Schedule and resources from the OHBM Open Science Room: Rome 2019
The official Twitter hashtag set of the Open Science Room for 2019 is #OHBM2019 #OSR. Use it to coordinate events, meetings and discussions!
Scroll down to see details of the Oral sessions and demos, Lightning talks and Scheduled meetings in the Open Science Room.
Click here to download a better resolution PDF of the schedule.
20 minutes + 5 minutes of questions (3 per session)
How are journals, granting agencies, and consortia working alongside the open science movement? This session will explore recently introduced policy changes from each of these groups, focusing on their motivations and the potential impact on the academic ecosystem.
- OpenNeuro: Demo and its role in open science
- Dissemination open data and tools: discoverability, licensing, citation, metrics and more
- ReproNim and the ReproPub
The statistical significance, reproducibility, and replicability of results does not necessarily make them biologically meaningful. Current efforts towards reproducible and statistically reliable results, therefore, need to expand to also assess the biological validity of findings. This session will focus on efforts to address the biological validity of neuroimaging results, with particular emphasis on how this can be done in an open and transparent fashion.
- Individual Brain Charting
- ARIbrain - Valid circular inference for fMRI
- PyBASC - bagging enhanced functional parcellations
In this session, the speakers will present recently developed open source methods on a variety of topics. They will walk you through a short hands-on demo with their toolbox on real data in real-time.
- Towards DIPY 1.0
- Statistical methods for studying population of connectomes
- The developing Human Connectome Project automated functional processing framework for neonates
Although the web has transformed our commerce, communication, and media consumption; its impacts are not yet fully realized in neuroimaging research. This session will explore the potential of web applications for solving neuroscientific problems.
5 minutes + 5 minutes of questions (6 per session)
Although the field is still grappling with big questions of reproducibility and replicability, practical questions such as “how do I best plot by results”, or “how do I get my data in a format to use this new toolbox” still present the largest source of concern for many neuroscientists. This session will feature six lightning talks that discuss open source hands-on solutions for everyday real-world problems.
- knitr for neuroimagers
- Voodoo-corrected effect sizes at local maxim
- BIDScoin: an easy toolkit to convert your data to BIDS
- Neuroquery: mapping text to brain regions.
- pyActigraphy, a toolbox for actigraphy data analysis
- Efficiently editing sub-millimeter segmentations in 7 Tesla MRI
Machine learning is on the rise everywhere, also in neuroscience. In this session, we will discuss how to perform novel statistical methods and machine learning methods on neuroscientific data with openly available software.
- Kernel methods for machine learning applications
- BrainIAK Demo: MVPA and Advanced fMRI Analysis
- Nilearn: Machine learning for Neuro-Imaging in Python
- Nistats: the General Linear Model, fast and easy
- fMRIDenoise: automated denoising strategies
- APACE - Accelerated Permutation Inference for ACE models
Note: this session replaces the 'multi-modal neuroscience' session, as there was a far greater demand for machine learning. This update was made after the program booklet had gone to press, so the booklet and the app have not been updated accordingly.
From cross-lab collaborations to collaboration in big consortia, working collaboratively can provide a lot of benefits to science and to scientists. Yet it may also introduce new challenges in terms of communication, data analysis, and authorship. This session will explore the benefits of collaboration and ways to overcome the challenges.
- Quantitative and histology MRI with the hMRI-toolbox
- MNE-Python
- JuBrain Anatomy Toolbox v3.0
- Clinica: software for clinical neuroimaging
- NeuroImaging Tools & Resources Collaboratory (NITRC)
- Predictive Analytics Competition 2019 Reward Session
The OSR will also be open to scheduled conversations and discussions about various topics of open science outside. You can submit requests via a GitHub issue in this repository. The calendar is available here
- Mon 10:30: BIDS for EEG and MEG
- Mon 11:30: niQC SIG Meeting
- Mon 15:00: BIDS community discussion
- Tue 12:45: Meet the Open Science SIG (https://ossig.netlify.com)
- Tue 17:00: Theory in Network Neuroscience
- Wed 12:00: Why haven't I shared my data (yet)?
- Wed 16:15: Multi-Echo fMRI not-SIG Meeting
We want to have a discussion about the greatest challenges to practicing Open Science. What are your biggest roadblocks and hurdles? We would like to hear from you in an interactive discussion. We would especially like to hear from early career researchers and newcomers to open science to inform our plans for further training opportunities and activities.
To wrap up, we're gonna find the nearest gelateria and the first 50 Gelati are on us! Ice Cream for Open Science!
All material in this repository is CC-BY licensed unless explicitly stated otherwise.
