Bibliography

Heterogenous brain activations across individuals localize to a common network
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Prédire l'évolution de la maladie de Parkinson à l'aide de données cliniques et d'IRM fonctionnelles: reproduction et robustesse d'une étude
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Hype, Sustainability, and the Price of the Bigger-is-Better Paradigm in AI
With the growing attention and investment in recent AI approaches such as large language models, the narrative that the larger the AI …
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ENCORE: a practical implementation to improve reproducibility and transparency of computational research
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Confidence intervals uncovered: Are we ready for real-world medical imaging AI?
Medical imaging is spearheading the AI transformation of healthcare. Performance reporting is key to determine which methods should be …
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Garden of forking paths in ERP research – Effects of varying pre-processing and analysis steps in an N400 experiment
Abstract This study tackles the Garden of Forking Paths, as a challenge for replicability and reproducibility of ERP studies. Here, we …
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Nonlinear latent representations of high-dimensional task-fMRI data: Unveiling cognitive and behavioral insights in heterogeneous spatial maps
Finding an interpretable and compact representation of complex neuroimaging data is extremely useful for understanding brain behavioral …
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Moving beyond processing- and analysis-related variation in resting-state functional brain imaging
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From Maps to Models: A Survey on the Reliability of Small Studies of Task-Based fMRI
Task-based functional magnetic resonance imaging is a powerful tool for studying brain function, but neuroimaging research produces …
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A standardized image processing and data quality platform for rodent fMRI
Abstract Functional magnetic resonance imaging in rodents holds great potential for advancing our understanding of brain networks. …
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A Set of FMRI Quality Control Tools in AFNI: Systematic, in-depth, and interactive QC with afni_proc.py and more
Abstract Quality control (QC) assessment is a vital part of FMRI processing and analysis, and a typically underdiscussed aspect of …
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Towards reusable derived data in neuroimaging
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Towards reproducible neuroimaging: Solutions for sharing and re-using brain imaging data
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The best of both worlds: using semantic web with JSON-LD. An example with NIDM-Results & Datalad
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Open-source tools and platforms to investigate analytical variability in neuroimaging
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DataLad extension module for neuroimaging studies — Datalad for Hirnis 0.0.8 documentation
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Computational basis and ReproIn/DataLad: A complete portable and reproducible fMRI study from scratch
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BIDS Extension Proposal (BEP028): Provenance
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XCP-D: A Robust Pipeline for the Post-Processing of fMRI data
Abstract Functional neuroimaging is an essential tool for neuroscience research. Pre-processing pipelines produce standardized, …
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Sharing brain imaging data in the Open Science era: how and why?
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Garden of forking paths in ERP research – Effects of varying pre-processing and analysis steps in an N400 experiment
Abstract This study tackles the Garden of Forking Paths, as a challenge for replicability and reproducibility of ERP studies. Here, we …
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Flexible adaptation of task-positive brain networks predicts efficiency of evidence accumulation
Abstract Efficiency of evidence accumulation (EEA), an individual’s ability to selectively gather goal-relevant information to make …
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Beyond Increasing Sample Sizes: Optimizing Effect Sizes in Neuroimaging Research on Individual Differences
Linking neurobiology to relatively stable individual differences in cognition, emotion, motivation, and behavior can require large …
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Addressing researcher degrees of freedom through minP adjustment
Abstract When different researchers study the same research question using the same dataset they may obtain different and potentially …
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Systematic evaluation of fMRI data-processing pipelines for consistent functional connectomics
Abstract Functional interactions between brain regions can be viewed as a network, enabling neuroscientists to investigate brain …
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Quality over quantity: powering neuroimaging samples in psychiatry
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Embracing variability in the search for biological mechanisms of psychiatric illness
Despite decades of research, we lack objective diagnostic or prognostic biomarkers of mental health problems. A key reason for this …
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demidenm/PyReliMRI: v2.1.0
Several changes and additions are made: A more comprehensive docstring is used to enhance information on PyReliMRI readthedocs The …
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Open Source in Lab Management
This document explores the advantages of integrating open source software and practices in managing a scientific lab, emphasizing …
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Neurodesk: an accessible, flexible and portable data analysis environment for reproducible neuroimaging
Angela I. Renton, Thuy T. Dao, Tom Johnstone, Oren Civier, Ryan P. Sullivan, David J. White, Paris Lyons, Benjamin M. Slade, David F. Abbott, Toluwani J. Amos, Saskia Bollmann, Andy Botting, Megan E. J. Campbell, Jeryn Chang, Thomas G. Close, Monika Dörig, Korbinian Eckstein, Gary F. Egan, Stefanie Evas, Guillaume Flandin, Kelly G. Garner, Marta I. Garrido, Satrajit S. Ghosh, Martin Grignard, Yaroslav O. Halchenko, Anthony J. Hannan, Anibal S. Heinsfeld, Laurentius Huber, Matthew E. Hughes, Jakub R. Kaczmarzyk, Lars Kasper, Levin Kuhlmann, Kexin Lou, Yorguin-Jose Mantilla-Ramos, Jason B. Mattingley, Michael L. Meier, Jo Morris, Akshaiy Narayanan, Franco Pestilli, Aina Puce, Fernanda L. Ribeiro, Nigel C. Rogasch, Chris Rorden, Mark M. Schira, Thomas B. Shaw, Paul F. Sowman, Gershon Spitz, Ashley W. Stewart, Xincheng Ye, Judy D. Zhu, Aswin Narayanan, Steffen Bollmann
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Consequences of the Scientific Reform Movement
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The past, present, and future of the brain imaging data structure (BIDS)
Abstract The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a …
Russell A. Poldrack, Christopher J. Markiewicz, Stefan Appelhoff, Yoni K. Ashar, Tibor Auer, Sylvain Baillet, Shashank Bansal, Leandro Beltrachini, Christian G. Benar, Giacomo Bertazzoli, Suyash Bhogawar, Ross W. Blair, Marta Bortoletto, Mathieu Boudreau, Teon L. Brooks, Vince D. Calhoun, Filippo Maria Castelli, Patricia Clement, Alexander L. Cohen, Julien Cohen-Adad, Sasha D’Ambrosio, Gilles De Hollander, María De La Iglesia-Vayá, Alejandro De La Vega, Arnaud Delorme, Orrin Devinsky, Dejan Draschkow, Eugene Paul Duff, Elizabeth DuPre, Eric Earl, Oscar Esteban, Franklin W. Feingold, Guillaume Flandin, Anthony Galassi, Giuseppe Gallitto, Melanie Ganz, Rémi Gau, James Gholam, Satrajit S. Ghosh, Alessio Giacomel, Ashley G. Gillman, Padraig Gleeson, Alexandre Gramfort, Samuel Guay, Giacomo Guidali, Yaroslav O. Halchenko, Daniel A. Handwerker, Nell Hardcastle, Peer Herholz, Dora Hermes, Christopher J. Honey, Robert B. Innis, Horea-Ioan Ioanas, Andrew Jahn, Agah Karakuzu, David B. Keator, Gregory Kiar, Balint Kincses, Angela R. Laird, Jonathan C. Lau, Alberto Lazari, Jon Haitz Legarreta, Adam Li, Xiangrui Li, Bradley C. Love, Hanzhang Lu, Eleonora Marcantoni, Camille Maumet, Giacomo Mazzamuto, Steven L. Meisler, Mark Mikkelsen, Henk Mutsaerts, Thomas E. Nichols, Aki Nikolaidis, Gustav Nilsonne, Guiomar Niso, Martin Norgaard, Thomas W. Okell, Robert Oostenveld, Eduard Ort, Patrick J. Park, Mateusz Pawlik, Cyril R. Pernet, Franco Pestilli, Jan Petr, Christophe Phillips, Jean-Baptiste Poline, Luca Pollonini, Pradeep Reddy Raamana, Petra Ritter, Gaia Rizzo, Kay A. Robbins, Alexander P. Rockhill, Christine Rogers, Ariel Rokem, Chris Rorden, Alexandre Routier, Jose Manuel Saborit-Torres, Taylor Salo, Michael Schirner, Robert E. Smith, Tamas Spisak, Julia Sprenger, Nicole C. Swann, Martin Szinte, Sylvain Takerkart, Bertrand Thirion, Adam G. Thomas, Sajjad Torabian, Gael Varoquaux, Bradley Voytek, Julius Welzel, Martin Wilson, Tal Yarkoni, Krzysztof J. Gorgolewski
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Impact of analytic decisions on test-retest reliability of individual and group estimates in functional magnetic resonance imaging: a multiverse analysis using the monetary incentive delay task
Abstract Empirical studies reporting low test-retest reliability of individual blood oxygen-level dependent (BOLD) signal estimates in …
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The Impact of Hardware Variability on Applications Packaged with Docker and Guix: a Case Study in Neuroimaging
The reproducibility of neuroimaging analyses across computational environments has gained significant attention over the last few …
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Exploring a formal approach to selecting studies for replication: A feasibility study in social neuroscience
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Data leakage inflates prediction performance in connectome-based machine learning models
Abstract Predictive modeling is a central technique in neuroimaging to identify brain-behavior relationships and test their …
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Data leakage inflates prediction performance in connectome-based machine learning models
Abstract Predictive modeling is a central technique in neuroimaging to identify brain-behavior relationships and test their …
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Vers une recherche reproductible
Livre d’introduction à la recherche reproductible rédigé lors d’un booksprint.
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The value of replications goes beyond replicability and is tied to the value of the research it replicates: Commentary on Isager et al. (2024)
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The past, present and future of neuroscience data sharing: a perspective on the state of practices and infrastructure for FAIR
Neuroscience has made significant strides over the past decade in moving from a largely closed science characterized by anemic data …
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Reproducibility in medical image computing: what is it and how is it assessed?
