Visualization and analysis of a variety of modalities / formats of neurobiological time series data


Chronux is an open-source software package for the analysis of neural data. It was originally developed through a collaborative research effort based at the Mitra Lab in Cold Spring Harbor Laboratory. Chronux routines may be employed in the analysis of both point process and continuous data, ranging from preprocessing, exploratory and confirmatory analysis.

The current release of Chronux is implemented as a MATLAB library.

Neuroscientists are increasingly gathering large time series data sets in the form of multichannel electrophysiological recordings, EEG, MEG, fMRI and optical image time series. The availability of such data has brought with it new challenges for analysis, and has created a pressing need for the development of software tools for storing and analyzing neural signals. In fact, while sophisticated methods for analyzing multichannel time series have been developed over the past several decades in statistics and signal processing, the lack of a unified, user-friendly, platform that implements these methods is a critical bottleneck in mining large neuroscientific datasets.

Chronux is an open source software platform that aims to fill this lacuna by providing a comprehensive software platform for the analysis of neural signals. It is a collaborative research effort currently based at Cold Spring Harbor Laboratory that draws on a number of previous research projects. The current version of Chronux includes a Matlab toolbox for signal processing of neural time series data, several specialized mini-packages for spike sorting, local regression, audio segmentation and other tasks. It also includes a graphical user interface (GUI). The current version of the GUI contains a number of features specialised to the analysis of electroencephalography (EEG) data. The eventual aim is to provide domain specific user interfaces (UIs) for each experimental modality, along with corresponding data management tools. In particular, we expect Chronux to grow to support analysis of time series data from most of the standard data acquisition modalities in use in neuroscience. We also expect it to grow in the types of analyses it implements. Chronux is supported by grant R01MH071744 from the NIH to Partha P. Mitra.