian S and Goldsmith, Arthur J and Ventuneac, Ana and Carballo-Di{\'e}guez, Alex and Du, Yong and Leal, Jeffrey P and Lee, Linda A and Torbenson, Michael S and Hendrix, Craig W} } @article {812, title = {Likelihood-based population independent component analysis.}, journal = {Biostatistics}, volume = {14}, year = {2013}, month = {2013 Jul}, pages = {514-27}, abstract = {

Independent component analysis (ICA) is a widely used technique for blind source separation, used heavily in several scientific research areas including acoustics, electrophysiology, and functional neuroimaging. We propose a scalable two-stage iterative true group ICA methodology for analyzing population level functional magnetic resonance imaging (fMRI) data where the number of subjects is very large. The method is based on likelihood estimators of the underlying source densities and the mixing matrix. As opposed to many commonly used group ICA algorithms, the proposed method does not require significant data reduction by a 2-fold singular value decomposition. In addition, the method can be applied to a large group of subjects since the memory requirements are not restrictive. The performance of our approach is compared with a commonly used group ICA algorithm via simulation studies. Furthermore, the proposed method is applied to a large collection of resting state fMRI datasets. The results show that established brain networks are well recovered by the proposed algorithm.

}, keywords = {Adult, Algorithms, Attention Deficit Disorder with Hyperactivity, Biostatistics, Brain, Child, Computer Simulation, Databases, Factual, Humans, Imaging, Three-Dimensional, Likelihood Functions, Magnetic Resonance Imaging, Principal Component Analysis, Statistics, Nonparametric}, issn = {1468-4357}, doi = {10.1093/biostatistics/kxs055}, author = {Eloyan, Ani and Crainiceanu, Ciprian M and Caffo, Brian S} } @article {821, title = {Practical Marginalized Multilevel Models.}, journal = {Stat}, volume = {2}, year = {2013}, month = {2013}, abstract = {

Clustered data analysis is characterized by the need to describe both systematic variation in a mean model and cluster-dependent random variation in an association model. Marginalized multilevel models embrace the robustness and interpretations of a marginal mean model, while retaining the likelihood inference capabilities and flexible dependence structures of a conditional association model. Although there has been increasing recognition of the attractiveness of marginalized multilevel models, there has been a gap in their practical application arising from a lack of readily available estimation procedures. We extend the marginalized multilevel model to allow for nonlinear functions in both the mean and association aspects. We then formulate marginal models through conditional specifications to facilitate estimation with mixed model computational solutions already in place. We illustrate the MMM and approximate MMM approaches on a cerebrovascular deficiency crossover trial using SAS and an epidemiological study on race and visual impairment using R. Datasets, SAS and R code are included as supplemental materials.

}, issn = {0038-9986}, doi = {10.1002/sta4.22}, author = {Griswold, Michael E and Swihart, Bruce J and Caffo, Brian S and Zeger, Scott L} } @article {805, title = {Practical recommendations for population PK studies with sampling time errors.}, journal = {Eur J Clin Pharmacol}, volume = {69}, year = {2013}, month = {2013 Dec}, pages = {2055-64}, abstract = {

PURPOSE: Population pharmacokinetic (PK) data collected from routine clinical practice offers a rich source of valuable information. However, in observational population PK data, accurate time information for blood samples is often missing, resulting in measurement errors (ME) in the sampling time variable. The goal of this study was to investigate the effects on model parameters when a scheduled time is used instead of the actual blood sampling time, and to propose ME correction methods.

METHODS: Simulation studies were conducted based on two major factors: the curvature in PK profiles and the size of ME. As ME correction methods, transform both sides (TBS) models were developed with application of Box-Cox power transformation and Taylor expansion. The TBS models were compared to a conventional population PK model using simulations.

RESULTS: The most important determinant of bias due to time ME was the degree of curvature (nonlinearity) in PK profiles; the smaller the curvature around sampling times, the smaller the associated bias. The second important determinant was the magnitude of ME; the larger the ME, the larger the bias. The proposed TBS models performed better than a conventional population PK modeling when curvature and ME were substantial.

CONCLUSIONS: Time ME in sampling time can lead to bias on the parameter estimators. The following practical recommendations are provided: 1) when the curvature of PK profiles is small, conventional population PK modeling is robust to even large ME; and 2) when the curvature is moderate or large, the proposed methodology reduces bias in parameter estimates.

}, keywords = {Humans, Models, Biological, Pharmacokinetics, Research Design, Time Factors}, issn = {1432-1041}, doi = {10.1007/s00228-013-1576-7}, author = {Choi, Leena and Crainiceanu, Ciprian M and Caffo, Brian S} }