Relating EEG eye-tracking data to attention network subsystems
Project info
Title: Relating eye-tracking EEG metrics to attention network systems
Project lead: Emily Olafson, mattermost: @emilyo email: olafsonemily@gmail.com
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:
https://github.com/emilyolafson/eyetrack-ANT
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:
- Extract reaction time and accuracy measures from ANT (Attention Network Task) outputs for each subject and for each session.
- Import .edf EEG data files to MATLAB and perform a quality check for each session (i.e. bad quality = eye gaze leaves the field)
Skills: Python or MATLAB skills at any level, statistics, familiarity with EEG
Tools/Software/Methods to Use: Python, MATLAB
Communication channels: https://mattermost.brainhack.org/brainhack/channels/eyetracking-project https://meet.jit.si/EyeTrackingProject
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