title: ViSAPy: a Python tool for biophysics-based generation of virtual spiking activity for evaluation of spike-sorting algorithms.
abstract: BACKGROUND
  New, silicon-based multielectrodes comprising hundreds or more electrode contacts offer the possibility to record spike trains from thousands of neurons simultaneously. This potential cannot be realized unless accurate, reliable automated methods for spike sorting are developed, in turn requiring benchmarking data sets with known ground-truth spike times.
  
  
  METHODS
  We here present a general simulation tool for computing benchmarking data for evaluation of spike-sorting algorithms entitled ViSAPy (Virtual Spiking Activity in Python). The tool is based on a well-established biophysical forward-modeling scheme and is implemented as a Python package built on top of the neuronal simulator NEURON and the Python tool LFPy.
  
  
  RESULTS
  ViSAPy allows for arbitrary combinations of multicompartmental neuron models and geometries of recording multielectrodes. Three example benchmarking data sets are generated, i.e., tetrode and polytrode data mimicking in vivo cortical recordings and microelectrode array (MEA) recordings of in vitro activity in salamander retinas. The synthesized example benchmarking data mimics salient features of typical experimental recordings, for example, spike waveforms depending on interspike interval.
  
  
  METHODS
  ViSAPy goes beyond existing methods as it includes biologically realistic model noise, synaptic activation by recurrent spiking networks, finite-sized electrode contacts, and allows for inhomogeneous electrical conductivities. ViSAPy is optimized to allow for generation of long time series of benchmarking data, spanning minutes of biological time, by parallel execution on multi-core computers.
  
  
  CONCLUSIONS
  ViSAPy is an open-ended tool as it can be generalized to produce benchmarking data or arbitrary recording-electrode geometries and with various levels of complexity.
authors: Department of Mathematical Sciences and Technology, Norwegian University of Life Sciences, P.O. Box 5003, NO-1432 Aas, Norway; Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6), Jülich Research Centre and JARA, 52425 Jülich, Germany. Electronic address: e.hagen@fz-juelich.de.
authors: Espen
authors: E
authors: Hagen
authors: Department of Mathematical Sciences and Technology, Norwegian University of Life Sciences, P.O. Box 5003, NO-1432 Aas, Norway.
authors: Torbjørn V
authors: TV
authors: Ness
authors: Department of Mathematical Sciences and Technology, Norwegian University of Life Sciences, P.O. Box 5003, NO-1432 Aas, Norway; Redwood Center for Theoretical Neuroscience, University of California, Berkeley, CA 94720-3198, USA; Nervana Systems, San Diego, CA 92121, USA.
authors: Amir
authors: A
authors: Khosrowshahi
authors: Hafting-Fyhn Neuroplasticity Group, Department of Biosciences, University of Oslo, P.O. Box 1066 Blindern, NO-0316 Oslo, Norway.
authors: Christina
authors: C
authors: Sørensen
authors: Hafting-Fyhn Neuroplasticity Group, Department of Biosciences, University of Oslo, P.O. Box 1066 Blindern, NO-0316 Oslo, Norway.
authors: Marianne
authors: M
authors: Fyhn
authors: Hafting-Fyhn Neuroplasticity Group, Department of Biosciences, University of Oslo, P.O. Box 1066 Blindern, NO-0316 Oslo, Norway.
authors: Torkel
authors: T
authors: Hafting
authors: Bio Engineering Laboratory, Department of Biosystems Science and Engineering, Swiss Federal Institute of Technology Zürich, CH-4058 Basel, Switzerland.
authors: Felix
authors: F
authors: Franke
authors: Department of Mathematical Sciences and Technology, Norwegian University of Life Sciences, P.O. Box 5003, NO-1432 Aas, Norway; Department of Physics, University of Oslo, P.O. Box 1066 Blindern, NO-0316 Oslo, Norway.
authors: Gaute T
authors: GT
authors: Einevoll
mesh_terms: D000200:Action Potentials / Q000502:physiology*; D000818:Animals; D001703:Biophysics; D058256:Brain Waves / Q000502:physiology; D003198:Computer Simulation; D051379:Mice; D008810:Mice, Inbred C57BL; D008839:Microelectrodes; D008959:Models, Neurological; D009474:Neurons / Q000166:cytology / Q000502:physiology*; D025341:Principal Component Analysis; D012160:Retina / Q000166:cytology / Q000502:physiology; D012815:Signal Processing, Computer-Assisted; D013569:Synapses / Q000502:physiology; D014793:Visual Cortex / Q000166:cytology*
keywords: Benchmark data; Extracellular potential; Methods validation; Multicompartment model; Open-source software; Spike sorting