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Join the unconference session with friends from EMEA and America! Click to see the speakers.
Pradeep Reddy Raamana — niQC: MR sequence Protocol compliance Chris+Alejandro — BIDS Stats Sebastian Urchs — Neurobagel: subject level cohort search across datasets
Join the unconference session with friends from EMEA and APAC! Click to see the speakers.
Ghislain Vaillant — Are BIDS derivatives specifications exhaustive enough? Dylan Nielson — Fmriprep group report Yu-Fang Yang — do we improve Diversity, Equity and inclusiveness by changing conference to hybird format NIMARE (James Kent) — NIMARE meta-analysis documentation
Join the unconference session with friends from EMEA and APAC! Click to see the speakers.
The serious reasons behind those brain animation projects — Faruk Gulban
Live event for EMEA. Replay for APAC and America.
— Paul McCarthy, Taylor Hanayik
Live event for EMEA and APAC. Replay for Americas.
— Yasmin Mzayek, Alexis Thual
Live event for EMEA and America. Replay for APAC.
The DANDI Archive — Yaroslav O. Halchenko
Live event for EMEA and APAC. Replay for Americas.
— Tristan Glatard
Live event for EMEA. Replay for APAC and America.
— Chris Markiewicz
Live event for EMEA and APAC. Replay for Americas.
— Paul Taylor, Gang Chen
Live event for EMEA and America. Replay for APAC.
Github is a useful, flexible collaboration tool that can be used for a wide variety of projects, not just code. In this session, we will practice using Github and review Git concepts at the same time by fixing an incomplete Git guide on Github. You will take turns being contributors and maintainers. Bonus points if you go all out and use Git to interact with Github to write about Git.
Github is a useful, flexible collaboration tool that can be used for a wide variety of projects, not just code. In this session, we will practice using Github and review Git concepts at the same time by fixing an incomplete Git guide on Github. You will take turns being contributors and maintainers. Bonus points if you go all out and use Git to interact with Github to write about Git.
No matter which language your programming depends on, bugs inevitably exist even for experienced coders. Simply running the code to completion does not guarantee it has no bugs. This makes code testing very necessary and important. In this session, we will go through key steps of code testing, potential tools, and some tips for efficient debugging/programming. You will be assigned into small groups to practice on some scenarios by testing Python code.
Almost all researchers have data and analysis scripts that generate results in the form of figures. Yet, few other researchers can use these exact data and scripts to generate the same figures, or to reproduce all results of the study. In this session, we’ll take you on a journey of building reproducible workflows that help alleviate the anxiety associated with receiving that dreaded email 'I’d like to reproduce your results...' We’ll start with helping others run your code on their machines, and end up with a fully reproducible workflow running in the cloud, with several pit stops in between.
Almost all researchers have data and analysis scripts that generate results in the form of figures. Yet, few other researchers can use these exact data and scripts to generate the same figures, or to reproduce all results of the study. In this session, we’ll take you on a journey of building reproducible workflows that help alleviate the anxiety associated with receiving that dreaded email 'I’d like to reproduce your results...' We’ll start with helping others run your code on their machines, and end up with a fully reproducible workflow running in the cloud, with several pit stops in between.
This short interactive workshop will introduce the basics of visualizing neuroimaging data in R and introduce you to some of the packages available in R. First, we will cover the principles of reproducible and programmatic data visualizations. We will then work through an R notebook where you will learn how to load, view, and run basic manipulations on Nifti images within R. We will also cover visualizing ROI- and vertex-level data, as well as edge-level brain network visualizations.
In this session, we will delve into using the Python programming language to fit various machine learning models on a sample neuroimaging dataset. We'll be using tools from numpy, pandas, and sklearn packages to read the input data, modify it and extract informative knowledge using the machine learning models. Thereafter, we'll use the visualization tools at our disposal to make sense of the fitted models. These visualizations can come in handy for translating our findings into a clarified visualization that summarizes the conclusions in a figure. While an elementary knowledge of the python programming language or familiarity with programming languages in general is anticipated, you are not required to have any tools installed to attend this session. We'll conduct all of our analysis on the cloud and in a simple step-by-step tutorial that can assist individuals who are new to programming.
This short interactive session will show you how to use the scikit-learn Python package to perform basic machine learning analysis. It will also cover how to visualize your results with the matplotlib and seaborn Python packages.
The Community Building workshop will be led by Jivesh Ramduny (@JRamduny) and Marta Topor (@MartaTopor) to introduce the importance of establishing an Open Science community with regards to the issues that surrounds the reproducibility crisis in research. The workshop will allow participants at all career stages to brainstorm about ideas that are fundamental to facilitate different community activities in addition to fostering an Open Science culture in academia via short- and long-term credible and collaborative projects. The workshop will also provide a practical section to allow participants to start planning their own community activities in an effort to help them start an Open Science community at their institutions or within their networks.
The Community Building workshop will be led by Jivesh Ramduny (@JRamduny) and Marta Topor (@MartaTopor) to introduce the importance of establishing an Open Science community with regards to the issues that surrounds the reproducibility crisis in research. The workshop will allow participants at all career stages to brainstorm about ideas that are fundamental to facilitate different community activities in addition to fostering an Open Science culture in academia via short- and long-term credible and collaborative projects. The workshop will also provide a practical section to allow participants to start planning their own community activities in an effort to help them start an Open Science community at their institutions or within their networks.
