3. Methods

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The methods presented here are a work in progress. For implementation inquiries or clarifications, please do not hesitate to contact me.

3.1. Download the HCP 7T-fMRI retinotopy dataset

• Fetch the HCP data using AWS and Python (Jupyter notebook)

3.2. Grouping V1, V2, and V3 data into foveal and para-foveal ROIs

• Define the ROIs using the average pRF parameters and the Wang-Kastner (Jupyter notebook)

3.3. Modelling the propagation of BOLD activity across V1, V2 and V3 using a multivariate Ornstein-Uhlenbeck network model

• Fit network model (Jupyter notebook)

• Statistical assessment of the model’s effective connectivity (EC) and its task-dependent changes (Jupyter notebook)

• Visualize the structure of EC interactions across ROIs using a 2D representation of the foveal confluence (Matlab script)

• Group the model’s parameters into larger ROIs for interpretation (Matlab script)