Abstract
Two spike train analysis techniques are introduced to establish how the probability of firing in a neuron is dependent on the number of sequential spikes fired in another neuron (temporal summation) and in any other neuron (spatial summation). The Joint InterNeuronal-Arrival-Time/Cross-Interval (J-INAT/CI) Probability Mass Function (PMF) is used to deduce how a sequential (burst) firing pattern in any neuron is contributing to the generation of a spike in a reference neuron. Analogously, the Joint Inter-Spike-ArrivalTime/Cross-Interval (J-LSAT/CI) PMF is defined similar to the former PMF except that the contribution from only one other neuron is considered. These analyses can be used to establish the precise coupling relationship between the firing times of neurons both spatially and temporally.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
I. Aertsen, A. M. H. J., Gerstein, G. L, Habib, M. K. and Palm, G. (1989) Dynamics of neuronal firing correlation: modulation of “effective connnectivity.” Journal of Neurophvsiology 61: 900–917.
Perkel, D. H., Gerstein, G. L. and Moore, G. P. (1967a) Neuronal spike trains and stochastic point process. I. The single spike train. Biophysical Journal. 7: 391–418.
Perkel, D. H., Gerstein, G. L. and Moore, G. P. (1967b) Neuronal spike trains and stochastic point process. II. Simultaneous spike trains. Biophysical Journal, 7: 419–440.
Perkel, D. H., Gerstein, G. L., Smith, M. S. and Tatton, W. G. (1975) Nerve-impulse patterns: A quantitative display technique for three neurons. Brain Research, 100: 271–296.
Rodieck, R. W., Kiang, N. Y.-S. and Gerstein, G. L. (1962) Some quantitative methods for the study of spontaneous activity of single neurons. Biophysical Journal, 2: 351–368.
Smith, C. E. (1992) A heuristic approach to stochastic models of single neurons. In: Single Neuron Contpulotion ( T. McKenna, J. Davis and S. Zornetzer, eds.) Academic Press, San Diego, CA. pp. 561–588.
Tam, D. C. (1993) A multi-neuronal vectorial phase-space analysis for detecting dynamical interactions in tiring patterns of biological neural networks. In: Computational Neural Systems. (F. H. Eeckman and J. M. Bower. eds.) Kluwer Academic Publishers, Norwell, MA. pp. 49–53.
Yang, X. and Shamma, S. (1990) Identification of connectivity in neural networks. Biophysical Journal, 57: 987–999.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1997 Springer Science+Business Media New York
About this chapter
Cite this chapter
Tam, D.C., Fitzurka, M.A. (1997). Inter-Arrival Time Spike Train Analyses for Detecting Spatial and Temporal Summation in Neurons. In: Bower, J.M. (eds) Computational Neuroscience. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-9800-5_31
Download citation
DOI: https://doi.org/10.1007/978-1-4757-9800-5_31
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4757-9802-9
Online ISBN: 978-1-4757-9800-5
eBook Packages: Springer Book Archive