HAL Id: hal-01368757
https://hal.inria.fr/hal-01368757
Submitted on 19 Sep 2016
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ENAS: A new software for spike train analysis and simulation
Bruno Cessac, Pierre Kornprobst, S. Kraria, H. Nasser, Daniela Pamplona, Geoffrey Portelli, Thierry Viéville
To cite this version:
Bruno Cessac, Pierre Kornprobst, S. Kraria, H. Nasser, Daniela Pamplona, et al.. ENAS: A new software for spike train analysis and simulation. Bernstein conference, Sep 2016, Berlin, Germany. �hal-01368757�
ENAS provides statistical analysis with Maximum Entropy-Gibbs distributions taking into account both spatial and temporal correlations as constraints, allowing to introduce causality and memory in statistics.
Virtual Retina simulator
Other features: Crop and bin rasters, select neurons subsets according to different criteria, set MEA array configuration, generate rasters from given statistics
As one gains more intuitions and results on the importance of concerted activity in spike trains, models are developed to extract potential canonical principles underlying spike coding. These methods shed a new light on spike train dynamics. However, they require time and expertise to be implemented efficiently, making them hard to use on a daily basis by neuroscientists or modelers. To bridge this gap, we developed the license free multiplatform software ENAS integrating tools for spike trains analysis and simulation.
ENAS includes a virtual retina simulator that includes feedback connections from the bipolar to the OPL layer and lateral connections in the IPL. This simulator maps images into spikes in a bio plausible way.
User-friendly
GUI
Parallel computing
Fast
Linux, MacOS,
Windows
Multi-platform
https://enas.inria.fr
Free
B. Cessac1 - P. Kornprobst1 - S. Kraria1 - H. Nasser1 - D. Pamplona1 - G. Portelli1 - T. Viéville2
1: Université Côte d'Azur, Inria, Biovision team, France 2: Inria, Mnemosyne team, France
Standard analysis
Spatio-temporal analysis
Receptive field estimation
ENAS
A new software for spike train
analysis and simulation
Contact: [email protected] This w ork wa s suppor ted by th e F rench ministr y of R esear ch and Un iversity of Nice ( EDSTIC), INRIA ADT, ER C-NER VI number 2277 47, KE OPS ANR -CONIC YT, th e Eu ropean Un ion P roject R envision #600 847 an d by the ECOS-Su d pr ogram ( grant C13E 06).