@article {836, title = {Brain mediators of the effects of noxious heat on pain.}, journal = {Pain}, volume = {155}, year = {2014}, month = {2014 Aug}, pages = {1632-48}, abstract = {

Recent human neuroimaging studies have investigated the neural correlates of either noxious stimulus intensity or reported pain. Although useful, analyzing brain relationships with stimulus intensity and behavior separately does not address how sensation and pain are linked in the central nervous system. In this study, we used multi-level mediation analysis to identify brain mediators of pain--regions in which trial-by-trial responses to heat explained variability in the relationship between noxious stimulus intensity (across 4 levels) and pain. This approach has the potential to identify multiple circuits with complementary roles in pain genesis. Brain mediators of noxious heat effects on pain included targets of ascending nociceptive pathways (anterior cingulate, insula, SII, and medial thalamus) and also prefrontal and subcortical regions not associated with nociceptive pathways per se. Cluster analysis revealed that mediators were grouped into several distinct functional networks, including the following: somatosensory, paralimbic, and striatal-cerebellar networks that increased with stimulus intensity; and 2 networks co-localized with "default mode" regions in which stimulus intensity-related decreases mediated increased pain. We also identified "thermosensory" regions that responded to increasing noxious heat but did not predict pain reports. Finally, several regions did not respond to noxious input, but their activity predicted pain; these included ventromedial prefrontal cortex, dorsolateral prefrontal cortex, cerebellar regions, and supplementary motor cortices. These regions likely underlie both nociceptive and non-nociceptive processes that contribute to pain, such as attention and decision-making processes. Overall, these results elucidate how multiple distinct brain systems jointly contribute to the central generation of pain.

}, issn = {1872-6623}, doi = {10.1016/j.pain.2014.05.015}, author = {Atlas, Lauren Y and Lindquist, Martin A and Bolger, Niall and Wager, Tor D} } @article {816, title = {Evidence for Specificity of Motor Impairments in Catching and Balance in Children with Autism.}, journal = {J Autism Dev Disord}, year = {2014}, month = {2014 Sep 18}, abstract = {

To evaluate evidence for motor impairment specificity in autism spectrum disorder (ASD) and attention deficit/hyperactivity disorder (ADHD). Children completed performance-based assessment of motor functioning (Movement Assessment Battery for Children: MABC-2). Logistic regression models were used to predict group membership. In the models comparing typically developing and developmental disability (DD), all three MABC subscale scores were significantly negatively associated with having a DD. In the models comparing ADHD and ASD, catching and static balance items were associated with ASD group membership, with a 1 point decrease in performance increasing odds of ASD by 36 and 39~\%, respectively. Impairments in motor skills requiring the coupling of visual and temporal feedback to guide and adjust movement appear specifically deficient in ASD.

}, issn = {1573-3432}, doi = {10.1007/s10803-014-2229-0}, author = {Ament, Katarina and Mejia, Amanda and Buhlman, Rebecca and Erklin, Shannon and Caffo, Brian and Mostofsky, Stewart and Wodka, Ericka} } @article {815, title = {Neuroinflammation and brain atrophy in former NFL players: An in vivo multimodal imaging pilot study.}, journal = {Neurobiol Dis}, volume = {74C}, year = {2014}, month = {2014 Nov 7}, pages = {58-65}, abstract = {

There are growing concerns about potential delayed, neuropsychiatric consequences (e.g, cognitive decline, mood or anxiety disorders) of sports-related traumatic brain injury (TBI). Autopsy studies of brains from a limited number of former athletes have described characteristic, pathologic changes of chronic traumatic encephalopathy (CTE) leading to questions about the relationship between these pathologic and the neuropsychiatric disturbances seen in former athletes. Research in this area will depend on in vivo methods that characterize molecular changes in the brain, linking CTE and other sports-related pathologies with delayed emergence of neuropsychiatric symptoms. In this pilot project we studied former National Football League (NFL) players using new neuroimaging techniques and clinical measures of cognitive functioning. We hypothesized that former NFL players would show molecular and structural changes in medial temporal and parietal lobe structures as well as specific cognitive deficits, namely those of verbal learning and memory. We observed a significant increase in binding of [(11)C]DPA-713 to the translocator protein (TSPO), a marker of brain injury and repair, in several brain regions, such as the supramarginal gyrus and right amygdala, in 9 former NFL players compared to 9 age-matched, healthy controls. We also observed significant atrophy of the right hippocampus. Finally, we report that these same former players had varied performance on a test of verbal learning and memory, suggesting that these molecular and pathologic changes may play a role in cognitive decline. These results suggest that localized brain injury and repair, indicated by increased [(11)C]DPA-713 binding to TSPO, may be linked to history of NFL play. [(11)C]DPA-713 PET is a promising new tool that can be used in future study design to examine further the relationship between TSPO expression in brain injury and repair, selective regional brain atrophy, and the potential link to deficits in verbal learning and memory after NFL play.

