1k citations · 1.3k across the 15 of their papers we have counts for
17 papers
Assessing metadata privacy in neuroimaging
Emilie Kibsgaard, Anita Sue Jwa, Christopher J Markiewicz +4
The ethical and legal imperative to share research data without causing harm requires careful attention to privacy risks. While mounting evidence demonstrates that data sharing ben…
The Past, Present, and Future of the Brain Imaging Data Structure (BIDS)
Russell A. Poldrack, Christopher J. Markiewicz, Stefan Appelhoff +111
The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is mean…
Differentiable programming for functional connectomics
Rastko Ciric, Armin W. Thomas, Oscar Esteban +1
Mapping the functional connectome has the potential to uncover key insights into brain organisation. However, existing workflows for functional connectomics are limited in their ad…
DeepDefacer: Automatic Removal of Facial Features via U-Net Image Segmentation
Anish Khazane, Julien Hoachuck, Krzysztof J. Gorgolewski +1
Recent advancements in the field of magnetic resonance imaging (MRI) have enabled large-scale collaboration among clinicians and researchers for neuroimaging tasks. However, resear…
Comparing interpretation methods in mental state decoding analyses with deep learning models
Armin W. Thomas, Christopher Ré, Russell A. Poldrack
Deep learning (DL) models find increasing application in mental state decoding, where researchers seek to understand the mapping between mental states (e.g., perceiving fear or joy…
NEMAR: An open access data, tools, and compute resource operating on NeuroElectroMagnetic data
Arnaud Delorme, Dung Truong, Choonhan Youn +5
To take advantage of recent and ongoing advances in large-scale computational methods, and to preserve the scientific data created by publicly funded research projects, data archiv…
Challenges for cognitive decoding using deep learning methods
Armin W. Thomas, Christopher Ré, Russell A. Poldrack
In cognitive decoding, researchers aim to characterize a brain region's representations by identifying the cognitive states (e.g., accepting/rejecting a gamble) that can be identif…
NeuroQuery: comprehensive meta-analysis of human brain mapping
Jérôme Dockès, Russell Poldrack, Romain Primet +5
Reaching a global view of brain organization requires assembling evidence on widely different mental processes and mechanisms. The variety of human neuroscience concepts and termin…
Computational and informatics advances for reproducible data analysis in neuroimaging
Russell A. Poldrack, Krzysztof J. Gorgolewski, Gael Varoquaux
The reproducibility of scientific research has become a point of critical concern. We argue that openness and transparency are critical for reproducibility, and we outline an ecosy…
Text to brain: predicting the spatial distribution of neuroimaging observations from text reports
Jérôme Dockès, Demian Wassermann, Russell Poldrack +3
Despite the digital nature of magnetic resonance imaging, the resulting observations are most frequently reported and stored in text documents. There is a trove of information unta…
Science In the Cloud (SIC): A use case in MRI Connectomics
Gregory Kiar, Krzysztof J. Gorgolewski, Dean Kleissas +8
Modern technologies are enabling scientists to collect extraordinary amounts of complex and sophisticated data across a huge range of scales like never before. With this onslaught…
Information Projection and Approximate Inference for Structured Sparse Variables
Rajiv Khanna, Joydeep Ghosh, Russell Poldrack +1
Approximate inference via information projection has been recently introduced as a general-purpose approach for efficient probabilistic inference given sparse variables. This manus…
A simple and provable algorithm for sparse diagonal CCA
Megasthenis Asteris, Anastasios Kyrillidis, Oluwasanmi Koyejo +1
Given two sets of variables, derived from a common set of samples, sparse Canonical Correlation Analysis (CCA) seeks linear combinations of a small number of variables in each set,…
What's in a pattern? Examining the Type of Signal Multivariate Analysis Uncovers At the Group Level
Roee Gilron, Jonathan Rosenblatt, Oluwasanmi Koyejo +2
Multivoxel pattern analysis (MVPA) has gained enormous popularity in the neuroimaging community over the past few years. At the group level, most MVPA studies adopt an "information…
Temporal meta-states are associated with differential patterns of dynamic connectivity, network topology and attention
James M. Shine, Oluwasanmi Koyejo, Russell A. Poldrack
Little is currently known about the coordination of neural activity over longitudinal time-scales and how these changes relate to behavior. To investigate this issue, we used resti…
The Dynamics of Functional Brain Networks: Integrated Network States during Cognitive Function
James M. Shine, Patrick G. Bissett, Peter T. Bell +5
Higher brain function relies upon the ability to flexibly integrate information across specialized communities of brain regions, however it is unclear how this mechanism manifests…
False discovery rate smoothing
Wesley Tansey, Oluwasanmi Koyejo, Russell A. Poldrack +1
We present false discovery rate smoothing, an empirical-Bayes method for exploiting spatial structure in large multiple-testing problems. FDR smoothing automatically finds spatiall…