Introduction and Background Information on NeuroSpec.

NeuroSpec consists of a number of MATLAB functions for performing multivariate Fourier analysis of time series and/or point process (spike train or event) data, and plotting the results. NeuroSpec 2.0 implements a bivariate spectral analysis, it includes routines for two channel auto spectral and cross spectral (coherence, phase, cumulant density) analysis, and a number of extensions including comparison of spectra, a stationarity test for spectra, comparison of coherence, system identification (gain, phase and impulse response), and pooled analysis (pooled spectra, pooled coherence, pooled phase, pooled cumulant density). Pooled analysis incorporates extended difference of spectra and extended difference of coherence tests. NeuroSpec 2.11 includes extensions for non-parametric directionality analysis of time series and spike train data. This includes unconditional directionality analysis for two signals and conditional directionality analysis for three signals. The framework was designed primarily for use on neural data, but is suited to a wide range of stationary stochastic (random) signals.

Theoretical and practical aspects of the analysis are described in the following articles:
Rosenberg, J.R., Amjad, A.M., Breeze, P., Brillinger, D.R. & Halliday, D.M. "The fourier approach to the identification of functional coupling between neuronal spike trains", Progress in Biophysics and molecular Biology, 53, 1-31, 1989. DOI: 10.1016/0079-6107(89)90004-7

Halliday D.M., Rosenberg J.R., Amjad A.M., Breeze P., Conway B.A. & Farmer S.F. "A framework for the analysis of mixed time series/point process data - Theory and application to the study of physiological tremor, single motor unit discharges and electromyograms", Progress in Biophysics and molecular Biology, 64, 237-278, 1995. DOI: 10.1016/S0079-6107(96)00009-0

Halliday D.M. "Nonparametric directionality measures for time series and point process data", Journal of Integrative Neuroscience, 14(2), 253-277, 2015. DOI: 10.1142/S0219635215300127

Halliday D.M., Senik M.H., Stevenson C.W., Mason R. "Non-parametric directionality analysis – Extension for removal of a single common predictor and application to time series", Journal of Neuroscience Methods, 268, 87–97, 2016. DOI: 10.1016/j.jneumeth.2016.05.008

Halliday D.M., Brittain J-S., Stevenson C.W., Mason R. "Adaptive spectral tracking for coherence estimation: the z -tracker", Journal of Neural Engineering, 15(2), 26004, 2018. DOI: 10.1088/1741-2552/aaa3b4

Acknowledgements
NeuroSpec has been written by David Halliday. The following people have all contributed to the development of the framework: Jay Rosenberg, Bernie Conway, Abdul Majeed Amjad, Alex Rigas, David Murray-Smith, Joe Lau, Peter Breeze, Simon Farmer, Jens Nielsen, Yang Zhan, John-Stuart Brittain, Carl Stevenson, Rob Mason.

Development of NeuroSpec has been supported in part by grants from the UK Joint Research Council Cognitive Science/HCI Initiative, The Wellcome Trust (Grants 036928; 048128; 058615), the UK Engineering and Physical Sciences Research Council (GR/R12350/01), and the UK Biotechnology and Biological Sciences Research Council (10477).

NeuroSpec is hosted by the Department of Electronics, University of York: http://www.elec.york.ac.uk/


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David Halliday,
Department of Electronics,
University of York,
YORK YO10 5DD, UK.
Last updated 2 Oct 2018