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Publications

Denoising scanner effects from multimodal MRI data using linked independent component analysis.

Li H. et al, (2019), Neuroimage, 208

Estimation of brain age delta from brain imaging.

Smith SM. et al, (2019), Neuroimage, 200, 528 - 539

Handedness, language areas and neuropsychiatric diseases: insights from brain imaging and genetics

Wiberg A. et al, (2019), Brain

Discovering markers of healthy aging: a prospective study in a Danish male birth cohort.

Zarnani K. et al, (2019), Aging (Albany NY), 11, 5943 - 5974

Structural Variability in the Human Brain Reflects Fine-Grained Functional Architecture at the Population Level.

Smith S. et al, (2019), J Neurosci, 39, 6136 - 6149

Towards algorithmic analytics for large-scale datasets

Bzdok D. et al, (2019), Nature Machine Intelligence, 1, 296 - 306

Hippocampal volume across age: Nomograms derived from over 19,700 people in UK Biobank

Nobis L. et al, (2019), NeuroImage: Clinical, 23

The relationship between spatial configuration and functional connectivity of brain regions revisited.

Bijsterbosch JD. et al, (2019), Elife, 8

The spatial correspondence and genetic influence of interhemispheric connectivity with white matter microstructure

Mollink J. et al, (2019), Nature Neuroscience, 22, 809 - 819

Classification of temporal ICA components for separating global noise from fMRI data: Reply to Power.

Glasser MF. et al, (2019), Neuroimage, 197, 435 - 438

Using GPUs to accelerate computational diffusion MRI: From microstructure estimation to tractography and connectomes

Hernandez-Fernandez M. et al, (2019), NeuroImage, 188, 598 - 615

Optimising neonatal fMRI data analysis: Design and validation of an extended dHCP preprocessing pipeline to characterise noxious-evoked brain activity in infants

Baxter L. et al, (2019), NeuroImage, 186, 286 - 300

Spatial parcellations, spectral filtering, and connectivity measures in fMRI: Optimizing for discrimination

Sala-Llonch R. et al, (2019), Human Brain Mapping, 40, 407 - 419

Automated processing pipeline for neonatal diffusion MRI in the developing Human Connectome Project

Bastiani M. et al, (2019), NeuroImage, 185, 750 - 763

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

Spisák T. et al, (2019), NeuroImage, 185, 12 - 26

The Lifespan Human Connectome Project in Aging: An overview

Bookheimer SY. et al, (2019), NeuroImage, 185, 335 - 348

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

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

Using temporal ICA to selectively remove global noise while preserving global signal in functional MRI data

Glasser MF. et al, (2018), NeuroImage, 181, 692 - 717

Construction of a neonatal cortical surface atlas using Multimodal Surface Matching in the Developing Human Connectome Project

Bozek J. et al, (2018), NeuroImage, 179, 11 - 29

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