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Publications

Exploring the impact of analysis software on task fMRI results.

Bowring A. et al, (2019), Hum Brain Mapp

Homogenizing estimates of heritability among SOLAR-eclipse, OpenMX, APACE, and FPHI software packages in neuroimaging data

Kochunov P. et al, (2019), Frontiers in Neuroinformatics, 13

A group analysis using the Multiregression Dynamic Models for fMRI networked time series

Costa L. et al, (2019), Journal of Statistical Planning and Inference, 198, 43 - 61

Accelerated estimation and permutation inference for ACE modeling

Chen X. et al, (2019), Human Brain Mapping

Bayesian log-Gaussian Cox process regression: applications to meta-analysis of neuroimaging working memory studies

Samartsidis P. et al, (2019), Journal of the Royal Statistical Society. Series C: Applied Statistics, 68, 217 - 234

Beyond Bonferroni revisited: concerns over inflated false positive research findings in the fields of conservation genetics, biology, and medicine

White T. et al, (2019), Conservation Genetics

Extending the Human Connectome Project across ages: Imaging protocols for the Lifespan Development and Aging projects.

Harms MP. et al, (2018), NeuroImage, 183, 972 - 984

Stable between-subject statistical inference from unstable within-subject functional connectivity estimates.

Vidaurre D. et al, (2018), Human brain mapping

Modelling the distribution of white matter hyperintensities due to ageing on MRI images using Bayesian inference.

Sundaresan V. et al, (2018), NeuroImage, 185, 434 - 445

Cluster failure revisited: Impact of first level design and physiological noise on cluster false positive rates

Eklund A. et al, (2018), Human Brain Mapping

Probabilistic TFCE: A generalized combination of cluster size and voxel intensity to increase statistical power.

Spisák T. et al, (2018), NeuroImage, 185, 12 - 26

Unravelling the GSK3β-related genotypic interaction network influencing hippocampal volume in recurrent major depressive disorder.

Inkster B. et al, (2018), Psychiatric genetics, 28, 77 - 84

MRI-based prediction of conversion from clinically isolated syndrome to clinically definite multiple sclerosis using SVM and lesion geometry

Bendfeldt K. et al, (2018), Brain Imaging and Behavior

The Lifespan Human Connectome Project in Development: A large-scale study of brain connectivity development in 5-21 year olds.

Somerville LH. et al, (2018), NeuroImage, 183, 456 - 468

Fast and powerful genome wide association of dense genetic data with high dimensional imaging phenotypes.

Ganjgahi H. et al, (2018), Nature communications, 9

Comparison of heritability estimates on resting state fMRI connectivity phenotypes using the ENIGMA analysis pipeline

Adhikari BM. et al, (2018), Human Brain Mapping

Directed functional connectivity using dynamic graphical models.

Schwab S. et al, (2018), NeuroImage, 175, 340 - 353

Insight and inference for DVARS.

Afyouni S. and Nichols TE., (2018), NeuroImage, 172, 291 - 312

Generalizable representations of pain, cognitive control, and negative emotion in medial frontal cortex.

Kragel PA. et al, (2018), Nature neuroscience, 21, 283 - 289

Joint Analysis of Cortical Area and Thickness as a Replacement for the Analysis of the Volume of the Cerebral Cortex.

Winkler AM. et al, (2018), Cerebral cortex (New York, N.Y. : 1991), 28, 738 - 749

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