Preserving Derivative Information while Transforming Neuronal Curves

Manuscript

Athey, T. L., Tward, D. J., Mueller, U., Younes, L., Vogelstein, J. T., & Miller, M. I. (2023). Preserving Derivative Information while Transforming Neuronal Curves. arXiv:2303.09649.

Neuron Mapping

  • First, make sure that you have installed the brainlit package [Documentation].

  • The notebook that best demonstrates the code in this project is: brainlit/experiments/map_neurons/tutorial.ipynb.

  • Figures in tha paper were made in the notebooks in brainlit/experiments/map_neurons/ and, when necessary, heavy computations were done using scripts in brainlit/experiments/map_neurons/other. Many of the notebooks rely on data generated by scripts and therefore will not run as-is.

  • Nonetheless, the notebooks can serve as a reference to the interested reader. The notebooks that made the specific figures in the current version of the manuscript are:

  • map_neurons.ipynb: Fig. 1a-b, 2.

  • motivating-example.ipynb: Fig. 1e-f.

  • morphometrics-compare.ipynb: Fig. 3, 4.

  • straight-downsample.ipynb: Fig. 5.

  • Other files are more for scratch work, and are unlikely to be useful to new users.

Poster

Athey, T. L., Vogelstein, J. T., & Miller, M. I. (2022). Nyquist Sampling Rate for Projection Neuron Reconstruction. Poster at Society for Neuroscience Meeting.

Relevant directory

brainlit/experiemnts/map_neurons

Nyquist Sampling Rate for Projection Neuron Reconstruction

  • First, make sure that you have installed the brainlit package [Documentation].

  • Results are in the notebook: brainlit/experiments/map_neurons/sampling.ipynb