Kidslang Project

Investigating Arabic language comprehension in an interactive context setting and a non-interactive no context setting Two tasks: The ‘Interactive Context Task’ is referred to as the ‘dialogue’ task in the scripts The ‘No Context Task’ is referred to as the ‘listening’ task in the scripts Each of these tasks has two conditions: an object condition and a phrase condition. So it’s a 2x2 design cond_list = [‘listening_phrase’, ‘listening_object’, ‘dialogue_phrase’, ‘dialogue_object’]

Available data from 21 participants:

  • MEG data (.con and .mrk)

  • MRI data (fsaverage)

  • Digitized headshape

Preprocessing is already done:

  • ICA for eyeblinks

  • Rejection of bad epochs

  • STC computed for all 21 participants (we only care about word 2, which defines the epoch) What is required: Time-lock analysis (not frequency) Statistical analysis:

  • Spatiotemporal clustering: finding regions of high activity across the entire brain over the duration of the epoch

  • ROI clustering:

Location for STC for word 2/Server/NEUROLING/PersonalFiles/SherineBouDargham/KidLang/Adults/stc/ara_stc_w2

[2]:

import matplotlib