}, issn = {1095-953X}, doi = {10.1016/j.nbd.2014.10.019}, author = {Coughlin, Jennifer M and Wang, Yuchuan and Munro, Cynthia A and Ma, Shuangchao and Yue, Chen and Chen, Shaojie and Airan, Raag and Kim, Pearl K and Adams, Ashley V and Garcia, Cinthya and Higgs, Cecilia and Sair, Haris I and Sawa, Akira and Smith, Gwenn and Lyketsos, Constantine G and Caffo, Brian and Kassiou, Michael and Guilarte, Tomas R and Pomper, Martin G} } @article {834, title = {Separate neural representations for physical pain and social rejection.}, journal = {Nat Commun}, volume = {5}, year = {2014}, month = {2014}, pages = {5380}, abstract = {

Current theories suggest that physical pain and social rejection share common neural mechanisms, largely by virtue of overlapping functional magnetic resonance imaging (fMRI) activity. Here we challenge this notion by identifying distinct multivariate fMRI patterns unique to pain and rejection. Sixty participants experience painful heat and warmth and view photos of ex-partners and friends on separate trials. FMRI pattern classifiers discriminate pain and rejection from their respective control conditions in out-of-sample individuals with 92\% and 80\% accuracy. The rejection classifier performs at chance on pain, and vice versa. Pain- and rejection-related representations are uncorrelated within regions thought to encode pain affect (for example, dorsal anterior cingulate) and show distinct functional connectivity with other regions in a separate resting-state data set (N=91). These findings demonstrate that separate representations underlie pain and rejection despite common fMRI activity at the gross anatomical level. Rather than co-opting pain circuitry, rejection involves distinct affective representations in humans.

}, issn = {2041-1723}, doi = {10.1038/ncomms6380}, author = {Woo, Choong-Wan and Koban, Leonie and Kross, Ethan and Lindquist, Martin A and Banich, Marie T and Ruzic, Luka and Andrews-Hanna, Jessica R and Wager, Tor D} } @article {838, title = {Detecting functional connectivity change points for single-subject fMRI data.}, journal = {Front Comput Neurosci}, volume = {7}, year = {2013}, month = {2013}, pages = {143}, abstract = {

Recently in functional magnetic resonance imaging (fMRI) studies there has been an increased interest in understanding the dynamic manner in which brain regions communicate with one another, as subjects perform a set of experimental tasks or as their psychological state changes. Dynamic Connectivity Regression (DCR) is a data-driven technique used for detecting temporal change points in functional connectivity between brain regions where the number and location of the change points are unknown a priori. After finding the change points, DCR estimates a graph or set of relationships between the brain regions for data that falls between pairs of change points. In previous work, the method was predominantly validated using multi-subject data. In this paper, we concentrate on single-subject data and introduce a new DCR algorithm. The new algorithm increases accuracy for individual subject data with a small number of observations and reduces the number of false positives in the estimated undirected graphs. We also introduce a new Likelihood Ratio test for comparing sparse graphs across (or within) subjects; thus allowing us to determine whether data should be combined across subjects. We perform an extensive simulation analysis on vector autoregression (VAR) data as well as to an fMRI data set from a study (n = 23) of a state anxiety induction using a socially evaluative threat challenge. The focus on single-subject data allows us to study the variation between individuals and may provide us with a deeper knowledge of the workings of the brain.

}, issn = {1662-5188}, doi = {10.3389/fncom.2013.00143}, author = {Cribben, Ivor and Wager, Tor D and Lindquist, Martin A} } @article {839, title = {An fMRI-based neurologic signature of physical pain.}, journal = {N Engl J Med}, volume = {368}, year = {2013}, month = {2013 Apr 11}, pages = {1388-97}, abstract = {

BACKGROUND: Persistent pain is measured by means of self-report, the sole reliance on which hampers diagnosis and treatment. Functional magnetic resonance imaging (fMRI) holds promise for identifying objective measures of pain, but brain measures that are sensitive and specific to physical pain have not yet been identified.

