A5062906939- Functional Brain Connectivity Studies
- Advanced MRI Techniques and Applications
- Neural dynamics and brain function
- Advanced Neuroimaging Techniques and Applications
- EEG and Brain-Computer Interfaces
- Blind Source Separation Techniques
- Optical Imaging and Spectroscopy Techniques
- Statistical Methods and Inference
- Medical Image Segmentation Techniques
- Psychedelics and Drug Studies
- Statistical Methods and Bayesian Inference
- Multiple Sclerosis Research Studies
- Dementia and Cognitive Impairment Research
- Autism Spectrum Disorder Research
- Meta-analysis and systematic reviews
- Fault Detection and Control Systems
- Tryptophan and brain disorders
- Amyotrophic Lateral Sclerosis Research
- Cell Image Analysis Techniques
- Health, Environment, Cognitive Aging
- Alzheimer's disease research and treatments
- Neurotransmitter Receptor Influence on Behavior
- Morphological variations and asymmetry
- Parkinson's Disease Mechanisms and Treatments
- Health Systems, Economic Evaluations, Quality of Life
Indiana University – Purdue University Indianapolis
2018-2025
Indiana University Bloomington
2015-2024
Indiana University
2019-2024
Johns Hopkins University
2014-2017
Rice University
2016
University of Pennsylvania
2016
National Institute of Neurological Disorders and Stroke
2016
Duke University
2016
North Carolina State University
2016
Neuroscience is advancing standardization and tool development to support rigor transparency. Consequently, data pipeline complexity has increased, hindering FAIR (findable, accessible, interoperable reusable) access. brainlife.io was developed democratize neuroimaging research. The platform provides standardization, management, visualization processing automatically tracks the provenance history of thousands objects. Here, described evaluated for validity, reliability, reproducibility,...
Objective The need for appropriate multiple comparisons correction when performing statistical inference is not a new problem. However, it has come to the forefront in many modern data-intensive disciplines. For example, researchers areas such as imaging and genetics are routinely required simultaneously perform thousands of tests. Ignoring this multiplicity can cause severe problems with false positives, thereby introducing nonreproducible results into literature. Methods This article...
Significance Science is rapidly changing with the current movement to improve science focused largely on reproducibility/replicability and open practices. Through network modeling semantic analysis, this article provides an initial exploration of structure, cultural frames collaboration prosociality, representation women in reproducibility literatures. Network analyses reveal that literatures are emerging relatively independently few common papers or authors. Open has a more collaborative...
Inference in neuroimaging typically occurs at the level of focal brain areas or circuits. Yet, increasingly, well-powered studies paint a much richer picture broad-scale effects distributed throughout brain, suggesting that many reports may only reflect tip iceberg underlying effects. How versus perspectives influence inferences we make has not yet been comprehensively evaluated using real data. Here, compare sensitivity and specificity across procedures representing multiple levels...
There is significant interest in adopting surface- and grayordinate-based analysis of MR data for a number reasons, including improved whole-cortex visualization, the ability to perform surface smoothing avoid issues associated with volumetric smoothing, inter-subject alignment, reduced dimensionality. The CIFTI grayordinate file format introduced by Human Connectome Project further advances combining gray matter from left right cortical hemispheres subcortex cerebellum into single file....
Artifacts in functional MRI (fMRI) data cause deviations from common distributional assumptions, introduce spatial and temporal outliers, reduce the signal-to-noise ratio of -- all which can have negative consequences for downstream statistical analysis. Scrubbing is a technique excluding fMRI volumes thought to be contaminated by artifacts generally comes two flavors. Motion scrubbing based on subject head motion-derived measures popular but suffers number drawbacks, especially high rates...
Cortical surface fMRI (cs-fMRI) has recently grown in popularity versus traditional volumetric fMRI. In addition to offering better whole-brain visualization, dimension reduction, removal of extraneous tissue types, and improved alignment cortical areas across subjects, it is also more compatible with common assumptions Bayesian spatial models. However, as no model been proposed for cs-fMRI data, most analyses continue employ the classical general linear (GLM), a "massive univariate"...
