@article {833, title = {Cross-sectional and longitudinal association of body mass index and brain volume.}, journal = {Hum Brain Mapp}, volume = {35}, year = {2014}, month = {2014 Jan}, pages = {75-88}, abstract = {

Although a link between body mass index (BMI) and brain volume has been established in several cross-sectional studies, evidence of the association between change in BMI over time and changes in brain structure is limited. Using data from a cohort of 347 former lead workers and community controls with two magnetic resonance imaging scans over a period of ~5 years, we estimated cross-sectional and longitudinal associations of BMI and brain volume using both region of interest (ROI) and voxel-based morphometric (VBM) methods. We found that associations of BMI and brain volume were not significantly different in former lead workers when compared with community controls. In the cross-sectional analysis, higher BMIs were associated with smaller brain volumes in gray matter (GM) using both ROI and VBM approaches. No associations with white matter (WM) were observed. In the longitudinal analysis, higher baseline BMI was associated with greater decline in temporal and occipital GM ROI volumes. Change in BMI over the 5-year period was only associated with change in hippocampal volume and was not associated with change in any of the GM ROIs. Overall, higher BMI was associated with lower GM volume in several ROIs and with declines in volume in temporal and occipital GM over time. These results suggest that sustained high body mass may contribute to progressive temporal and occipital atrophy.

}, keywords = {Aged, Atrophy, Body Mass Index, Brain, Cross-Sectional Studies, Humans, Image Interpretation, Computer-Assisted, Longitudinal Studies, Magnetic Resonance Imaging, Male, Middle Aged, Obesity}, issn = {1097-0193}, doi = {10.1002/hbm.22159}, author = {Bobb, Jennifer F and Schwartz, Brian S and Davatzikos, Christos and Caffo, Brian} } @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 {817, title = {The neural correlates of learned motor acuity.}, journal = {J Neurophysiol}, volume = {112}, year = {2014}, month = {2014 Aug 15}, pages = {971-80}, abstract = {

We recently defined a component of motor skill learning as "motor acuity," quantified as a shift in the speed-accuracy trade-off function for a task. These shifts are primarily driven by reductions in movement variability. To determine the neural correlates of improvement in motor acuity, we devised a motor task compatible with magnetic resonance brain imaging that required subjects to make finely controlled wrist movements under visual guidance. Subjects were imaged on day 1 and day 5 while they performed this task and were trained outside the scanner on intervening days 2, 3, and 4. The potential confound of performance changes between days 1 and 5 was avoided by constraining movement time to a fixed duration. After training, subjects showed a marked increase in success rate and a reduction in trial-by-trial variability for the trained task but not for an untrained control task, without changes in mean trajectory. The decrease in variability for the trained task was associated with increased activation in contralateral primary motor and premotor cortical areas and in ipsilateral cerebellum. A global nonlocalizing multivariate analysis confirmed that learning was associated with increased overall brain activation. We suggest that motor acuity is acquired through increases in the number of neurons recruited in contralateral motor cortical areas and in ipsilateral cerebellum, which could reflect increased signal-to-noise ratio in motor output and improved state estimation for feedback corrections, respectively.

}, issn = {1522-1598}, doi = {10.1152/jn.00897.2013}, author = {Shmuelof, Lior and Yang, Juemin and Caffo, Brian and Mazzoni, Pietro and Krakauer, John W} } @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 {792, title = {Shrinkage prediction of seed-voxel brain connectivity using resting state fMRI.}, journal = {Neuroimage}, volume = {102 Pt 2}, year = {2014}, month = {2014 Nov 15}, pages = {938-44}, abstract = {

Resting-state functional magnetic resonance imaging (rs-fMRI) is used to investigate synchronous activations in spatially distinct regions of the brain, which are thought to reflect functional systems supporting cognitive processes. Analyses are often performed using seed-based correlation analysis, allowing researchers to explore functional connectivity between data in a seed region and the rest of the brain. Using scan-rescan rs-fMRI data, we investigate how well the subject-specific seed-based correlation map from the second replication of the study can be predicted using data from the first replication. We show that one can dramatically improve prediction of subject-specific connectivity by borrowing strength from the group correlation map computed using all other subjects in the study. Even more surprisingly, we found that the group correlation map provided a better prediction of a subject{\textquoteright}s connectivity than the individual{\textquoteright}s own data. While further discussion and experimentation are required to understand how this can be used in practice, results indicate that shrinkage-based methods that borrow strength from the population mean should play a role in rs-fMRI data analysis.

