Announcing a Workshop on Open and Reproducible Neuroimaging Software at the Vision Sciences Society’s 2024 Meeting
- Website: https://nben.net/vss2024
- When: May 20th, 2pm–5pm
- Where: Vision Sciences Society (VSS), 2024 Meeting, Banyan/Citrus room
- Registration: Required (see this page)
Announcing the workshop How to Stop Worrying and Love Computational Neuroimaging of the Visual Cortex at this year’s VSS meeting in St. Pete Beach, FL. The workshop is a VSS satellite event that will introduce participants to a variety of open source software tools that make reproducible computational neuroimaging work easy. The workshop will discuss fMRIprep, BIDS, Neurodesk, population receptive field (PRF) modeling tools, and machine learning techniques including CNNs. Lectures will focus on live-coding examples of the relevant software tools when possible, and all participants will be given access to a shared compute environment that includes all discussed software and numerous tutorials.
A small registration fee is required to help offset costs for the compute environment, which will remain available to participants for one month following the VSS conference. The workshop will not be live-streamed but materials will be made public after the event.
The workshop will consist of three sessions with short breaks between:
- Mark Schira will discuss the use of reproducible software tools for lab management, classroom settings, and high performance compute clusters. Mark will demonstrate the Neurodesk platform, which drastically simplifies the management, installation, versioning, and use of numerous open source neuroimaging software tools across environments.
- Noah C. Benson will walk through the processing of visual MRI data using fMRIprep, BIDS, and Python tools for visualization, analysis, and annotation of cortical surface data. Noah will demonstrate these tools in live-coded examples in which a pipeline is established from start to finish for examining data from visual MRI experiments.
- Fernanda L. Ribeiro will discuss and demonstrate machine learning tools, including convolutional neural networks (CNNs), that model complex relationships in visual data.
More information, including advice on preparing for the workshop, can be found on the website. Please contact Noah Benson with any questions.