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NYU-DiffusionMRI/monte-carlo-simulation-1D-membrane

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Monte Carlo simulations of diffusion through 1d permeable membranes (CUDA C++)

The code re-implements 1d Monte Carlo simulations originally developed in Fieremans, et al., NMR Biomed, 2010 and Novikov, et al., Nature Physics, 2011, demonstrating the power spectrum of bead distribution along axons (Figure 8) and diffusivity and kurtosis time-dependence (Figure 9) in Lee and Papaioannou, et al., NeuroImage 2020.

  • Demo 1, bead statistics: Concatenate the bead distributions along 33 axons coming from Hellwig, et al., Biological Cybernetics, 1994, and calculate its power spectrum (Figure 8a) and the number of beads within a sliding window (Figure 8c).
  • Demo 2, packing generation: Generation of randomly distributed membranes based on the bead distance along axons in Hellwig, et al., Biological Cybernetics, 1994.
  • Demo 3, simulations: Perform Monte Carlos simulations of diffusion through 1d permeable membranes. The code is implemented in CUDA C++, and you need an Nvidia GPU to run the code.
  • Demo 4, analysis: Calculate diffusivity and kurtosis time-dependence based on displacement cumulants and diffusion signals.

These are good exercises if you just start your own MC simulation codes. Some results can suprise you, even if you are well experienced!!

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Authors

Acknowledgement

We would like to thank Sune N Jespersen for the discussion of CUDA C++ implementation.

License

This project is licensed under the LICENSE.

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