Spectral properties of neuronal pulse interval modulation

Varghese, J. J., Weegink, K. J., Bellette, P. A. and Bradley, A. P. (2015). Spectral properties of neuronal pulse interval modulation. In: 2015 IEEE International Conference on Acoustics, Speech, and Signal Processing: Proceedings. International Conference on Acoustics, Speech, and Signal Processing (ICASSP) Conference, Brisbane, QLD, Australia, (1007-1011). 19-24 April 2015. doi:10.1109/ICASSP.2015.7178121

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Author Varghese, J. J.
Weegink, K. J.
Bellette, P. A.
Bradley, A. P.
Title of paper Spectral properties of neuronal pulse interval modulation
Conference name International Conference on Acoustics, Speech, and Signal Processing (ICASSP) Conference
Conference location Brisbane, QLD, Australia
Conference dates 19-24 April 2015
Convener IEEE
Proceedings title 2015 IEEE International Conference on Acoustics, Speech, and Signal Processing: Proceedings   Check publisher's open access policy
Journal name ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings   Check publisher's open access policy
Place of Publication Piscataway, NJ, United States
Publisher IEEE (Institute for Electrical and Electronic Engineers)
Publication Year 2015
Sub-type Fully published paper
DOI 10.1109/ICASSP.2015.7178121
Open Access Status Not yet assessed
ISBN 9781467369978
ISSN 1520-6149
Volume 2015-August
Start page 1007
End page 1011
Total pages 5
Collection year 2016
Language eng
Formatted Abstract/Summary
We determine the power spectrum of an ideal neuron which encodes information using a pulse interval modulation scheme in continuous time. We develop this by considering the rigorous derivation of the Digital Pulse Interval Modulation (DPIM) coding scheme spectra of L. Vangelista et al. in the limit of the coding slot size approaching zero. We show in this limit the spectrum is identical to that of a filtered renewal process frequently used to model neuroscience time series data. Using this renewal theory equivalence we then use the 'Fundamental Isometry Theorem' developed by Win & Ridolfi to show that introducing firing time jitter (as a simple model for noise effects) removes non-Poisson structure and reduces the utility of spectral feature selection. Lastly we show with sufficient jittering that the Bartlett spectrum of any renewal process reduces to that of a Poisson process, with a spectral density consistent with Carson's theorem for shot noise.
Keyword DPIM
Renewal process
Fundamental Isometry Theorem
Neural time series analysis
Q-Index Code E1
Q-Index Status Confirmed Code
Institutional Status UQ
Additional Notes BISP-P4.9

 
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Created: Wed, 01 Jul 2015, 15:30:56 EST by Rose Clements on behalf of School of Mechanical and Mining Engineering