METHODS: In four studies involving a total of 114 participants, we developed an fMRI-based measure that predicts pain intensity at the level of the individual person. In study 1, we used machine-learning analyses to identify a pattern of fMRI activity across brain regions--a neurologic signature--that was associated with heat-induced pain. The pattern included the thalamus, the posterior and anterior insulae, the secondary somatosensory cortex, the anterior cingulate cortex, the periaqueductal gray matter, and other regions. In study 2, we tested the sensitivity and specificity of the signature to pain versus warmth in a new sample. In study 3, we assessed specificity relative to social pain, which activates many of the same brain regions as physical pain. In study 4, we assessed the responsiveness of the measure to the analgesic agent remifentanil.

RESULTS: In study 1, the neurologic signature showed sensitivity and specificity of 94\% or more (95\% confidence interval [CI], 89 to 98) in discriminating painful heat from nonpainful warmth, pain anticipation, and pain recall. In study 2, the signature discriminated between painful heat and nonpainful warmth with 93\% sensitivity and specificity (95\% CI, 84 to 100). In study 3, it discriminated between physical pain and social pain with 85\% sensitivity (95\% CI, 76 to 94) and 73\% specificity (95\% CI, 61 to 84) and with 95\% sensitivity and specificity in a forced-choice test of which of two conditions was more painful. In study 4, the strength of the signature response was substantially reduced when remifentanil was administered.

CONCLUSIONS: It is possible to use fMRI to assess pain elicited by noxious heat in healthy persons. Future studies are needed to assess whether the signature predicts clinical pain. (Funded by the National Institute on Drug Abuse and others.).

}, keywords = {Adult, Analgesics, Opioid, Artificial Intelligence, Brain, brain mapping, Female, Hot Temperature, Humans, Magnetic Resonance Imaging, Male, Pain, Pain Measurement, Piperidines, ROC Curve, Sensitivity and Specificity, Young Adult}, issn = {1533-4406}, doi = {10.1056/NEJMoa1204471}, author = {Wager, Tor D and Atlas, Lauren Y and Lindquist, Martin A and Roy, Mathieu and Woo, Choong-Wan and Kross, Ethan} } @article {800, title = {Hierarchical Adaptive Regression Kernels for Regression with Functional Predictors.}, journal = {J Comput Graph Stat}, volume = {22}, year = {2013}, month = {2013}, abstract = {

We propose a new method for regression using a parsimonious and scientifically interpretable representation of functional predictors. Our approach is designed for data that exhibit features such as spikes, dips, and plateaus whose frequency, location, size, and shape varies stochastically across subjects. We propose Bayesian inference of the joint functional and exposure models, and give a method for efficient computation. We contrast our approach with existing state-of-the-art methods for regression with functional predictors, and show that our method is more effective and efficient for data that include features occurring at varying locations. We apply our methodology to a large and complex dataset from the Sleep Heart Health Study, to quantify the association between sleep characteristics and health outcomes. Software and technical appendices are provided in online supplemental materials.

}, issn = {1061-8600}, doi = {10.1080/10618600.2012.694765}, author = {Woodard, Dawn B and Crainiceanu, Ciprian and Ruppert, David} } @article {ellignton, title = {Computerized lung sound analysis to improve the specificity of pediatric pneumonia in resource-poor settings}, journal = {Accepted in the British Medical Journal Open}, year = {2012}, author = {Ellington, L and Gilman, R and Tielsch, J and Steinhoff, M and Figueroa, D and Rodriguez, S and Caffo, B and Tracey, B and West, J and Checkley, W} } @article {841, title = {Dissociable influences of opiates and expectations on pain.}, journal = {J Neurosci}, volume = {32}, year = {2012}, month = {2012 Jun 6}, pages = {8053-64}, abstract = {

Placebo treatments and opiate drugs are thought to have common effects on the opioid system and pain-related brain processes. This has created excitement about the potential for expectations to modulate drug effects themselves. If drug effects differ as a function of belief, this would challenge the assumptions underlying the standard clinical trial. We conducted two studies to directly examine the relationship between expectations and opioid analgesia. We administered the opioid agonist remifentanil to human subjects during experimental thermal pain and manipulated participants{\textquoteright} knowledge of drug delivery using an open-hidden design. This allowed us to test drug effects, expectancy (knowledge) effects, and their interactions on pain reports and pain-related responses in the brain. Remifentanil and expectancy both reduced pain, but drug effects on pain reports and fMRI activity did not interact with expectancy. Regions associated with pain processing showed drug-induced modulation during both Open and Hidden conditions, with no differences in drug effects as a function of expectation. Instead, expectancy modulated activity in frontal cortex, with a separable time course from drug effects. These findings reveal that opiates and placebo treatments both influence clinically relevant outcomes and operate without mutual interference.

