Analysis of Parallel Spike Trains
Action potentials, or spikes, are the most salient expression of neuronal processing in the active brain, and they are likely an important key to understanding the neuronal mechanisms of behavior. However, it is the group dynamics of large networks of neurons that is likely to underlie brain functio...
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| Other Authors: | , |
| Format: | Electronic |
| Language: | English |
| Published: |
Boston, MA :
Springer US,
2010.
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| Series: | Springer Series in Computational Neuroscience ;
7 |
| Subjects: | |
| Online Access: | https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-1-4419-5675-0 |
Table of Contents:
- Part 1: Basic spike train statistics: Point process models Ch 1
- Stochastic models of spike trains-Carl van Vreeswijk. Ch 2
- Estimating the firing rate- Shigeru Shinomoto. Ch 3
- Processing of phase-locked spikes and periodic signals- Go Ashida, Hermann Wagner and Catherine E. Carr. Ch 4
- Analysis and interpretation of interval and count variability in neural spike trains- Martin Paul Nawrot. Part II: Pairwise comparison of spike trains. Ch 5
- Dependence of spike-count correlations on spike-train statistics and observation time-scale- Tom Tetzlaff and Markus Diesmann. Ch 6
- Pair-correlation in the time and frequency domain- Jos J. Eggermont. Ch 7
- Spike metrics- Jonathan D. Victor and Keith P. Purpura. Ch8
- Gravitational clustering- George Gerstein. Part III: Multiple-neuron spike patterns. Ch 9
- Spatio-temporal patterns- Moshe Abeles. Ch 10
- Unitary Events analysis- Sonja Gr<U+00fc>n, Markus Diesmann and Ad Aertsen. Ch 11
- Information geometry of multiple spike trains- Shun-ichi Amari. Ch 12
- Higher-order correlations and cumulants- Benjamin Staude, Sonja Gr<U+00fc>n and Stefan Rotter. Part IV: Population-based approaches. Ch13
- Information theory and systems neuroscience- Don H. Johnson, lan N. Goodman and Christopher J. Rozell. Ch 14
- Population coding- Stefano Panzeri, Fernando Montani, Giuseppe Notaro, Cesare Magri and Rasmus S. Petersen. Ch 15. Chastic models for multivariate neural point processes: Collective dynamics and neural decoding- Wilson Truccolo. Part V: Practical issues. Ch 15
- Simulation of stochastic point processes with defined properties-Stefano Cardanobile and Stefan Rotter. Ch 16. Generation and selection of surrogate methods for correlation analysis-Sebastien Louis, Christian Borgelt and Sonja Gr<U+00fc>n. Ch 17
- Bootstrap tests of hypotheses-Valerie Ventura. Ch18
- Generating random numbers
- Hans Ekkehard Plesser. Ch 19. Practically trivial parallel data processing in a neuroscience laboratory- Michael Denker, Bernd Wiebelt, Denny Fliegner, Markus Diesmann and Abigail Morrison.