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MAM 1.1.0
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@shimoura shimoura released this 20 Sep 15:39
· 230 commits to master since this release
v1.1.0
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Learn about vigilant mode.

The release MAM 1.1.0 brings many improvements and new features, which enhance the model's reliability, usability, and overall user experience. It also serves as a base version specifying the dependencies required to run on EBRAINS for future releases up to and including MAM 2.0.0.

New Features:

  • Documentation Enhancements:

    • Streamlined README.md with a Try It On EBRAINS button and step-by-step user instructions.
    • Removed "Testing on EBRAINS" section for clarity.

  • Parameter Tuning Improvements:

    • Segregated parameters in down-scale multi-area mode into Parameters to Tune and Default Parameters.
    • Introduced exposure of four user-friendly parameters, while retaining others for internal tuning.

  • Visualization Augmentations:

    • Introduced Extract and Visualize Interareal Connectivity to display area-level relative connectivity via heatmaps.
    • Added Simulation Results Visualization section with separate code modules in “./figures/MAM2EBRAINS”.
    • Enriched visualization with three new plots detailing instantaneous firing rate, resting state, and time-averaged population rates.
    • Refined representation of resting state plots inspired by Schmidt M et al. (2018), allowing users flexible area selection, altered synchrony representation, and a focus on binned spike histograms.

Enhancements:

  • Notebook Refinements:
    • Overhauled Jupyter Notebook structure with an accessible table of contents for user navigation.
    • Enhanced parameter descriptions for both exposed and default sets.
    • Incorporated model overview and concise description of the down-scaled multi-area model.
    • Cross-referenced relevant publication figures for user benefit.

Code Optimizations:

  • Minimized irrelevant print statements in codebase for clearer user outputs.
  • Updated .gitignore to exclude checkpoint files.

Bug Fixes:

  • Resolved file path separator issue in ./multiarea_model/data_multiarea/SLN_logdensities.R.
  • Addressed datatype concerns in ./multiarea-model/analysis.py for array initialization.
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