}, issn = {1095-9572}, doi = {10.1016/j.neuroimage.2014.05.043}, author = {Shou, Haochang and Eloyan, Ani and Nebel, Mary Beth and Mejia, Amanda and Pekar, James J and Mostofsky, Stewart and Caffo, Brian and Lindquist, Martin A and Crainiceanu, Ciprian M} } @article {828, title = {Axial 3D gradient-echo imaging for improved multiple sclerosis lesion detection in the cervical spinal cord at 3T.}, journal = {Neuroradiology}, volume = {55}, year = {2013}, month = {2013 Mar}, pages = {431-9}, abstract = {

INTRODUCTION: In multiple sclerosis (MS), spinal cord imaging can help in diagnosis and follow-up evaluation. However, spinal cord magnetic resonance imaging (MRI) is technically challenging, and image quality, particularly in the axial plane, is typically poor compared to brain MRI. Because gradient-recalled echo (GRE) images might offer improved contrast resolution within the spinal cord at high magnetic field strength, both without and with a magnetization transfer prepulse, we compared them to T2-weighted fast-spin-echo (T2-FSE) images for the detection of MS lesions in the cervical cord at 3T.

METHODS: On a clinical 3T MRI scanner, we studied 62 MS cases and 19 healthy volunteers. Axial 3D GRE sequences were performed without and with off-resonance radiofrequency irradiation. To mimic clinical practice, all images were evaluated in conjunction with linked images from a sagittal short tau inversion recovery scan, which is considered the gold standard for lesion detection in MS. Two experienced observers recorded image quality, location and size of focal lesions, atrophy, swelling, and diffuse signal abnormality independently at first and then in consensus.

RESULTS: The number and volume of lesions detected with high confidence was more than three times as high on both GRE sequences compared to T2-FSE (p < 0.0001). Approximately 5 \% of GRE scans were affected by artifacts that interfered with image interpretation, not significantly different from T2W-FSE.

CONCLUSIONS: Axial 3D GRE sequences are useful for MS lesion detection when compared to 2D T2-FSE sequences in the cervical spinal cord at 3T and should be considered when examining intramedullary spinal cord lesions.

}, keywords = {Adult, Aged, Algorithms, Cervical Vertebrae, Echo-Planar Imaging, Female, Humans, Image Enhancement, Image Interpretation, Computer-Assisted, Imaging, Three-Dimensional, Male, Middle Aged, Multiple Sclerosis, Reproducibility of Results, Sensitivity and Specificity, Spinal Cord}, issn = {1432-1920}, doi = {10.1007/s00234-012-1118-5}, author = {Ozturk, Arzu and Aygun, Nafi and Smith, Seth A and Caffo, Brian and Calabresi, Peter A and Reich, Daniel S} } @article {824, title = {A decision-theory approach to interpretable set analysis for high-dimensional data.}, journal = {Biometrics}, volume = {69}, year = {2013}, month = {2013 Sep}, pages = {614-23}, abstract = {

A key problem in high-dimensional significance analysis is to find pre-defined sets that show enrichment for a statistical signal of interest; the classic example is the enrichment of gene sets for differentially expressed genes. Here, we propose a new decision-theory approach to the analysis of gene sets which focuses on estimating the fraction of non-null variables in a set. We introduce the idea of "atoms," non-overlapping sets based on the original pre-defined set annotations. Our approach focuses on finding the union of atoms that minimizes a weighted average of the number of false discoveries and missed discoveries. We introduce a new false discovery rate for sets, called the atomic false discovery rate (afdr), and prove that the optimal estimator in our decision-theory framework is to threshold the afdr. These results provide a coherent and interpretable framework for the analysis of sets that addresses the key issues of overlapping annotations and difficulty in interpreting p values in both competitive and self-contained tests. We illustrate our method and compare it to a popular existing method using simulated examples, as well as gene-set and brain ROI data analyses.

}, keywords = {Algorithms, Bayes Theorem, Biometry, Brain, Computer Simulation, Data Interpretation, Statistical, Decision Theory, Functional Neuroimaging, Gene Expression Profiling, Genomics, Humans, Magnetic Resonance Imaging, Models, Statistical, Oligonucleotide Array Sequence Analysis}, issn = {1541-0420}, doi = {10.1111/biom.12060}, author = {Boca, Simina M and Bravo, H{\'e}ctor C{\'e}orrada and Caffo, Brian and Leek, Jeffrey T and Parmigiani, Giovanni} } @article {808, title = {Ironing out the statistical wrinkles in "ten ironic rules".}, journal = {Neuroimage}, volume = {81}, year = {2013}, month = {2013 Nov 1}, pages = {499-502}, abstract = {

The article "Ten ironic rules for non-statistical reviewers" (Friston, 2012) shares some commonly heard frustrations about the peer-review process that all researchers can identify with. Though we found the article amusing, we have some concerns about its description of a number of statistical issues. In this commentary we address these issues, as well as the premise of the article.

