Neuroscientists acquire single-channel, multichannel, and spatiotemporal data in ever-increasing quantities and need high-quality software tools for preprocessing, exploration, and analysis. Such tools are critical to addressing pressing neuroscientific questions, such as the nature of the neural code and the role of correlated activity of many neurons in perception and behavior. While several groups have developed related tools for internal use, there is currently no software system suitable for multiple data types and formats, usable for large volumes of data, with high-quality numerics, and professionally documented and maintained. Such a software system would enhance neuroscience research by (a) providing access to advanced analytical tools to groups that lack the resources to create them internally, (b) reducing the duplication of effort across groups, (c) allowing for a fuller utilization of physiological data sets, and (d) improving the communication of results between groups. Over the past five years, precisely such a set of tools have been developed by the PI and colleagues. These are in use in over 24 laboratories worldwide for research, in the Neuroinformatics course at the Marine Biological Laboratories for pedagogy, and have led to over 25 publications. In response to many requests, demonstrated by the approximately 24 appended letters, the aim of this grant is the continued development, maintenance and distribution of Chronux, an open source software package for advanced analysis of neurobiological time series data.
Specific aims are: 1. Further development and maintenance of a numerical analysis library. Initial emphasis will be on electrophysiological data, both spikes and continuous signals (EEG/MEG/LFP), but later releases will provide routines specialized for image time series data. 2. Incorporation of an I/O library for multiple neurobiological data and metadata formats, consisting of a set of filters to a number of existing formats, along with a general specification for such filters. 3. Development of a graphical user interface, to facilitate use by the typical neuroscientist. 4. Documentation, distribution, maintenance and quality assurance for Chronux. We will work closely with approximately 24 laboratories and the Neuroinformatics course at the MBL via a feedback process to ensure the quality and usability of Chronux.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
5R01MH071744-02
Application #
7027077
Study Section
Special Emphasis Panel (ZRG1-BST-D (51))
Program Officer
Cavelier, German
Project Start
2005-03-04
Project End
2009-02-28
Budget Start
2006-03-01
Budget End
2007-02-28
Support Year
2
Fiscal Year
2006
Total Cost
$481,421
Indirect Cost
Name
Cold Spring Harbor Laboratory
Department
Type
DUNS #
065968786
City
Cold Spring Harbor
State
NY
Country
United States
Zip Code
11724
Kleinfeld, David; Mitra, Partha P (2014) Spectral methods for functional brain imaging. Cold Spring Harb Protoc 2014:248-62
Menzer, David L; Bokil, Hemant; Ryou, Jae Wook et al. (2010) Characterization of trial-to-trial fluctuations in local field potentials recorded in cerebral cortex of awake behaving macaque. J Neurosci Methods 186:250-61
Bokil, Hemant; Andrews, Peter; Kulkarni, Jayant E et al. (2010) Chronux: a platform for analyzing neural signals. J Neurosci Methods 192:146-51
Saar, Sigal; Mitra, Partha P (2008) A technique for characterizing the development of rhythms in bird song. PLoS One 3:e1461
Bokil, Hemant; Purpura, Keith; Schoffelen, Jan-Mathijs et al. (2007) Comparing spectra and coherences for groups of unequal size. J Neurosci Methods 159:337-45
DeCoteau, William E; Thorn, Catherine; Gibson, Daniel J et al. (2007) Oscillations of local field potentials in the rat dorsal striatum during spontaneous and instructed behaviors. J Neurophysiol 97:3800-5
DeCoteau, William E; Thorn, Catherine; Gibson, Daniel J et al. (2007) Learning-related coordination of striatal and hippocampal theta rhythms during acquisition of a procedural maze task. Proc Natl Acad Sci U S A 104:5644-9
Bokil, Hemant; Tchernichovsky, Ofer; Mitra, Partha P (2006) Dynamic phenotypes: time series analysis techniques for characterizing neuronal and behavioral dynamics. Neuroinformatics 4:119-28