Large brain imaging databases contain a wealth of information on organization in the populations they target, and individual variability. While such have been used to study group-level features directly, are currently underutilized as resource inform single-subject analysis. Here, we propose leveraging contained large functional magnetic resonance (fMRI) by establishing population priors employ an empirical Bayesian framework. We focus estimation networks source signals independent component...
Classic psychedelics, such as psilocybin and LSD, other serotonin 2A receptor (5-HT2AR) agonists evoke acute alterations in perception cognition. Altered thalamocortical connectivity has been hypothesized to underlie these effects, which is supported by some functional MRI (fMRI) studies. These studies have treated the thalamus a unitary structure, despite known differential 5-HT2AR expression specificity of different intrathalamic nuclei. Independent Component Analysis (ICA) previously used...
Background: Despite reports of gross motor problems in mild cognitive impairment (MCI) and Alzheimer’s disease (AD), fine function has been relatively understudied. Objective: We examined if finger tapping is affected AD, related to AD biomarkers, able classify MCI or AD. Methods: Forty-seven cognitively normal, 27 amnestic MCI, 26 subjects completed unimanual bimanual computerized tests. tested 1) group differences with permutation models; 2) associations between biomarkers (PET amyloid-β,...
Current theories of the neurobiological basis autism spectrum disorder ( ASD ) posit an altered pattern connectivity in large‐scale brain networks. Here we used diffusion tensor imaging to investigate microstructural properties white matter WM that mediates interregional 36 high‐functioning children with HF‐ASD as compared 37 controls. By employing atlas‐based analysis using large deformation diffeometric morphic mapping registration, a widespread but left‐lateralized abnormalities was...
Objective To determine whether the presence and degree of muscle weakness in scleroderma is associated with disability. Methods The study included a cohort 1,718 patients who had available data on strength primary independent variable was as defined by maximum Medsger severity score outcome disability measured last recorded Health Assessment Questionnaire index (HAQ DI) score. Univariate regression analyses were performed to assess association HAQ DI scores other characteristics. A...
The general linear model (GLM) is a widely popular and convenient tool for estimating the functional brain response identifying areas of significant activation during task or stimulus. However, classical GLM based on massive univariate approach that does not explicitly leverage similarity patterns among neighboring locations. As result, it tends to produce noisy estimates be underpowered detect activations, particularly in individual subjects small groups. A recently proposed alternative,...
Abstract Resting-state functional connectivity is a widely used approach to study the brain network organization during early development. However, estimation of networks in individual infants has been rather elusive due unique challenges involved with magnetic resonance imaging (fMRI) data from young populations. Here, we use fMRI developing Human Connectome Project (dHCP) database characterize variability large cohort term-born (N = 289) using novel data-driven Bayesian framework. To...
Violence is a major risk factor for depression across development. Depression quickly worsens during early adolescence, however, and especially among females, who experience worse following threats than males. This may be because they perceive future as less controllable. Evidence suggests that features of the salience network serve particularly critical mechanisms explaining sex differences on in response to threat, those with depressive disorders have more expansive networks controls,...
Outlier detection for high-dimensional (HD) data is a popular topic in modern statistical research. However, one source of HD that has received relatively little attention functional magnetic resonance images (fMRI), which consists hundreds thousands measurements sampled at time points. At when the availability fMRI rapidly growing-primarily through large, publicly available grassroots datasets-automated quality control and outlier methods are greatly needed. We propose principal components...
Healthcare industry players make payments to medical providers for non-research expenses. While these may pose conflicts of interest, their relationship with overall healthcare costs remains largely unknown. In this study, we linked Open Payments data on providers' Medicare costs. We investigated 374,766 and demonstrate that receiving higher amounts tend bill drug Specifically, find a 10% increase in is associated 1.3% 1.8% For typical provider, example, or $25 annual would be approximately...