@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 {pmid22499683, title = {Fast wavelet based functional models for transcriptome analysis with tiling arrays}, journal = {Stat Appl Genet Mol Biol}, volume = {11}, number = {1}, year = {2012}, pages = {1{\textendash}36}, author = {Clement, Lieven and De Beuf, K. and Thas, O. and Vuylsteke, M. and Irizarry, R and Crainiceanu, C} } @article {lindquist12, title = {Functional causal mediation analysis with an application to brain connectivity}, journal = {Journal of the American Statistical Association, to appear.}, year = {2012}, author = {Lindquist, Martin A} } @article {840, title = {Functional Causal Mediation Analysis With an Application to Brain Connectivity.}, journal = {J Am Stat Assoc}, volume = {107}, year = {2012}, month = {2012 Dec 21}, pages = {1297-1309}, abstract = {

Mediation analysis is often used in the behavioral sciences to investigate the role of intermediate variables that lie on the causal path between a randomized treatment and an outcome variable. Typically, mediation is assessed using structural equation models (SEMs), with model coefficients interpreted as causal effects. In this article, we present an extension of SEMs to the functional data analysis (FDA) setting that allows the mediating variable to be a continuous function rather than a single scalar measure, thus providing the opportunity to study the functional effects of the mediator on the outcome. We provide sufficient conditions for identifying the average causal effects of the functional mediators using the extended SEM, as well as weaker conditions under which an instrumental variable estimand may be interpreted as an effect. The method is applied to data from a functional magnetic resonance imaging (fMRI) study of thermal pain that sought to determine whether activation in certain brain regions mediated the effect of applied temperature on self-reported pain. Our approach provides valuable information about the timing of the mediating effect that is not readily available when using the standard nonfunctional approach. To the best of our knowledge, this work provides the first application of causal inference to the FDA framework.

}, issn = {0162-1459}, doi = {10.1080/01621459.2012.695640}, author = {Lindquist, Martin A} } @article {mhssr2012, title = {Functional Generalized Additive Models}, journal = {J. of Computational and Graphical Statistics}, year = {2012}, pages = {to appear}, author = {McLean, M. and Hooker, G. and Staicu, A. M. and Scheipl, F. and Ruppert, D.} } @article {VP11_QAP, title = {Fast Inexact Graph Mathing with Applications in Statistical Connectomics}, journal = {under review}, year = {2011}, author = {Vogelstein, Joshua T and Conroy, John C and Podrazik, Louis J and Kratzer, Steven G and Fishkind, Donniell E and Vogelstein, Joshua T and Priebe, Carey E} } @article {vadimNI, title = {Functional principal components model for high-dimensional brain imaging}, journal = {Neuroimage, NIHSMID: 316403}, volume = {58}, number = {3}, year = {2011}, pages = {772 {\textendash} 784}, author = {Zipunnikov, V. and Caffo, B and Yousem, D and Davatziko, C and Schwartz, B and Crainiceanu, C} } @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 {reiss2010fast, title = {Fast function-on-scalar regression with penalized basis expansions}, journal = {International Journal of Biostatistics}, volume = {6}, number = {1}, year = {2010}, pages = {article{\textendash}28}, author = {Reiss, P.T. and Huang, L. and Mennes, M.} } @article {pmid20089508, title = {Fast methods for spatially correlated multilevel functional data}, journal = {Biostatistics}, volume = {11}, number = {2}, year = {2010}, month = {Apr}, pages = {177{\textendash}194}, author = {Staicu, A. M. and Crainiceanu, C and Carroll, R. J.} } @article {Kriv:Crai:Kaue:fast:2008, title = {Fast Adaptive Penalized Splines}, journal = {Journal of Computational and Graphical Statistics}, volume = {17}, number = {1}, year = {2008}, pages = {1{\textendash}20}, keywords = {function of locally varying complexity, hierarchical mixed model, Laplace approximation}, author = {Krivobokova, Tatyana and Crainiceanu, C and Kauermann, G{\"o}ran} } @article {stamatakis2008fasting, title = {Fasting Glycemia in Sleep Disordered Breathing: Lowering the Threshold on Oxyhemoglobin Desaturation}, journal = {Sleep, PMCID: PMC2491502}, volume = {31}, number = {7}, year = {2008}, pages = {1018{\textendash}1024}, publisher = {American Academy of Sleep Medicine}, author = {Stamatakis, K and Sanders, M and Caffo, B and Resnick, H and Gottlieb, D and Mehra, R and Punjabi, N} } @article {suskauer2008fmri, title = {fMRI of Intrasubject Variability in ADHD: Anomalous Premotor Activity With Prefrontal Compensation}, journal = {Journal of American Academy of Child \& Adolescent Psychiatry, NIHMSID: 71813}, volume = {47}, number = {10}, year = {2008}, pages = {1141{\textendash}1150}, author = {Suskauer, S and Simmonds, D and Caffo, B and Denckla, M and Pekar, J and Mostofsky, S} } @article {caffo2007flexible, title = {Flexible random intercept models for binary outcomes using mixtures of normals}, journal = {Computational Statistics and Data Analysis, PMCID: PMC2031853}, volume = {51}, number = {11}, year = {2007}, pages = {5220{\textendash}5235}, publisher = {Elsevier}, author = {Caffo, B and An, M and Rohde, C} } @article {bassett2006familial, title = {Familial risk for Alzheimer{\textquoteright}s disease alters fMRI activation patterns}, journal = {Brain, PMCID: PMC2744898}, volume = {129}, number = {5}, year = {2006}, pages = {1229{\textendash}1239}, publisher = {Oxford Univ Press}, author = {Bassett, S and Yousem, D and Cristinzio, C and Kusevic, I and Yassa, M and Caffo, B and Zeger, S} } @article {jones2006fixed, title = {Fixed-width output analysis for Markov chain Monte Carlo}, journal = {Journal of the American Statistical Association}, volume = {101}, number = {476}, year = {2006}, pages = {1537{\textendash}1547}, publisher = {ASA}, author = {Jones, G and Haran, M and Caffo, B and Neath, R} }