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  • Created a tutorial-style Jupyter notebook demonstrating communication between two HNN networks (Network A and Network B).
  • Implemented a streamlined workflow using tempfile to save and read Network A's spike data, enhancing efficiency and reducing manual handling.
  • Structured the notebook with step-by-step explanations, including conceptual overviews and code cells.
  • Optimized code by consolidating drive parameters into dictionaries and simplifying spike data processing with numpy arrays.
  • Added visualization of spike rasters for both networks and verification of the spike train drive setup.

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