SORTED

Research toolbox

A curated collection of resources and tools for managing and analyzing neuroimaging data and research, including data repositories, journals, protocols, and tools.

SORTED: A curated collection of interesting ideas, tools, and resources in neuroscience, data management, and data science, all in the spirit of Open Science. Additionally, it includes interesting miscellaneous links related to AI, biohacking, and productivity.

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awesome-listbraincollectionsdatadata-analysisdata-scienceelectrophysiologyfmriideasknowledge-sharinglinksharelistmrineuroscienceopen-scienceresearchresourcesscience-ideasstatisticstools

SORTED / Open Data Science / Data Repositories (suitable for neuroimaging datasets)
OpenNeuro : A platform for sharing BIDS-compliant MRI, PET, MEG, and EEG data
OpenNeuro PET : A specialized repository for BIDS-compliant PET data
NeuroVault : A repository for unthresholded statistical maps, parcellations, and atlases from MRI and PET studies
BossDB : A volumetric database for 3D and 4D neuroscience data
GigaDB : Hosts over 2201 discoverable, trackable, and citable datasets with DOIs for public download and use
Harvard Dataverse : A repository for research data across all disciplines
Dryad : An open data publishing platform for a wide range of research data
GIN : A modern research data management platform for neuroscience
Zenodo : A general-purpose open data repository
NeMO : A data repository focused on multi-omic data from brain research projects
DABI : A shared repository for invasive neurophysiology data from the NIH BRAIN Initiative

SORTED / Open Data Science / Journals (for Data Notes)
Data in Brief
Gigascience
Scientific Data
Frontiers in Big Data
Journal of Open Research Software

SORTED / Additional Resources:
Open Science Framework : A platform for sharing and collaborating on scientific research
Machine Learning Datasets : A comprehensive list of machine learning datasets from various sources
Awesome Neuroscience 1,315 28 days ago : A curated list of neuroscience libraries, software, and resources
Open Computational Neuroscience Resources 563 7 months ago : A collection of open computational neuroscience resources
Open Science Resources 111 over 2 years ago : A collection of open science tools, datasets, and meta-resources
OtherLists 5 over 2 years ago : A list of other lists that collect and curate resources

SORTED / Miscellaneous for Researchers / General tools
BIDS : Brain Imaging Data Structure; simple and intuitive way to organize and describe neuroimaging and behavioral data
Protocols.io : science methods, assays, clinical trials, operational procedures and checklists for keeping your protocols up do date as recommended by Good Laboratory Practice (GLP) and Good Manufacturing Practice (GMP)
Sample Consent Forms for neuroimaging research (EN/DE) | : an international initiative that aims to provide researchers in the brain imaging community with information about data sharing options and tools
DataLad : a free and open source distributed data management system
ADDI + : Alzheimer's Disease Data Initiative; "a free data sharing platform, data science tools, funding opportunities, and global collaborations, ADDI is advancing scientific breakthroughs and accelerating progress towards new treatments and cures for AD and related dementias"
The Human Protein Atlas : "The Human Protein Atlas is a Swedish-based program initiated in 2003 with the aim to map all the human proteins in cells, tissues, and organs using an integration of various omics technologies, including antibody-based imaging, mass spectrometry-based proteomics, transcriptomics, and systems biology."
Most Wiedzy/ Bridge of Knowledge : a Polish-based system with collection of publications, studies, projects and a lot of other types of resources from a number of different subject areas (open-access)
Journal Citation Reports : "the world's leading journals and publisher-neutral data"

SORTED / Miscellaneous for Researchers / Coding/ Software
Dask : parallel computing with Python
Docker : OS-level virtualization to deliver software in packages called containers
Statistics in R : guidelines for ANOVA in R

SORTED / Miscellaneous for Researchers / Neuroscience
fMRIPrep : a preprocessing pipeline for task-based and resting-state fMRI data
Neurosynth : a platform for large-scale, automated synthesis of functional magnetic resonance imaging (fMRI) data
BrainMap : a database of published functional and structural neuroimaging experiments with coordinate-based results (x,y,z) in Talairach or MNI space
NEMAR : an open access data, tools, and compute resource for assessing and processing human NeuroElectroMagnetic data shared by its authors thru OpenNeuro
ReproNim : ReproNim delivers a reproducible analysis framework
NiMARE : a Python package for neuroimaging meta-analyses (Neuroimaging Meta-Analysis Research Environment)
BrainIAK : advanced fMRI analyses in Python, optimized for speed under the hood with MPI, Cython, and C++
BrainAge 29 4 months ago Brain-age models (brain-predicted age value from a raw T1-weighted MRI scans): ,
SPAMRI : A MATLAB Toolbox for Surface-Based Processing and Analysis of Magnetic Resonance Imaging
ENIGMA toolbox : Python/MATLAB based. Cortical and subcortical visualization tools, Preprocessed micro- and macroscale data, Multiscale analytical workflows, 100+ ENIGMA-derived statistical maps

SORTED / Miscellaneous for Researchers / Fellowships & Grants
Marie Skłodowska-Curie Actions **: Fellowships for researchers
EMBO Fellowships **: Fellowships for postdoctoral researchers in the life sciences
HFSP Fellowships **: Fellowships for interdisciplinary research in the life sciences
Traveling Fellowships, The Company of Biologists **: Funding for travel to undertake collaborative research
NIH Grants **: Information on grants provided by the National Institutes of Health
European Research Council Grants **: Funding opportunities from the ERC
ReproNim/INCF Training Fellowship

