@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 = {<p>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.</p>},
	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 {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 = {<p>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.</p>},
	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}
}