}, keywords = {Analgesics, Opioid, Anticipation, Psychological, Behavior, brain mapping, Dose-Response Relationship, Drug, Female, Hemodynamics, Hot Temperature, Humans, Image Processing, Computer-Assisted, Injections, Intravenous, Linear Models, Magnetic Resonance Imaging, Male, Pain, Pain Measurement, Piperidines, Young Adult}, issn = {1529-2401}, doi = {10.1523/JNEUROSCI.0383-12.2012}, author = {Atlas, Lauren Y and Whittington, Robert A and Lindquist, Martin A and Wielgosz, Joe and Sonty, Nomita and Wager, Tor D} } @article {nicole, title = {Distribution of cell-free and cell-associated HIV surrogates in the female genital tract following simulated vaginal intercourse}, journal = {Appeared online in the Journal of Infectious Diseases}, year = {2012}, author = {Louissaint, N and Nimmagadda, S and Bakshi, R and Du, Y and Macura, K and King, K and Wahl, R and Goldsmith, J and Caffo, B and Cao, Y and Anderson, J and Fuchs, E and Hendrix, C} } @article {cribben2012dynamic, title = {Dynamic connectivity regression: Determining state-related changes in brain connectivity}, journal = {NeuroImage}, year = {2012}, publisher = {Elsevier}, author = {Cribben, Ivor and Haraldsdottir, Ragnheidur and Atlas, Lauren Y and Wager, Tor D and Lindquist, Martin A} } @article {842, title = {Dynamic connectivity regression: determining state-related changes in brain connectivity.}, journal = {Neuroimage}, volume = {61}, year = {2012}, month = {2012 Jul 16}, pages = {907-20}, abstract = {

Most statistical analyses of fMRI data assume that the nature, timing and duration of the psychological processes being studied are known. However, often it is hard to specify this information a priori. In this work we introduce a data-driven technique for partitioning the experimental time course into distinct temporal intervals with different multivariate functional connectivity patterns between a set of regions of interest (ROIs). The technique, called Dynamic Connectivity Regression (DCR), detects temporal change points in functional connectivity and estimates a graph, or set of relationships between ROIs, for data in the temporal partition that falls between pairs of change points. Hence, DCR allows for estimation of both the time of change in connectivity and the connectivity graph for each partition, without requiring prior knowledge of the nature of the experimental design. Permutation and bootstrapping methods are used to perform inference on the change points. The method is applied to various simulated data sets as well as to an fMRI data set from a study (N=26) of a state anxiety induction using a socially evaluative threat challenge. The results illustrate the method{\textquoteright}s ability to observe how the networks between different brain regions changed with subjects{\textquoteright} emotional state.

}, keywords = {Algorithms, Brain, brain mapping, Computer Simulation, Emotions, Humans, Image Interpretation, Computer-Assisted, Magnetic Resonance Imaging, Neural Pathways}, issn = {1095-9572}, doi = {10.1016/j.neuroimage.2012.03.070}, author = {Cribben, Ivor and Haraldsdottir, Ragnheidur and Atlas, Lauren Y and Wager, Tor D and Lindquist, Martin A} } @article {lindquist2012estimating, title = {Estimating and testing variance components in a multi-level GLM}, journal = {Neuroimage}, volume = {59}, number = {1}, year = {2012}, pages = {490{\textendash}501}, publisher = {Elsevier}, author = {Lindquist, Martin A and Spicer, Julie and Asllani, Iris and Wager, Tor D} } @article {844, title = {Estimating and testing variance components in a multi-level GLM.}, journal = {Neuroimage}, volume = {59}, year = {2012}, month = {2012 Jan 2}, pages = {490-501}, abstract = {

