Neural Engineering

Transformative Technologies

Work Package: WP6
Programme: P16

Deliverable: 16.3: “Development of a Matlab toolbox for spike train time series analysis Ver 1, Ver 2”

Deliverable due date: month 16, 28

This document reports on the progress of work on Deliverable 16.3. All the planned tasks related to this Deliverable have been accomplished. The main outcome of our work within the NETT framework in relation to this Deliverable is the software package “SPIKY”, which is now freely available online:
http://www.fi.isc.cnr.it/users/thomas.kreuz/Source-Code/SPIKY.html.
Version 1 of SPIKY was released in June 2014 while the current version 2.2 was released in March 2015. Furthermore, we have published a peer-reviewed article in the “Journal of Neurophysiology” presenting the SPIKY software package:
http://jn.physiology.org/content/113/9/3432.abstract
With the SPIKY software package and this publication we have successfully achieved Milestones 5 and 11, and completed Deliverable 16.3.
In the
NETT 289146 Grant Annex, we stated in the context of Deliverable 16.3: “P16 will serve as a tool to be applied in all nodes of the ITN to teach innovative uni- and multi-variate data analysis and to help in developing nonlinear time series analysis specific to projects at the local laboratories.”
Therefore, the SPIKY package has been introduced in several talks/posters within the NETT project, e.g. at the NETT Florence Workshop in 2014, the NETT Mid-Term Review Meeting in Nijmegen 2014, in a seminary talk at the Radboud University in Nijmegen in 2014 and at the NETT International Conference on System Level Approaches to Neural Engineering in Barcelona, 2015. Furthermore, we have used SPIKY for analyzing spike train data in collaborative projects with the NETT partners BitBrain Technologies in Spain, Radboud University in Netherlands and Cortexica Ltd in the UK.
In the above mentioned publication we give an overview of SPIKY's capabilities and use cases, discuss the provided methods and their efficient implementation in Matlab using backends implemented in C. Furthermore, we provide exemplary analysis of multi-variate data sets to stress the ability of our methods and the SPIKY software package for multi-variate recording.

Hence, we have fully accomplished Deliverable 16.3 in full compliance with the NETT 289146 Grant Annex.

Contributors:
Thomas Kreuz, Nebojsa Bozanic, Mario Mulansky