Kernel Current Source Density

This is v1.2 version of kCSD inverse method proposed in

J. Potworowski, W. Jakuczun, S. Łęski, D. K. Wójcik "Kernel Current Source Density Method" Neural Computation 24 (2012), 541–575

For citation policy see the end of this file.

Code status

master branch

kcsd library basics (click to open in browser, jupyter notebook)

kcsd library advanced (click to open in browser, jupyter notebook)

Earlier Stable versions

Please see git tags for earlier versions

• v1.0 corresponds to the version with the test cases written inside tests folder
• v1.1 corresponds to the elephant python library version - no tests here

License

Modified BSD License

Installation

pip install .

or

python setup.py install

(for development / purposes)

pip install -e .

or

python setup.py develop

Requirements

• python 2.7 / 3.4 / 3.5
• numpy 1.10
• scipy 0.17

Additional Packages

• scikit-monaco 0.2 (for monte carlo type integration for 3D case)
• matplotlib 0.99 (for visualization and plotting)

Status

• KCSD1D
• KCSD2D
• KCSD3D
• MoIKCSD
• sKCSD

Usage

from kcsd import KCSD1D, KCSD2D, KCSD3D, MoIKCSD, sKCSD

from kcsd import utility_functions as utils

from kcsd import csd_profile as CSD

For data acquired from experiments, please use Elephant instead.

Contact

Prof. Daniel K. Wojcik

d.wojcik[at]nencki[dot]gov[dot]pl

Citation policy

If you use this software in published research please cite the following work

• KCSD1D - [1, 2]
• KCSD2D - [1, 3]
• KCSD3D - [1, 4]
• MoIkCSD - [1, 3, 5]
• sKCSD - [6]

1. Potworowski, J., Jakuczun, W., Łęski, S. & Wójcik, D. (2012) 'Kernel current source density method.' Neural Comput 24(2), 541-575.
2. Pettersen, K. H., Devor, A., Ulbert, I., Dale, A. M. & Einevoll, G. T. (2006) 'Current-source density estimation based on inversion of electrostatic forward solution: effects of finite extent of neuronal activity and conductivity discontinuities.' J Neurosci Methods 154(1-2), 116-133.
3. Łęski, S., Pettersen, K. H., Tunstall, B., Einevoll, G. T., Gigg, J. & Wójcik, D. K. (2011) 'Inverse Current Source Density method in two dimensions: Inferring neural activation from multielectrode recordings.' Neuroinformatics 9(4), 401-425.
4. Łęski, S., Wójcik, D. K., Tereszczuk, J., Świejkowski, D. A., Kublik, E. & Wróbel, A. (2007) 'Inverse current-source density method in 3D: reconstruction fidelity, boundary effects, and influence of distant sources.' Neuroinformatics 5(4), 207-222.
5. Ness, T. V., Chintaluri, C., Potworowski, J., Łeski, S., Głabska, H., Wójcik, D. K. & Einevoll, G. T. (2015) 'Modelling and Analysis of Electrical Potentials Recorded in Microelectrode Arrays (MEAs).' Neuroinformatics 13(4), 403-426.
6. Cserpan, D., Meszena, D., Wittner, L., Toth, K., Ulbert, I., Somogyvari, Z., Wójcik, D. K. (2017) 'Revealing The Distribution Of Transmembrane Currents Along The Dendritic Tree Of A Neuron From Extracellular Recordings.' eLife (2017) 6:e29384