Premise


Although the instruction and exchange of ideas that naturally emerges from our lab environments may nurture us as methodologists, it can be a struggle to enter new computational and scientific territory within our often all too insular lab environments. Without this support network, it is especially challenging to learn and properly apply computational techniques to data. Let's face it: When it comes to the enthralling mess that is neuroscience data, formal coursework often fails to bridge the gap between theory and practice. In this group, we seek to remediate this problem by supplementing our lab environments with informal statistical and computational instruction and exchange of ideas with like-minded peers. The diverse knowledge and skill set that each member brings is critical to forming a balanced group; we encourage experimenters, statisticians, and theorists alike to join us in breaking down the barriers that separate and prevent us from tackling the most exciting problems in neuroscience.

Meeting Format


To meet the diverse needs of the group, meetings will take on varying:
MEETING FORMATS
  • Clinic: Presentation of a specific experimental / statistical / computational challenge encountered with data from a neuroscience-related field, followed by questions, discussion, and feedback from group members.
  • Data Blitz: Multiple short presentations (10-20 minutes) of data from a neuroscience-related field, each followed by questions, discussion, and feedback from group members (10-20 minutes).
  • Hacking Session: Group works together to code up the solution to a statistical / computational problem.
  • Lightening Talks: Very short presentation (~5 mintues) of an extremely practical nugget of  experimental / statistical / computational information, usually at the beginning of a meeting.
  • Method Discussion: Informal lecture (30-60 minutes) on an experimental / statistical / computational topic followed by questions and discussion.
  • Method Demo: Hands-on demonstration of how to employ a statistical / computational method.
  • Paper Discussion: The group works together to understand, discuss, and critique a paper employing statistical / computational method.
  • Other
DIFFICULTY
  • Beginner
  • Intermediate
  • Advanced
  • Mixed
  • N/A
We ask that all members strive to keep the meetings accessible to group members with limited backgrounds in experimentation, statistics, and/or computing, but still interesting enough for those with strong backgrounds in these subjects.  By joining this group you are implicitly agreeing to take on this formidable, but essential task!

Group Leadership


Founders: Katelyn Arnemann, Yvonne Fonken & Keven Laboy