Brainhack Vanderbilt

January 20th - 21st, 2024

Vanderbilt University

2205 West End Avenue, Nashville, TN 37240

About

A Quick Dive into Brainhack

So, you've heard of hackathons, right? Now, imagine that vibe but tailored specifically for the brainy world of neuroscience. That's Brainhack for you!

Why the Buzz Around Brainhack?

Neuroscience has some big questions on its plate. To tackle them (we're talking about massive datasets and some serious analytical firepower) Brainhack steps in. It's like a global rendezvous for brain enthusiasts, data geeks, and everyone in between.

What's Cooking at Brainhack?

Brainhack isn't just another science conference. Picture a global playground where researchers from all corners and fields come together. They roll up their sleeves and dive headfirst into some cool neuroscience projects.

Brainhack has this groovy mix of Hackathon energy with Unconference spontaneity. Workshops? Check. Brainstorming data science tools for neuroscience? Double-check. A major chunk is all about open collaboration. Imagine teams from different disciplines geeking out and brainstorming solutions for neuroscience puzzles.

And because learning never stops, Brainhack has a side of tutorials. Dive into Python, get friendly with GitHub, float around in cloud computing, or dive deep into some fresh statistical methods. To wrap it up, Brainhack isn't just an eventβ€”it's a vibe. A place where data science flirts with neuroscience, all in the name of unlocking the secrets of the brain. Cool, right?

Brainhack Vanderbilt is dedicated to a harassment-free conference experience for everyone. We follow Global Brainhack anti-harassment policy can be found here: Code of Conduct

Hacking Schedule

Saturday, January 20th

8:00 - 9:00 AM Check-in & Breakfast.
9:00 - 9:15 AM Hybrid Welcoming Ceremony.
9:15 - 10:00 AM Opening Keynote: Pierre Bellec
To Build a Home: 12 Years of Brainhack.
10:00 AM - 11:00 PM Hybrid Project Pitches.
11:00 AM - 12:00 PM Hacking Commences.
12:00 - 1:00 PM Lunch Keynote: Remi Gau
Open Science Best Practices: Past Accomplishments, Future Challenges.
1:00 - 6:00 PM Open Hacking.
5:00 - 6:00 PM Social Night: Hors d'oeuvres, Mocktails and Trivia

Sunday, January 21st

8:00 - 9:00 AM Breakfast & Coffee.
9:00 AM - 12:00 PM Hacking Proceeds.
12:00 - 1:00 PM Lunch.
1:00 - 2:00 PM Hacking & Wrapping.
2:00 - 3:00 PM Hybrid Final Project Presentations & Kudos.

Training Schedule

Saturday, January 20th

Neuro Track

Programming Track

1:00 - 2:00 PM Practical Introduction to Structural and Diffusion MRI with Adam Anderson Foundation Models and Domain Adaptation with Charreau Bell
2:00 - 3:00 PM Practical Introduction to Functional MRI with Soyoung Choi and Shiyu Wang Git and Visual Studio Code Workflow for Open Source Development with Richard Song
3:00 - 4:00 PM Introduction to Portable Imaging with Noah Roy Fram (EEG), Anupam Kumar and Seth Crawford (fNIRS) Large Language Models as Research Accelerator with Myranda Shirk
4:00 - 5:00 PM Introduction to Animal Connectome and Brain-Wide Activity Data with Mikail Rubinov Reproducible Project Management with Anwar Said

Projects

Attendee Proposed Projects

Brief project descriptions provided below!


Visit projects page on GitHub for more information:
github.com/brainhack-vandy/projects

PhysioQA

Functional magnetic resonance imaging (fMRI) is a powerful and widely used technique in human brain research, measuring blood-oxygen-level-dependent (BOLD) changes in the brain, as a PROXY for neural activity. Due to blood-oxygen dependency, two major influences on fMRI data are respiration and cardiac related processes which affect blood-oxygen levels in the brain. So people collect the measures of respiration and heart rate concurrently with fMRI to study and also to remove these effects. Fantastic! But here is the catch, like any other data we need to quality-check! Let's face it, checking the quality of this data can be a real headache. It usually involves a time consuming tedious manual labor and is prone to human error - you need to know what is real data, what is an artifact. That's why we want to create a nifty deep-learning tool to automate quality assessment! This tool doesn't just check the quality of your data; it also points out any issues and gives you tips on how to fix them. It's like having a friendly expert on your team, making sure your research data is as good as it can be!

Resting State Networks Across Age

Since their discovery, resting state networks have elucidated our understanding of cognitive function such as emotion processing, working memory, and daydreaming. Additionally, a collective of scientists believe resting state networks may be a possible biomarker of mental disorders. However, before we can confirm resting state networks point to a characteristic of mental disorders it is important to model how they change across age. Many studies have identified that age does influence the connectivity of resting state networks however which brain regions within resting state networks change specifically needs to be further understood. The goal of this project is to compare methods of how resting state network information are retrieved and potentially model how they change across age.

fMRI-EEG Preprocessing

Preprocessing is a critical step in neuroimaging analysis, laying the foundation for accurate and meaningful scientific discoveries. We need help configuring a pipeline to quality check for multiple datasets. This project will allow attendees with or without experience handling fMRI/EEG data to get a chance to work with what we call the "raw data". Working on a QC pipeline includes devising visuals of what the data looks like at various stages to make sure that the preprocessing is working as you expected and the data collected is good quality for future analyses. Toolboxes used include AFNI, FSL, ANTs, chronux, etc.

BIDS derivatives

Physiopy is a community dedicated to developing solutions for handling physiological data acquired in neuroimaging setups. Currently, physiopy supports and maintains phys2bids, a library that standardizes raw physiological data in accordance with the Brain Imaging Data Structure (BIDS). The community is also developing and managing other libraries like peakdet (processing and analysing), phys2denoise (producing physiological regressors for neuroimaging denoising), and physioQC (quality control). All those libraries produce a bunch of different derivatives. However, the derivatives structure and requirements for physiological data (i.e. cardiac, respiratory, blood pressure, etc.) are not yet covered by the BIDS specification. With this project, we are hoping to start a discussion around an eventual BIDS proposal on physiological derivatives.

Neural Manifolds

What are the meaningful changes in the brain with experience, that allows for adaptive behavior? When we look at the coordinated activity across spiking networks of neuronal ensembles, we see a delicate balance of stability and flexibility, as needed for a system that can both learn and remember. In this project, we present a population of simultaneously-recorded neurons from the non-human primate during learning of a complex sequence memory task, and in sleep afterwards. These data are exceptionally rich for exploration, but also to address three fundamental questions: (1) can we decode behavioral states from the ensemble dynamics? (2) what is the core representational geometry of the ensembles (what factors are best preserved/differentiated in low-dimensional spaces, and how does the geometry constrain the computations and dynamics of the network? (3) does the ensemble activity drift with time and experience, and if so, how?

Location

Vanderbilt University

2205 West End Avenue, Nashville, TN 37240

Get in touch

  • Email

    • roza.g.bayrak [at] vanderbilt.edu
    • catie.chang [at] vanderbilt.edu
  • Organizers

      Roza Gunes Bayrak, Catie Chang, Shiyu Wang, Richard Song, Sarah Goodale, Alex Oh, Maya Anderson, Terra Lee, Michelle Bukowski, Teagan Stewart

Brainhack Vanderbilt is kindly supported by: