Assistant Professor, Department of Statistics
Member, Programs in Neuroscience, Cognitive Science and Data Science
Indiana University Bloomington
Luddy Center for Artificial Intelligence, 3027F
Three new papers out in NeuroImage!
Damon Pham’s paper describing the R package ciftiTools, which facilitates analysis and statistical method development for surface/grayordinate neuroimaging data.
Daniel Spencer’s paper validating our surface-based spatial Bayesian GLM for task fMRI analysis using test-retest data from the Human Connectome Project.
My paper with Robert Welsh, Vincent Koppelmans and co-authors examining neurodegeneration in ALS. We combined a rare longitudinal study of ALS with native-surface-space-based analysis and advanced spatial Bayesian task fMRI modeling to discover a complex pattern of neurodegeneration that may precede clinical signs of disability. This suggests potential for an early functional imaging-based biomarker of ALS.
Along with three new preprints:
Damon Pham’s paper comparing data-driven data cleaning to motion-based data cleaning methods for fMRI data.
Dan Spencer’s paper proposing and validating a new EM-based computation strategy for spatial Bayesian task fMRI analysis.
Collaborative work with Hopkins team led by Fred Barrett examining the effects of psilocybin on the functional topology and connectivity of the thalamus. They applied our template ICA method to perform a nuanced analysis looking at the unique effects of psilocybin on individual subjects’ brain organization and how that relates to their subjective experience on psilocybin (which is predictive of therapeutic efficacy!).
November 2021: Welcome to the world, Frances Luz Mejia!
Oct 2021: New pre-print titled “Longitudinal surface-based spatial Bayesian GLM reveals complex trajectories of motor neurodegeneration in ALS” is now available, the result of a collaboration with Robert Welsh & Vincent Koppelmans at University of Utah. https://arxiv.org/abs/2110.01510
June 2021: New pre-print out led by Damon Pham on ciftiTools, an R package for working with CIFTI and GIFTI-format “grayordinates” neuroimaging data. Great work, Damon! https://arxiv.org/abs/2106.11338
June 2021: New pre-print out led by Dan Spencer on surface-based spatial Bayesian modeling of task fMRI and its ability to produce reliable and powerful task activations in individuals and groups. Great work, Dan! https://arxiv.org/abs/2106.06669
May 2021: Mandy and University of Utah site PI Robert Welsh and co-I’s Vincent Koppelmans and Kevin Duff are awarded NIH funding to develop fMRI-based brain biomarkers for Alzheimer’s and MCI!
September 2020: After a long team effort, our paper titled “Open Science, Communal Culture, and Women’s Participation in the Movement to Improve Science” has been published in PNAS!
July 2020: So thrilled to welcome Daniel Spencer, postdoctoral researcher working on Bayesian models for cortical surface fMRI analysis!
June 2020: New preprint describing our work building a spatial Bayesian template ICA model for fMRI analysis. This model provides efficient estimation and powerful inference for subject-level brain networks. “A spatial template independent component analysis model for subject-level brain network estimation and inference“
May 2020: Welcome to Damon Pham, research assistant extraordinaire working on software for outlier detection in fMRI data and visualization of cortical surface neuroimaging data in R!
October 2019: Our new paper on fast, reliable estimation of subject-level brain networks using a hierarchical Bayesian framework with empirical “big data” population priors is now in press in Journal of the American Statistical Association! “Template Independent Component Analysis: Targeted and Reliable Estimation of Subject-level Brain Networks using Big Data Population Priors“
September 2019: New paper in Nature Communications with Jorge Mejia and Franco Pestilli! “Open data on industry payments to healthcare providers reveals potential hidden costs to the public”
June 2019: New paper describing our method for estimating task activation on the cortical surface of the brain using spatial Bayesian modeling with INLA just published in Journal of the American Statistical Association! “A Bayesian General Linear Modeling Approach to Cortical Surface fMRI Data Analysis”
March 2019: Post-doc opportunity! Details here.
January 2019: Mandy is awarded an NIH grant 1R01EB027119-01 on Bayesian methods for cortical surface neuroimaging data with co-investigators Martin Lindquist and Mary Beth Nebel.
December 24, 2018: Welcome to the world, Ana Lucia Mejia!
December 2018: Mandy is awarded a ASA Biometrics Section JSM 2019 travel award for the paper “A Bayesian General Linear Modeling Approach to Cortical Surface fMRI Data Analysis,” joint work with Ryan Yue, David Bolin, Finn Lindgren and Martin Lindquist.
May 2018: New manuscript, “Improved estimation of subject-level functional connectivity using full and partial correlation with empirical Bayes shrinkage” published in NeuroImage.