Title: Relating eye-tracking EEG metrics to attention network systems
Project lead: Emily Olafson, mattermost: @emilyo email: firstname.lastname@example.org
Project collaborators: Sudhin Shah
Registered Brainhack Global 2020 Event: Brainhack NY, USA
Project Description: This project involves analysis eye-tracking EEG data that was recorded during the Attention Network Task, a paradigm used to assess different components of attention. Each of the primary attention systems—alerting, orienting, and executive control monitoring—involves salient autonomic correlates as evidenced by changes in reactive pupil dilation and blinks. The goal of the project will be to understand how physiological correlates of attention vary in healthy individuals and in patients with traumatic brain injury (TBI).
Data to use: The data consists of EEG outputs in the form of .edf files which include pupil dilation and eye-blinks, as well as accompanying behavioural data (Attention Network Task) including measures like reaction time. The data was collected by Dr. Sudhin Shah at Weill Cornell Medicine.
Link to project repository/sources:
Goals for Brainhack Global 2020:
Assess all ANT trial eye-tracking data to identity outliers/poor quality trials, look for differences in eye-tracking metrics across age and diagnosis, relate eye-tracking metrics to behaviour (i.e. reaction time).
Good first issues:
Skills: Python or MATLAB skills at any level, statistics, familiarity with EEG
Tools/Software/Methods to Use: Python, MATLAB
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Twitter-sized summary of your project pitch: “In this project, pupil dilation and eye-blinks recorded during an attention task will be related to behaviour in a sample of healthy individuals and patients with traumatic brain injury.”
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