@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 {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 {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} }