FIND - Finding Information in Neuronal Data: An open source framework for the analysis of neuronal activity data

Abstract

Event Abstract Back to Event FIND - Finding Information in Neuronal Data: An open source framework for the analysis of neuronal activity data Christian Garbers1*, Antje Kilias1, Ad Aertsen1, Ulrich Egert1 and Ralph Meier1 1 BCCN Freiburg, Germany The complexity of neurophysiology data has increased tremendously over the last years, especially due to the widespread application of multi-channel recording techniques. With increasing computing power, the current limitation for sophisticated data analysis is the effort and time it takes scientists to translate their ideas into working code. Advanced analysis methods are complex and often lack reproducibility on the basis of published descriptions. To overcome these limitations we developed FIND (http://find.bccn.uni-freiburg.de) as a platform-independent, open source framework for the analysis of neuronal activity data based on MATLAB (Mathworks). FIND provides unified data import from various proprietary formats, simplifying standardized interfacing with tools for analysis, simulation and visualization (Meier, R. et al. 2008a). The toolbox FIND covers a steadily increasing number of well documented tools. Analysis tools address various types of neural activity data, including time series of spike events, analog data (intra-cellular recordings and population activity data) and imaging data. Additionally, the toolbox provides solutions for the simulation of multi-variate stochastic point processes to model multi-channel spiking activity. Recently, support for the HDF5 Data Format, Clean Data (Musial et al. 2002), and the ability to calculate nonlinear interdependences in a massively parallel fashion (Meier et al. 2008b) using the Message Passing Interface (MPI) were added to the toolbox. We will outline design and functionality of the toolbox and show a usage example from a study in which FIND was used on multi electrode array data to analyse the network activity dynamics causing the transition from normal brain activity into hypersynchronous epileptiform spiking in mesial temporal lobe epilepsy (Meier et al. 2008b). Project funded by BMBF grant 01GQ0420 to BCCN Freiburg and EU grant 15879-FACETS.