Neural Comp. NEW Faster Access
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
QUICK SEARCH:   [advanced]


     

This Article
Right arrow Full Text
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Mikula, S.
Right arrow Articles by Niebur, E.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Mikula, S.
Right arrow Articles by Niebur, E.
(Neural Computation. 2003;15:539-547.)
© 2003 The MIT Press

Note

The Effects of Input Rate and Synchrony on a Coincidence Detector: Analytical Solution

Shawn Mikula

mikula{at}jhmi.edu, Zanvyl Krieger Mind/Brain Institute and Department of Neuroscience, Johns Hopkins University, Baltimore, MD 21218, U.S.A.

Ernst Niebur

niebur{at}jhu.edu, Zanvyl Krieger Mind/Brain Institute and Department of Neuroscience, Johns Hopkins University, Baltimore, MD 21218, U.S.A.

We derive analytically the solution for the output rate of the ideal coincidence detector. The solution is for an arbitrary number of input spike trains with identical binomial count distributions (which includes Poisson statistics as a special case) and identical arbitrary pairwise cross-correlations, from zero correlation (independent processes) to complete correlation(identical processes).




This article has been cited by other articles:


Home page
 Neural Comput.Home page
T. Tetzlaff, S. Rotter, E. Stark, M. Abeles, A. Aertsen, and M. Diesmann
Dependence of Neuronal Correlations on Filter Characteristics and Marginal Spike Train Statistics
Neural Comput., September 1, 2008; 20(9): 2133 - 2184.
[Abstract] [Full Text] [PDF]

Home page
 J. Neurophysiol.Home page
A. Roy, P. N. Steinmetz, S. S. Hsiao, K. O. Johnson, and E. Niebur
Synchrony: A Neural Correlate of Somatosensory Attention
J Neurophysiol, September 1, 2007; 98(3): 1645 - 1661.
[Abstract] [Full Text] [PDF]

Home page
 J. Neurophysiol.Home page
S. Panzeri, R. Senatore, M. A. Montemurro, and R. S. Petersen
Correcting for the Sampling Bias Problem in Spike Train Information Measures
J Neurophysiol, September 1, 2007; 98(3): 1064 - 1072.
[Abstract] [Full Text] [PDF]

Home page
 Neural Comput.Home page
E. Niebur
Generation of synthetic spike trains with defined pairwise correlations.
Neural Comput., July 1, 2007; 19(7): 1720 - 1738.
[Abstract] [Full Text] [PDF]

Home page
 Neural Comput.Home page
S. Mikula and E. Niebur
Rate and Synchrony in Feedforward Networks of Coincidence Detectors: Analytical Solution
Neural Comput., April 1, 2005; 17(4): 881 - 902.
[Abstract] [Full Text] [PDF]

Home page
 J. Neurophysiol.Home page
M. Tomita and J. J. Eggermont
Cross-Correlation and Joint Spectro-Temporal Receptive Field Properties in Auditory Cortex
J Neurophysiol, January 1, 2005; 93(1): 378 - 392.
[Abstract] [Full Text] [PDF]

Home page
 Neural Comput.Home page
S. Mikula and E. Niebur
Synaptic Depression Leads to Nonmonotonic Frequency Dependence in the Coincidence Detector
Neural Comput., October 1, 2003; 15(10): 2339 - 2358.
[Abstract] [Full Text] [PDF]


HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
J COGNITIVE NEUROSCIENCE NEURAL COMPUTATION MIT PRESS JOURNALS
Copyright © 2003 by The MIT Press.