Most analysis of multi-subject fMRI data is concerned with determining whether there exists a significant population-wide {\textquoteright}activation{\textquoteright} in a comparison between two or more conditions. This is typically assessed by testing the average value of a contrast of parameter estimates (COPE) against zero in a general linear model (GLM) analysis. However, important information can also be obtained by testing whether there exist significant individual differences in effect magnitude between subjects, i.e. whether the variance of a COPE is significantly different from zero. Intuitively, such a test amounts to testing whether inter-individual differences are larger than would be expected given the within-subject error variance. We compare several methods for estimating variance components, including a) a na{\"\i}ve estimate using ordinary least squares (OLS); b) linear mixed effects in R (LMER); c) a novel Matlab implementation of iterative generalized least squares (IGLS) and its restricted maximum likelihood variant (RIGLS). All methods produced reasonable estimates of within- and between-subject variance components, with IGLS providing an attractive balance between sensitivity and appropriate control of false positives. Finally, we use the IGLS method to estimate inter-subject variance in a perfusion fMRI study (N=18) of social evaluative threat, and show evidence for significant inter-individual differences in ventromedial prefrontal cortex (VMPFC), amygdala, hippocampus and medial temporal lobes, insula, and brainstem, with predicted inverse coupling between VMPFC and the midbrain periaqueductal gray only when high inter-individual variance was used to define the seed for functional connectivity analyses. In sum, tests of variance provides a way of selecting regions that show significant inter-individual variability for subsequent analyses that attempt to explain those individual differences.

}, keywords = {Brain, brain mapping, Humans, Image Interpretation, Computer-Assisted, Linear Models, Magnetic Resonance Imaging, Models, Neurological, Sensitivity and Specificity}, issn = {1095-9572}, doi = {10.1016/j.neuroimage.2011.07.077}, author = {Lindquist, Martin A and Spicer, Julie and Asllani, Iris and Wager, Tor D} } @article {rectalab, title = {Quantification of the spatial distribution of rectally-applied surrogates for microbicide and semen in colon with SPECT imaging}, journal = {Accepted in the British Journal of Clinical Pharmacology}, year = {2012}, author = {Cao, Y and Caffo, B and Fuchs, E and Lee, L and Du, Y and Li, L and Bakshi, R and Khan, W and Wahl, R and Grohskopf, L and Hendrix, C} } @article {PACE:PACE2905, title = {Clinical predictors of conduction disease progression in type I myotonic muscular dystrophy}, journal = {Pacing and Clinical Electrophysiology, PMCID: PMC3035751}, volume = {34}, number = {2}, year = {2011}, pages = {171{\textendash}176}, publisher = {Blackwell Publishing Inc}, keywords = {cardiomyopathy, conduction disease, electrocardiography, myotonic muscular dystrophy, sudden death}, issn = {1540-8159}, doi = {10.1111/j.1540-8159.2010.02905.x}, url = {http://dx.doi.org/10.1111/j.1540-8159.2010.02905.x}, author = {Nazarian, S and Wagner, K and Caffo, B and Tomaselli, G} } @article {Gold:Wand:Crai:func:2011, title = {Functional Regression Via Variational Bayes}, journal = {Electronic Journal of Statistics}, volume = {5}, year = {2011}, pages = {572{\textendash}602}, keywords = {approximate Bayesian inference, Markov chain Monte Carlo, penalized splines}, author = {Goldsmith, J and Wand, Matt P. and Crainiceanu, C} } @article {pmid21853058, title = {The impact of utilizing different optical coherence tomography devices for clinical purposes and in multiple sclerosis trials}, journal = {PLoS ONE}, volume = {6}, number = {8}, year = {2011}, pages = {e22947}, author = {Warner, C. V. and Syc, S. B. and Stankiewicz, A. M. and Hiremath, G. and Farrell, S and Crainiceanu, C and Conger, A. and Frohman, T. C. and Bisker, E. R. and Balcer, L and Frohman, E. M. and Calabresi, P and Saidha, S.} } @article {atlas, title = {Brain mediators of predictive cue effects on perceived pain}, journal = {J Neurosci}, volume = {30}, year = {2010}, pages = {12964-77}, author = {Atlas, L.Y. and Bolger, N. and Lindquist, Martin A and Wager, T.D.} } @article {846, title = {Brain mediators of predictive cue effects on perceived pain.}, journal = {J Neurosci}, volume = {30}, year = {2010}, month = {2010 Sep 29}, pages = {12964-77}, abstract = {

