NeuroImaging + Brain-Hack 2017

Online Intensive for Brain Science: Cerebral Computation and Neuro Imaging

Sara Rose Kimmich

Overview

The aim of this program is to empower undergraduate and early graduate students the utilize the tools and technology of modern neuroscience in a real world setting: a BrainHack. This program will cover research design and ethics, with a foundation of technical knowledge for neuroimaging and computational neuroscience. We will utilize open source datasets to think critically about data quality and study design through hands on processing and analysis. There will be a strong focus on collaborative thinking and rapid prototyping, and participants are strongly encouraged to participate in one of the global BrainHacks of 2017 after the course.

Goals

1. Goal 1: Develop core competency in coding, computer environments and computational analysis geared toward scientific analysis.
2. Goal 2: Support a selection of students to join researchers for a Brainhack at National Institutes of Health, 9-10 November 2017; ± followed by the 4 day Society for Neuroscience Conference, 11-15 November 2017. (*Tentative)

Womanium Scholarships: Womanium will sponsor a selection of graduate and undergraduate student registrations to the Society for Neuroscience Annual Conference in Washington D.C. November 11-15 2017.
»» Apply to become a Womanium NIH NeuroScience Scholar

Course Content

Week 1: Open Neuroscience + Prototype Thinking

• Course Overview - Sara Kimmich, NIH
• Introduction to Brainhacks - Cameron Craddock, UC Davis
• Learning through Data Mining on Open Data Sets - Emily Finn, NIH
• Platforms for Developing and Sharing Open Software - Greg Kiar, McGill University
• Multimodal Human Connectome Project - Emma Robertson, Imperial College London*
• Reproducibility in Brain Science - Kirstie Whitaker, Cambridge
• Project: Research design for an available open source data base (bonus points: execute)


• » Takeaway: Students should be familiar with the course requirements and established in a project group. This week they should develop introductory knowledge to data mining of open data sets.

Week 2: Brain Imaging Data Analysis: a Focus on fMRI

• fMRI Physics - Karla Miller, Oxford*
• fMRI Quality Control - Sue Whitfield Gabrieli, Massachusetts Institute of Health
• Rapid Prototyping with Git and Github - Sara Kimmich, NIH-UCL
• Project: fMRI Data Processing: Running Uber_subejct


• » Takeaway: Students should understand how to maintain a basic collection, processing and analysis pipeline for data. Be able to download, edit, and upload code content on github.

Week 3: Research Design and Reproducibility

• fMRI Biostatistics - Jeanette Mumford, University of Wisconsin-Madison
• Representing Statistics - Regina Nuzzo, Gallaudet University
• Neurofeedback: How the brain changes itself - Michal Ramot, NIH
• Operationalizing your test case using Pytest - Jan Vereda, NIH


• » Takeaway: Students should be able to do a risk/benefits analysis of research analysis and develop statistical literacy. Run PyTest. Revisit first week’s research design and evaluate.

Week 4: Computational Neuroscience

• Computational Modeling - Megan Peters, UCLA
• Computational Neuroscience - Adrienne Fairhall, University of Washington*
• Neural Circuitry - Rachel Wilson, Harvard*
• Course Wrap Up - Sara Kimmich, NIH


• » Takeaway: Understand different approaches to computational modeling.

Timeline

Start	:	2017 August 28
End	:	2017 September 30

Course Platform

Course content is available via the open source learning platform OpenEdX, GitHub and via Womanium.

Participant Requirements

Students with backgrounds in neuroscience, biomedicine, computer science, physics, electrical engineering, mathematics are well suited to this course. All students will have access to supplementary learning material for the topics covered on the course.

All students must commit at least 3 hours a week: 2 hours of learning material and 1 hour online meeting with their project group. Online ‘office hours’ will provided every week to assist students with milestone projects and course material. A breakdown of participation options available here.

Guest Lecturer Requirements

Guest lecturers are asked to commit 1 hour between August 28 - September 30:

30 minutes of live lecture on a course topic, and 30 minutes of follow up ‘office hours’ for students to discuss the lecture material. Guest lecturers are asked to be available via email during the week of their course topic.

Talks should have some focus on how software and data storage are leveraged in their work.

Topic Specialist Requirements

Topic specialist are asked to commit 1 hour a week to online office hours for students to consult on lecture material and project development. Topic Specialists are expected to be familiar with each week’s content, but are asked to state a specific topic (ex: bash scripting, neuroanatomy) in which they can provide expertise in. Each Topic Specialists will provide a 2 minute video introducing their research interests, technical strengths and the best way to contact them throughout the course.

Teaching Assistant Requirements

Teaching Assistants are asked to commit 1 hour a week to online office hours for students to consult on lecture material and project development. Teaching assistants are expected to be familiar with each week’s content.

NeuroImaging + Brain-Hack 2017

Online Intensive for Brain Science: Cerebral Computation and Neuro Imaging

INSTRUCTORS

NeuroImaging + Brain-Hack 2017

Online Intensive for Brain Science: Cerebral Computation and Neuro Imaging

AMBASSADORS

Official Computational Partner + for Womanium Scholars

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