SORTED / Miscellaneous for Researchers / Learning
Neuroscience Tutorials **: Tutorials on various neuroscience topics
NeuroStars **: A forum for discussing neuroscience research and tools
ReproNim Statistics Module : Statistical basis for neuroimaging analyses: the basics / Effect size and variation of effect sizes in brain imaging / P-values and their issues / Statistical power in neuroimaging and statistical reproducibility / The positive Predictive Value / Cultural and psychological issues
DataCamp
Seeing Theory : a simple introduction to statistics and probability through the use of interactive visualizations (Brown University)

SORTED / Miscellaneous for Researchers / Summer Schools
Neuromatch Academy **: An online summer school for computational neuroscience
Google Summer of Code : a global, online program focused on bringing new contributors into open source software development
Neurohackademy : a summer school in neuroiming & data science, held at the University of Washington eScience Institute

SORTED / Initiatives, research groups, associations, labs, companies
ENIGMA : The ENIGMA Consortium brings together researchers in imaging genomics to understand brain structure, function, and disease, based on brain imaging and genetic data
The EuroLaD-EEG consortium : towards a global EEG platform for dementia (*more information is not yet available)
BrainArt SIG : "The scope of the Brain–Art SIG is to promote the exchange between Art & Science by fostering the dialogue between artists and members of the OHBM community." |
DeepMind : "We’re a team of scientists, engineers, ethicists and more, committed to solving intelligence, to advance science and benefit humanity"
The Center for Brains, Minds and Machines
NeuroDataScience - ORIGAMI lab
Opium : Polish National Institute for Machine Learning

SORTED / Initiatives, research groups, associations, labs, companies / Predatory journals/publishers etc.
Think-Check-Submit : this international, cross-sector initiative aims to educate researchers, promote integrity, and build trust in credible research and publications
Beall's List: expanded 2022 : a list of predatory journals & trusted resources

SORTED / Data Visualisation
BrainPainter : a free software for visualisation of brain structures, biomarkers and associated pathological processes
HSLuv : HSLuv is a human-friendly alternative to HSL
Information is beautiful : The Information is Beautiful Awards celebrates excellence & beauty in data visualization, infographics, interactives &  information art

SORTED / AI tools
AI Tools and Applications **: A curated list of AI tools and their applications
Elicit : AI research assistant

SORTED / Productivity
reMarkable List 6,309 about 1 month ago **: A list of projects related to the reMarkable tablet

SORTED / Biohacking
Biohacking Brain Health **: Research on the effects of fasting and diet changes on brain health
Bulletproof Blog **: Articles on biohacking and wellness
SelfHacked **: Research-based information on health, biohacking, and self-improvement

SORTED / Reading corner / Design
The Design of Everyday Things (Donald Norman): how users use objects, and how to optimize and standardize things and make them more intuitive and user-friendly

SORTED / Reading corner / Programming
The Art of Readable Code (Dustin Boswell & Trevor Foucher): a basic principles and practical techniques that one can apply to write a better code

SORTED / Reading corner / Relaxing on a hammock under a tree...
What If? Serious Scientific Answers to Absurd Hypothetical Questions (Randall Munroe)

SORTED / Reading corner / Unreliable Science (*and how to try overcome this issue)
Paper (PLOS/ John Ioannidis) | / : an essay written by John Ioannidis (Stanford School of Medicine); author argues that a large number of papers in medical research contain results that in fact cannot be replicated and are a false positive results
Article (Nature/ Regina Nuzzo) | / : cognitive fallacies in research and debiasing techniques
Paper (Nature/ Katherine S. Button et al.) | : low statistical power and its influence on true/false effects
Paper (Nat Rev Neurosci/ Russell A. Poldrack et al.) | : problems that should be acknowledge during neuroimaging data analysis (low statistical power, flexibility in data analysis, software errors etc.)
Paper (Nature/ Rotem Botvinik-Nezer et al.) | : analytical flexibility can have substantial effects on scientific conclusions
Paper (and why you shouldn't) (Psychophysiology/ Steven J. Luck & Nicholas Gaspelin) | : the purpose of this paper is to demonstrate how common and seemingly innocuous methods for quantifying and analyzing ERP effects can lead to very high rates of significant-but-bogus effects
Paper (PNAS/ Johan S. G. Chu & James A. Evans) | : "Examining 1.8 billion citations among 90 million papers across 241 subjects, we find a deluge of papers does not lead to turnover of central ideas in a field, but rather to ossification of canon. Scholars in fields where many papers are published annually face difficulty getting published, read, and cited unless their work references already widely cited articles. New papers containing potentially important contributions cannot garner field-wide attention through gradual processes of diffusion."
Paper (Joseph P. Simmons & Leif D. Nelson) | : "First, we show that despite empirical psychologists’ nominal endorsement of a low rate of false-positive findings (≤ .05), flexibility in data collection, analysis, and reporting dramatically increases actual false-positive rates."
Paper (PNAS/ Valen E. Johnson) | : "The lack of reproducibility of scientific research undermines public confidence in science and leads to the misuse of resources when researchers attempt to replicate and extend fallacious research findings. (...) Modifications of common standards of evidence are proposed to reduce the rate of nonreproducibility of scientific research by a factor of 5 or greater."
Paper (Robert Rosenthal) | : "For any given research area, one cannot tell how many studies have been conducted but never reported. The extreme view of the "file drawer problem" is that journals are filled with the 5% of the studies that show Type I errors, while the file drawers are filled with the 95% of the studies that show nonsignificant results."
Paper (Richard A. Armstrong) | & (S. Kunte & A. P. Gore) : statistical issues with large sample sizes
Paper (Dario Gordillo et al.) |
Paper (Corey Horien et al.) | : "Here we offer practical tips for working with large datasets from the end-user’s perspective. We cover all aspects of the data lifecycle: from what to consider when downloading and storing the data to tips on how to become acquainted with a dataset one did not collect and what to share when communicating results"

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