Information about upcoming pain strongly influences pain experience in experimental and clinical settings, but little is known about the brain mechanisms that link expectation and experience. To identify the pathways by which informational cues influence perception, analyses must jointly consider both the effects of cues on brain responses and the relationship between brain responses and changes in reported experience. Our task and analysis strategy were designed to test these relationships. Auditory cues elicited expectations for barely painful or highly painful thermal stimulation, and we assessed how cues influenced human subjects{\textquoteright} pain reports and brain responses to matched levels of noxious heat using functional magnetic resonance imaging. We used multilevel mediation analysis to identify brain regions that (1) are modulated by predictive cues, (2) predict trial-to-trial variations in pain reports, and (3) formally mediate the relationship between cues and reported pain. Cues influenced heat-evoked responses in most canonical pain-processing regions, including both medial and lateral pain pathways. Effects on several regions correlated with pretask expectations, suggesting that expectancy plays a prominent role. A subset of pain-processing regions, including anterior cingulate cortex, anterior insula, and thalamus, formally mediated cue effects on pain. Effects on these regions were in turn mediated by cue-evoked anticipatory activity in the medial orbitofrontal cortex (OFC) and ventral striatum, areas not previously directly implicated in nociception. These results suggest that activity in pain-processing regions reflects a combination of nociceptive input and top-down information related to expectations, and that anticipatory processes in OFC and striatum may play a key role in modulating pain processing.

}, keywords = {Adult, Brain, Cognition, Cues, Female, Hot Temperature, Humans, Male, Pain, Pain Threshold, Perception, Physical Stimulation}, issn = {1529-2401}, doi = {10.1523/JNEUROSCI.0057-10.2010}, author = {Atlas, Lauren Y and Bolger, Niall and Lindquist, Martin A and Wager, Tor D} } @article {Paninski2010, title = {A new look at state-space models for neural data.}, journal = {Journal of computational neuroscience}, volume = {29}, number = {1-2}, year = {2010}, pages = {107{\textendash}26}, abstract = {

State space methods have proven indispensable in neural data analysis. However, common methods for performing inference in state-space models with non-Gaussian observations rely on certain approximations which are not always accurate. Here we review direct optimization methods that avoid these approximations, but that nonetheless retain the computational efficiency of the approximate methods. We discuss a variety of examples, applying these direct optimization techniques to problems in spike train smoothing, stimulus decoding, parameter estimation, and inference of synaptic properties. Along the way, we point out connections to some related standard statistical methods, including spline smoothing and isotonic regression. Finally, we note that the computational methods reviewed here do not in fact depend on the state-space setting at all; instead, the key property we are exploiting involves the bandedness of certain matrices. We close by discussing some applications of this more general point of view, including Markov chain Monte Carlo methods for neural decoding and efficient estimation of spatially-varying firing rates.