Medical image computing (MIC) is devoted to computational methods for analysis of medical imaging data and their assessment through …
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Illusory generalizability of clinical prediction models
It is widely hoped that statistical models can improve decision-making related to medical treatments. Because of the cost and scarcity …
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ENIGMA’s simple seven: Recommendations to enhance the reproducibility of resting-state fMRI in traumatic brain injury
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bids-standard/BEP028_BIDSprov
Organizing and coordinating BIDS extension proposal 28 : BIDS Provenance
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A reproducible and generalizable software workflow for analysis of large-scale neuroimaging data collections using BIDS Apps
Abstract Neuroimaging research faces a crisis of reproducibility. With massive sample sizes and greater data complexity, this problem …
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nipy/heudiconv: v1.0.0
💥 Breaking Change gh-actions: Bump actions/checkout from 3 to 4 #703 (@dependabot[bot]) 🚀 Enhancement Fix inconsistent behavior of …
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Reproducibility in Neuroimaging Analysis: Challenges and Solutions
Recent years have marked a renaissance in efforts to increase research reproducibility in psychology, neuroscience, and related fields. …
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Editorial: Reproducibility in neuroscience
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Why every lab needs a handbook
A lab handbook is a flexible document that outlines the ethos of a research lab or group. A good handbook will outline the different …
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Sampling inequalities affect generalization of neuroimaging-based diagnostic classifiers in psychiatry
Abstract Background The development of machine learning models for aiding in the diagnosis of mental disorder is recognized as a …
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Containers for computational reproducibility
This PrimeView highlights the range of applications benefiting from the use of containers for reproducibility of computational data …
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Reprohackathons: promoting reproducibility in bioinformatics through training
The reproducibility crisis has highlighted the importance of improving the way bioinformatics data analyses are implemented, executed, …
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A reproducible benchmark of resting-state fMRIdenoising strategies using fMRIPrep and Nilearn
Reducing contributions from non-neuronal sources is a crucial step in functional magnetic resonance imaging (fMRI) connectivity …
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Neurodesk: An accessible, flexible, and portable data analysis environment for reproducible neuroimaging
Abstract Neuroimaging data analysis often requires purpose-built software, which can be challenging to install and may produce …
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Multivariate BWAS can be replicable with moderate sample sizes
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The Software Heritage Open Science Ecosystem
Software Heritage is the largest public archive of software source code and associated development history, as captured by modern …
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Reproducibility in MRI
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Integrating the BIDS Neuroimaging Data Format and Workflow Optimization for Large-Scale Medical Image Analysis
A robust medical image computing infrastructure must host massive multimodal archives, perform extensive analysis pipelines, and …
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Open and reproducible neuroimaging: From study inception to publication
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Toward practical transparent verifiable and long-term reproducible research using Guix
Abstract Reproducibility crisis urge scientists to promote transparency which allows peers to draw same conclusions after performing …
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qMRI-BIDS: An extension to the brain imaging data structure for quantitative magnetic resonance imaging data
Abstract The Brain Imaging Data Structure (BIDS) established community consensus on the organization of data and metadata for several …
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Reproducing FSL's fMRI data analysis via Nipype: Relevance, challenges, and solutions
The “replication crisis” in neuroscientific research has led to calls for improving reproducibility. In traditional neuroscience …
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A guided multiverse study of neuroimaging analyses
Abstract For most neuroimaging questions the range of possible analytic choices makes it unclear how to evaluate conclusions from any …
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The replication crisis is not a crisis of false positives
Efforts to replicate portions of the scientific literature have lead to widely varying and often low rates of replicability. This has …
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Reproducible brain-wide association studies require thousands of individuals
Magnetic resonance imaging (MRI) has transformed our understanding of the human brain through well-replicated mapping of abilities to …
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FAIRly big: A framework for computationally reproducible processing of large-scale data
Abstract Large-scale datasets present unique opportunities to perform scientific investigations with unprecedented breadth. However, …
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Data sharing and privacy issues in neuroimaging research: Opportunities, obstacles, challenges, and monsters under the bed
Collaborative networks and data sharing initiatives are broadening the opportunities for the advancement of science. These initiatives …
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DataLad: distributed system for joint management of code, data, and their relationship
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A hitchhiker’s guide to working with large, open-source neuroimaging datasets
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Influence of sample size and analytic approach on stability and interpretation of brain‐behavior correlations in task‐related fMRI data
Limited statistical power due to small sample sizes is a problem in fMRI research. Most of the work to date has examined the impact of …
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FAIR Computational Workflows
Computational workflows describe the complex multi-step methods that are used for data collection, data preparation, analytics, …
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fMRI data of mixed gambles from the Neuroimaging Analysis Replication and Prediction Study
Abstract There is an ongoing debate about the replicability of neuroimaging research. It was suggested that one of the main reasons for …
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Scrutinizing the EU General Data Protection Regulation
How will new decentralized governance impact research? , On 25 May 2018, the European Union (EU) regulation 2016/679 on data …
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Best practices in data analysis and sharing in neuroimaging using MRI
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Making data sharing work: The FCP/INDI experience
Over a decade ago, the fMRI Data Center (fMRIDC) pioneered open-access data sharing in the task-based functional neuroimaging …
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