}, keywords = {Neuroimaging, Peer Review, Research, Research Design, Statistics as Topic}, issn = {1095-9572}, doi = {10.1016/j.neuroimage.2013.02.056}, author = {Lindquist, Martin A and Caffo, Brian and Crainiceanu, Ciprian} } @article {827, title = {Analysis of group ICA-based connectivity measures from fMRI: application to Alzheimer{\textquoteright}s disease.}, journal = {PLoS One}, volume = {7}, year = {2012}, month = {2012}, pages = {e49340}, abstract = {

Functional magnetic resonance imaging (fMRI) is a powerful tool for the in vivo study of the pathophysiology of brain disorders and disease. In this manuscript, we propose an analysis stream for fMRI functional connectivity data and apply it to a novel study of Alzheimer{\textquoteright}s disease. In the first stage, spatial independent component analysis is applied to group fMRI data to obtain common brain networks (spatial maps) and subject-specific mixing matrices (time courses). In the second stage, functional principal component analysis is utilized to decompose the mixing matrices into population-level eigenvectors and subject-specific loadings. Inference is performed using permutation-based exact logistic regression for matched pairs data. The method is applied to a novel fMRI study of Alzheimer{\textquoteright}s disease risk under a verbal paired associates task. We found empirical evidence of alternative ICA-based metrics of connectivity when comparing subjects evidencing mild cognitive impairment relative to carefully matched controls.

}, keywords = {Aged, Algorithms, Alzheimer Disease, Brain, brain mapping, Case-Control Studies, Female, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Middle Aged, Mild Cognitive Impairment, Nerve Net, Principal Component Analysis, Task Performance and Analysis, Time Factors}, issn = {1932-6203}, doi = {10.1371/journal.pone.0049340}, author = {Li, Shanshan and Eloyan, Ani and Joel, Suresh and Mostofsky, Stewart and Pekar, James and Bassett, Susan Spear and Caffo, Brian} } @article {813, title = {Movelets: A dictionary of movement.}, journal = {Electron J Stat}, volume = {6}, year = {2012}, month = {2012}, pages = {559-578}, abstract = {

Recent technological advances provide researchers with a way of gathering real-time information on an individual{\textquoteright}s movement through the use of wearable devices that record acceleration. In this paper, we propose a method for identifying activity types, like walking, standing, and resting, from acceleration data. Our approach decomposes movements into short components called "movelets", and builds a reference for each activity type. Unknown activities are predicted by matching new movelets to the reference. We apply our method to data collected from a single, three-axis accelerometer and focus on activities of interest in studying physical function in elderly populations. An important technical advantage of our methods is that they allow identification of short activities, such as taking two or three steps and then stopping, as well as low frequency rare(compared with the whole time series) activities, such as sitting on a chair. Based on our results we provide simple and actionable recommendations for the design and implementation of large epidemiological studies that could collect accelerometry data for the purpose of predicting the time series of activities and connecting it to health outcomes.

}, issn = {1935-7524}, doi = {10.1214/12-EJS684}, author = {Bai, Jiawei and Goldsmith, Jeff and Caffo, Brian and Glass, Thomas A and Crainiceanu, Ciprian M} } @article {830, title = {Total white matter hyperintensity volume in bipolar disorder patients and their healthy relatives.}, journal = {Bipolar Disord}, volume = {14}, year = {2012}, month = {2012 Dec}, pages = {888-93}, abstract = {

OBJECTIVES: White matter hyperintensities (WMH) are more common in subjects with bipolar disorder (BP) than in healthy subjects (HS). Few studies have examined the effect of the diagnostic type of bipolar illness on WMH burden, and none have approached this question through a direct measurement of the volume of affected white matter in relationship to familiality. In this pilot study, we utilized a volumetric measurement of WMH to investigate the relationship between the total volume of WMH and the familiality and type of BP.

METHODS: Forty-five individuals with bipolar I disorder (BP-I) with psychotic features, BP-I without psychotic features, or bipolar II disorder (BP-II), seven of their unaffected relatives, and 32 HS were recruited for participation. T-2 weighted magnetic resonance imaging scans were obtained on all subjects, and the total volume of all WMH for each subject was measured in cubic centimeters. The significance of difference between groups was tested using ANOVA with post-hoc adjustment for multiple comparisons. Further, we used logistic regression to test for trends between symptom load and total WMH volume.

RESULTS: The mean total volume of WMH in BP-I patients with psychotic features was significantly higher (p < 0.05) than that of HS. Further, we observed a positive linear trend by familiality and type of affectedness when comparing mean total WMH volume of HS, unaffected family members, subjects with BP-II, and BP-I with and without a history of psychosis (p < 0.05).

CONCLUSIONS: Based on a quantitative technique, WMH burden appears to be associated with familiality and type of BP. The significance of these findings remains to be fully elucidated.

}, keywords = {Adult, Analysis of Variance, Bipolar Disorder, Brain, Female, Humans, Image Processing, Computer-Assisted, Leukoencephalopathies, Magnetic Resonance Imaging, Male, Nerve Fibers, Myelinated}, issn = {1399-5618}, doi = {10.1111/bdi.12019}, author = {Tighe, Sarah K and Reading, Sarah A and Rivkin, Paul and Caffo, Brian and Schweizer, Barbara and Pearlson, Godfrey and Potash, James B and Depaulo, J Raymond and Bassett, Susan S} }