}, keywords = {1 introduction, Action Potentials, Action Potentials: physiology, Animals, Computer Simulation, for inference in state-space, forward-backward methods, hidden markov model, models, neural coding, Neurological, Neurons, Neurons: physiology, Retinal Ganglion Cells, Retinal Ganglion Cells: physiology, state-space models, Statistical, Synapses, Synapses: physiology, tridiagonal matrix}, issn = {1573-6873}, doi = {10.1007/s10827-009-0179-x}, url = {http://www.ncbi.nlm.nih.gov/pubmed/19649698}, author = {Paninski, Liam and Ahmadian, Yashar and Gil, Daniel and Shinsuke, Ferreira and Rahnama, Kamiar and Michael, Rad and Vogelstein, Joshua T and Wu, Wei and Ferreira, Daniel Gil and Koyama, Shinsuke and {Rahnama Rad}, Kamiar and Vidne, Michael} } @article {nazarian:qrs, title = {QRS Prolongation in Myotonic Muscular Dystrophy and Diffuse Fibrosis on Cardiac Magnetic Resonance}, journal = {Magnetic Resonance in Medicine, PMCID: PMC3034129}, volume = {64}, number = {1}, year = {2010}, pages = {107{\textendash}114}, author = {Nazarian, S and Bluemke, D and Wagner, K and Zviman, M and Turkbey, E and Caffo, B and Shehata, M and Edwards,D and Butcher, B and Calkins, H and Berger, R and Halperin, H and Tomaselli, G} } @article {hao, title = {Redefining CpG Islands Using a Hidden Markov Models}, journal = {Biostatistics, PMCID: PMC2883304}, volume = {11}, number = {3}, year = {2010}, pages = {499{\textendash}514}, author = {Wu, H and Caffo, B and Jaffee, H and Feinberg, A and Irizarry, R} } @article {chen2009adaptive, title = {Adaptive control of the false discovery rate in voxel-based morphometry}, journal = {Human Brain Mapping, NIHMSID: 316414}, volume = {30}, number = {7}, year = {2009}, pages = {2304{\textendash}2311}, publisher = {Wiley Subscription Services, Inc., A Wiley Company Hoboken}, author = {Chen, S and Wang, C. and Eberly, L and Caffo, B and Schwartz, B} } @article {Wager09a, title = {Brain mediators of cardiovascular responses to social threat, Part I: Reciprocal dorsal and ventral sub-regions of the medial prefrontal cortex and heart-rate reactivity}, journal = {NeuroImage}, volume = {47}, year = {2009}, pages = {821-835}, author = {Wager, T.D. and Waugh, C.E. and Lindquist, Martin A and Noll, D.C. and Fredrickson, B.L. and Taylor, S.F.} } @article {Wager09b, title = {Brain mediators of cardiovascular responses to social threat, Part II: Prefrontal subcortical pathways and relationship with anxiety}, journal = {NeuroImage}, volume = {47}, year = {2009}, pages = {836-851}, author = {Wager, T.D. and van Ast, V. and Davidson, M.L. and Lindquist, Martin A and Ochsner, K.N.} } @article {wager2009evaluating, title = {Evaluating the consistency and specificity of neuroimaging data using meta-analysis}, journal = {Neuroimage}, volume = {45}, number = {1}, year = {2009}, pages = {S210{\textendash}S221}, publisher = {Elsevier}, author = {Wager, Tor D and Lindquist, Martin A and Nichols, Thomas E and Kober, Hedy and Van Snellenberg, Jared X} } @article {pmid20049214, title = {Mercury induces an unopposed inflammatory response in human peripheral blood mononuclear cells in vitro}, journal = {Environ. Health Perspect.}, volume = {117}, number = {12}, year = {2009}, month = {Dec}, pages = {1932{\textendash}1938}, author = {Gardner, R. M. and Nyland, J. F. and Evans, S. L. and Wang, S. B. and Doyle, K. M. and Crainiceanu, C and Silbergeld, E. K.} } @article {lindquist09, title = {Modeling the Hemodynamic Response Function in fMRI: Efficiency, Bias and Mis-modeling}, journal = {NeuroImage}, volume = {45}, year = {2009}, pages = {S187-S198}, author = {Lindquist, Martin A and Loh, J.M. and Atlas, L. and Wager, T.D.} } @article {VogelsteinPaninski09, title = {Spike inference from calcium imaging using sequential Monte Carlo methods.}, journal = {Biophys J}, volume = {97}, number = {2}, year = {2009}, pages = {636{\textendash}655}, publisher = {Department of Neuroscience, The Johns Hopkins School of Medicine, Baltimore, Maryland, USA. joshuav@jhu.edu}, abstract = {

As recent advances in calcium sensing technologies facilitate simultaneously imaging action potentials in neuronal populations, complementary analytical tools must also be developed to maximize the utility of this experimental paradigm. Although the observations here are fluorescence movies, the signals of interest{\textendash}spike trains and/or time varying intracellular calcium concentrations{\textendash}are hidden. Inferring these hidden signals is often problematic due to noise, nonlinearities, slow imaging rate, and unknown biophysical parameters. We overcome these difficulties by developing sequential Monte Carlo methods (particle filters) based on biophysical models of spiking, calcium dynamics, and fluorescence. We show that even in simple cases, the particle filters outperform the optimal linear (i.e., Wiener) filter, both by obtaining better estimates and by providing error bars. We then relax a number of our model assumptions to incorporate nonlinear saturation of the fluorescence signal, as well external stimulus and spike history dependence (e.g., refractoriness) of the spike trains. Using both simulations and in vitro fluorescence observations, we demonstrate temporal superresolution by inferring when within a frame each spike occurs. Furthermore, the model parameters may be estimated using expectation maximization with only a very limited amount of data (e.g., approximately 5-10 s or 5-40 spikes), without the requirement of any simultaneous electrophysiology or imaging experiments.

