Analysis of Parallel Spike Trains by Carl van Vreeswijk (auth.), Sonja Grün, Stefan Rotter (eds.) PDF

By Carl van Vreeswijk (auth.), Sonja Grün, Stefan Rotter (eds.)

ISBN-10: 1441956743

ISBN-13: 9781441956743

ISBN-10: 1441956751

ISBN-13: 9781441956750

Action potentials, or spikes, are the main salient expression of neuronal processing within the lively mind, and they're most probably a big key to knowing the neuronal mechanisms of habit. even though, it's the crew dynamics of huge networks of neurons that's more likely to underlie mind functionality, and this may in basic terms be liked if the motion potentials from a number of person nerve cells are saw at the same time. ideas that hire multi-electrodes for parallel spike educate recordings were to be had for lots of many years, and their use has won extensive acceptance between neuroscientists. To reliably interpret the result of such electrophysiological experiments, stable and understandable info research is important. the advance of knowledge research equipment, notwithstanding, has probably not stored speed with the advances in recording know-how. Neither common thoughts, nor statistical technique look sufficient for the recent experimental chances. Promising techniques are scattered throughout magazine guides, and the correct mathematical heritage literature is buried deep in journals of alternative fields. Compiling an invaluable reader for college kids or collaborators is either exhausting and problematical. this case led us to assemble state of the art methodologies for examining parallel spike trains right into a unmarried booklet, which then may well function a vantage aspect for present thoughts and a launching aspect for destiny improvement. To our wisdom, this can be the 1st textbook with an particular concentrate on the topic. It comprises 20 chapters, every one of them written by means of chosen specialists within the box.

About the Editors:
Sonja Grün, born 1960, acquired her MSc (University of Tübingen and Max-Planck Institute for organic Cybernetics) and PhD (University of Bochum, Weizmann Institute of technology in Rehovot) in physics (theoretical neuroscience), and her Habilitation (University of Freiburg) in neurobiology and biophysics. in the course of her postdoc on the Hebrew collage in Jerusalem, she played a number of single-neuron recordings in behaving monkeys. outfitted with this adventure she back again to computational neuroscience to additional enhance research instruments for multi-electrode recordings, first on the Max-Planck Institute for mind study in Frankfurt/Main after which as an assistant professor on the Freie Universität in Berlin linked to the neighborhood Bernstein heart for Computational Neuroscience. due to the fact that 2006 she has been unit chief for statistical neuroscience on the RIKEN mind technological know-how Institute in Wako-Shi, Japan. Her medical paintings makes a speciality of cooperative community dynamics appropriate for mind functionality and behaviour. Stefan Rotter, born 1961, holds a MSc in arithmetic, a PhD in Physics and a Habilitation in Biology. considering the fact that 2008, he has been Professor on the college of Biology and the Bernstein middle Freiburg, a multidisciplinary learn establishment for Computational Neuroscience and Neurotechnology at Albert-Ludwig college Freiburg. His study is targeted at the kinfolk among constitution, dynamics, and serve as in spiking networks of the mind. He combines neuronal community modeling and spike educate research, frequently utilizing stochastic element approaches as a conceptual link.

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3) n The factor of 2 in this definition is chosen so that for a Poisson process, we have CV2 = 1. Nothing prevents us from using CV2 in models where the rate is constant. This allows us to explore the relationship between CV2 and CV . 3), that CV2 ≤ 2, and therefore CV2 ≡ CV . For Gamma processes, where √ CV = 1/ γ , it can be shown that CV2 is given by CV2 = (2γ )/{γ [2γ −1 (γ )]2 }. For Log-Normal processes, where CV = exp(σ 2 ) − 1, CV2 satisfies the equation ∞ CV2 = 4π −1/2 0 exp(−x 2 ) tanh(σ x) dx.

7). The averaging of C( ) over the initial binning positions is useful for limiting the possible fluctuation due to the finiteness of data. 4 displays the raw and averaged cost functions computed for the set of spike data given in Fig. 3, demonstrating significant fluctuation for a raw cost function. By applying the optimization method to spike trains whose intensity does not modulate greatly in time, it might come to pass that the original cost function C( ) computed for n spike sequences does not have a minimum or has a minimum at a binsize comparable to the observation period T .

Neural Comput 15:965–991 Snyder D (1975) Random point processes. Wiley, New York Stein RB (1965) A theoretical analysis of neuronal variability. Biophys J 5:173–194 Chapter 3 Analysis and Interpretation of Interval and Count Variability in Neural Spike Trains Martin Paul Nawrot Abstract Understanding the nature and origin of neural variability at the level of single neurons and neural networks is fundamental to our understanding of how neural systems can reliably process information. This chapter provides a starting point to the empirical analysis and interpretation of the variability of single neuron spike trains.

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Analysis of Parallel Spike Trains by Carl van Vreeswijk (auth.), Sonja Grün, Stefan Rotter (eds.)


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