Amanda F. Mejia

发表

Template Independent Component Analysis: Targeted and Reliable Estimation of Subject-level Brain Networks Using Big Data Population Priors

Brian S. Caffo, Ying Guo, Amanda F. Mejia, 2019, Journal of the American Statistical Association.

A spatial template independent component analysis model for subject-level brain network estimation and inference

David Bolin, Brian S. Caffo, Amanda F. Mejia, 2020 .

Improving reliability of subject-level resting-state fMRI parcellation with shrinkage estimators

Martin A. Lindquist, Ciprian M. Crainiceanu, Amanda F. Mejia, 2014, NeuroImage.

Improved estimation of subject-level functional connectivity using full and partial correlation with empirical Bayes shrinkage

Martin A. Lindquist, Amanda F. Mejia, Mary Beth Nebel, 2018, NeuroImage.

Statistical estimation of T 1 relaxation times using conventional magnetic resonance imaging

Russell T. Shinohara, Daniel S. Reich, Amanda F. Mejia, 2016, NeuroImage.

Spatial Bayesian GLM on the cortical surface produces reliable task activations in individuals and groups

David Bolin, Amanda F. Mejia, Daniel Spencer, 2021, NeuroImage.

Longitudinal surface-based spatial Bayesian GLM reveals complex trajectories of motor neurodegeneration in ALS

Amanda F. Mejia, Sanjay Kalra, Robert C. Welsh, 2021, NeuroImage.

Evidence for Specificity of Motor Impairments in Catching and Balance in Children with Autism

Amanda F. Mejia, Brian Caffo, Stewart Mostofsky, 2014, Journal of Autism and Developmental Disorders.

Statistical estimation of white matter microstructure from conventional MRI

Amanda F. Mejia, Pascal Sati, Daniel S Reich, 2016, NeuroImage: Clinical.

A Survey of Statistics in the Neurological Sciences with a Focus on Human Neuroimaging

Amanda F. Mejia, B. Caffo, M. Lindquist, 2018, Wiley StatsRef: Statistics Reference Online.

A LAG FUNCTIONAL LINEAR MODEL FOR PREDICTION OF MAGNETIZATION TRANSFER RATIO IN MULTIPLE SCLEROSIS LESIONS.

Russell T. Shinohara, Ana-Maria Staicu, Daniel S. Reich, 2016, The annals of applied statistics.

Statistical Methods for Functional Magnetic Resonance Imaging Data

Amanda F. Mejia, 2016 .

Less is more: balancing noise reduction and data retention in fMRI with projection scrubbing

Amanda F. Mejia, M. B. Nebel, L. Ding, 2022 .

ciftiTools: A package for reading, writing, visualizing, and manipulating CIFTI files in R

Amanda F. Mejia, J. Muschelli, Damon Pham, 2021, NeuroImage.

Effects of Scan Length and Shrinkage on Reliability of Resting-State Functional Connectivity in the Human Connectome Project

Amanda F. Mejia, Ann S. Choe, M. B. Nebel, 2016, 1606.06284.

Improving power in functional magnetic resonance imaging by moving beyond cluster-level inference

Amanda F. Mejia, D. Scheinost, A. Zalesky, 2022, Proceedings of the National Academy of Sciences of the United States of America.

Sources of Residual Autocorrelation in Multiband Task fMRI and Strategies for Effective Mitigation

Amanda F. Mejia, Daniel Spencer, Damon Pham, 2022, 2209.06783.

Sources of residual autocorrelation in multiband task fMRI and strategies for effective mitigation

Amanda F. Mejia, Daniel Spencer, Damon Pham, 2022, Frontiers in Neuroscience.

Template Independent Component Analysis with Spatial Priors for Accurate Subject-Level Brain Network Estimation and Inference

Amanda F. Mejia, M. B. Nebel, B. Caffo, 2022, J. Comput. Graph. Stat..

Highlight Results, Don’t Hide Them: Enhance interpretation, reduce biases and improve reproducibility

Amanda F. Mejia, P. Bandettini, J. Gonzalez-Castillo, 2022, bioRxiv.

Fast Bayesian estimation of brain activation with cortical surface fMRI data using EM

Amanda F. Mejia, D. Bolin, Daniel A. Spencer, 2022, 2211.01429.

Shrinkage prediction of seed-voxel brain connectivity using resting state fMRI

Martin A. Lindquist, Ciprian M. Crainiceanu, Amanda F. Mejia, 2014, NeuroImage.

Projection scrubbing: a more effective, data-driven fMRI denoising method

Amanda F. Mejia, Mary Beth Nebel, M. B. Nebel, 2021 .

Big Data and Neuroimaging

Martin A. Lindquist, Amanda F. Mejia, Shaojie Chen, 2017, Statistics in biosciences.

A Bayesian General Linear Modeling Approach to Cortical Surface fMRI Data Analysis

Martin A. Lindquist, David Bolin, Amanda F. Mejia, 2017, Journal of the American Statistical Association.

Big Data and Neuroimaging

Amanda F. Mejia, Aaron J. Fisher, B. Caffo, 2017, Statistics in Biosciences.

PCA leverage: outlier detection for high‐dimensional functional magnetic resonance imaging data

Amanda F. Mejia, Mary Beth Nebel, Martin A Lindquist, 2015, Biostatistics.

Psilocybin induces spatially constrained alterations in thalamic functional organizaton and connectivity

Amanda F. Mejia, M. B. Nebel, S. Mostofsky, 2022, NeuroImage.

Zen and the Art of Multiple Comparisons

Amanda F. Mejia, Martin A Lindquist, Amanda Mejia, 2015, Psychosomatic medicine.

Leveling up: improving power in fMRI by moving beyond cluster-level inference

Amanda F. Mejia, D. Scheinost, A. Zalesky, 2021, bioRxiv.

Left‐Hemispheric Microstructural Abnormalities in Children With High‐Functioning Autism Spectrum Disorder

Amanda F. Mejia, Deana Crocetti, Stewart Mostofsky, 2015, Autism research : official journal of the International Society for Autism Research.

Highlight results, don't hide them: Enhance interpretation, reduce biases and improve reproducibility

Amanda F. Mejia, P. Bandettini, J. Gonzalez-Castillo, 2022, NeuroImage.

Discussion on “distributional independent component analysis for diverse neuroimaging modalities” by Ben Wu, Subhadip Pal, Jian Kang, and Ying Guo

Amanda F. Mejia, 2021, Biometrics.

Less is more: balancing noise reduction and data retention in fMRI with data-driven scrubbing

Amanda F. Mejia, M. B. Nebel, L. Ding, 2021, NeuroImage.

Fast Bayesian estimation of brain activation with cortical surface and subcortical fMRI data using EM

Amanda F. Mejia, M. B. Nebel, D. Bolin, 2022, 2203.00053.

Individual patterns of functional connectivity in neonates as revealed by surfaced-based Bayesian modeling

Amanda F. Mejia, S. Ferradal, Damon D. Pham, 2023, bioRxiv.