[Comp-neuro] Software for simulation of extracellular field potentials

LFPy: SOFTWARE FOR SIMULATION OF EXTRACELLULAR FIELD POTENTIALS

We would like to draw your attention to LFPy, a Python package for simulation of extracellular potentials that runs on top of the NEURON simulator [1,2]. LFPy is now available for download at:

http://compneuro.umb.no/LFPy/

where also installation instructions, documentation and example scripts can be found.

BACKGROUND:
One important challenge for both experimentalists and modelers is to relate measurements at different spatial and temporal scales to the underlying neural activity. For extracellular potentials, one of the most commonly measured signal in neural recordings, the biophysical relation between activity at the cellular level and the recorded signal is in principle known and a framework for numerical simulations exists: the extracellular potential can be calculated as a weighted sum of transmembrane currents in the vicinity of the recording electrode [3]. Interpreting experimentally recorded signals is, however, often difficult as the potentials are dependent on the complicated morphologies of nearby neurons. The good news is that we can extend our knowledge about the link between measurement and activity by using numerical simulations of multi-compartment neuron models. In the Computational Neuroscience Group at the Norwegian University of Life Sciences this approach has in recent years been used to study e.g. extracellular signatures of action potentials [4] and synaptic input currents [5], and for studying features of multi-unit activity and LFP signals from populations of neurons [6,7]. During this work we have developed a set of Python tools to use with the NEURON simulator [2] that we are now making publically available under the name LFPy, with the hope that it might benefit other modeling efforts in the computational neuroscience community.

FEATURES:
- Simple-to-use object classes for defining cells, synapses and recording electrodes
- Functionality to define detailed models of single neurons, and for running simulations with simultaneous calculation of extracellular potentials
- Use of standard formats for neuronal morphologies, allowing for use of morphological reconstructions available in online databases (e.g., http://neuromorpho.org/)
- Flexible and extendable thanks to the NEURON and Python programming environments.

DEVELOPERS:
Henrik Lindén, Espen Hagen, Szymon Łęski, Eivind Norheim, Klas H. Pettersen, Gaute T. Einevoll

LFPy has been developed in the Computational Neuroscience Group (http://compneuro.umb.no/) at the Norwegian University of Life Sciences in collaboration with the Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology, Warsaw, Poland, with support from the International Neuroinformatics Coordinating Facility (INCF) and the Research Council of Norway (eScience, NevroNor).

REFERENCES:
[1] Hines & Carnevale, Neural Comput 9:1179 (1997)
[2] Hines et al., Front Neuroinformatics 3:1-12 (2009)
[3] Holt & Koch, J Comp Neurosci 6:169 (1999)
[4] Pettersen & Einevoll , Biophys J 94:784 (2008)
[5] Lindén et al , J Comp Neurosci 29:423 (2010)
[6] Pettersen et al, J Comp Neurosci 24(3), 291–313 (2008)
[7] Lindén et al, Neuron 72:859-872 (2011)

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Henrik Lindén, PhD
Department of Computational Biology,
Royal Institute of Technology (KTH)
Stockholm, Sweden
http://www.csc.kth.se/~helinden/