}, keywords = {Animals, Biological, Calcium, cytology/metabolism, Fluorescence, Inbred C57BL, Intracellular Space, metabolism, Mice, models, Monte Carlo Method, Neurons, Probability, Time Factors}, doi = {10.1016/j.bpj.2008.08.005}, url = {http://dx.doi.org/10.1016/j.bpj.2008.08.005}, author = {Vogelstein, Joshua T and Watson, Brendon O and Packer, Adam M and Yuste, Rafael and Jedynak, Bruno and Paninski, Liam} } @article {grinband2008detection, title = {Detection of time-varying signals in event-related fMRI designs}, journal = {Neuroimage}, volume = {43}, number = {3}, year = {2008}, pages = {509{\textendash}520}, publisher = {Elsevier}, author = {Grinband, Jack and Wager, Tor D and Lindquist, Martin A and Ferrera, Vincent P and Hirsch, Joy} } @article {pmid18552590, title = {Model selection and health effect estimation in environmental epidemiology}, journal = {Epidemiology}, volume = {19}, number = {4}, year = {2008}, month = {Jul}, pages = {558{\textendash}560}, author = {Dominici, F. and Wang, C. and Crainiceanu, C and Parmigiani, G.} } @article {Wager08, title = {Prefrontal-Subcortical Pathways Mediating Successful Emotion Regulation}, journal = {Neuron}, volume = {59}, year = {2008}, pages = {1037-1050}, author = {Wager, T.D. and Davidson, M.L. and Hughes, B.L. and Lindquist, Martin A and Ochsner, K.N.} } @article {wager2007meta, title = {Meta-analysis of functional neuroimaging data: current and future directions}, journal = {Social Cognitive and Affective Neuroscience}, volume = {2}, number = {2}, year = {2007}, pages = {150{\textendash}158}, publisher = {Oxford University Press}, author = {Wager, Tor D and Lindquist, Martin A and Kaplan, Lauren} } @article {lindquist2007modeling, title = {Modeling state-related fMRI activity using change-point theory}, journal = {NeuroImage}, volume = {35}, number = {3}, year = {2007}, pages = {1125{\textendash}1141}, publisher = {Elsevier}, author = {Lindquist, Martin A and Waugh, Christian and Wager, Tor D} } @article {lindquist07, title = {Validity and Power in Hemodynamic Response Modeling: A comparison study and a new approach}, journal = {Human Brain Mapping}, volume = {28}, year = {2007}, pages = {764-784}, author = {Lindquist, Martin A and Wager, T.D.} } @article {Crai:Rupp:Clae:Wand:exac:2005, title = {Exact Likelihood Ratio Tests for Penalised Splines}, journal = {Biometrika}, volume = {92}, number = {1}, year = {2005}, pages = {91{\textendash}103}, keywords = {Linear mixed model, Penalised spline, Smoothing, Zero variance component}, author = {Crainiceanu, C and Ruppert, D. and Claeskens, Gerda and Wand, M. P.} } @article {Greenspan1997, title = {Loss of FHIT expression in cervical carcinoma cell lines and primary tumors.}, journal = {Cancer Research}, volume = {57}, number = {21}, year = {1997}, pages = {4692{\textendash}4698}, publisher = {Department of Pathology, The Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA.}, abstract = {

Allelic deletions involving the short arm of chromosome 3 (3p13-21.1) have been observed frequently in cervical carcinomas. Recently, a candidate tumor suppressor gene, FHIT (Fragile Histidine Triad), was cloned and mapped to this chromosomal region (3p14.2). Abnormal FHIT transcripts have been identified previously in a variety of tumor cell lines and primary carcinomas, although their significance and the molecular mechanisms underlying their origin remain incompletely defined. In addition, integration of human papillomavirus DNA has been identified at a fragile site (FRA3B) within the FHIT locus in cervical cancer. These observations motivated us to evaluate FHIT mRNA and protein expression in cervical cancer cell lines, primary cervical carcinomas, and normal tissues. Transcripts of the expected size and sequence were the predominant species identified by reverse transcription (RT)-PCR in cultured keratinocytes and all normal tissues evaluated. In contrast, aberrant FHIT transcripts were readily demonstrated in 6 of 7 cervical carcinoma cell lines and 17 of 25 (68\%) primary cervical carcinomas. Northern blot analyses demonstrated reduced or absent FHIT expression in the cervical carcinoma cell lines, particularly those with aberrant RT-PCR products. Immunohistochemical analysis of Fhit expression in cervical tissues revealed strong immunoreactivity in nonneoplastic squamous and glandular cervical epithelium and marked reduction or loss of Fhit protein in 25 of 33 (76\%) primary cervical carcinomas. In those cervical cancer cell lines and primary tumors with exclusively aberrant or absent FHIT transcripts by RT-PCR, Fhit protein expression was always markedly reduced or absent. The frequent alterations in FHIT expression in many cervical carcinomas, but not in normal tissues, suggest that FHIT gene alterations may play an important role in cervical tumorigenesis.

}, url = {http://www.ncbi.nlm.nih.gov/pubmed/9354423}, author = {Greenspan, D L and Connolly, D C and Wu, R and Lei, R Y and Vogelstein, Joshua T and Kim, Y T and Mok, J E and Mu{\~n}oz, N and Bosch, F X and Shah, K and Cho, K R} }