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  • 1
    Electronic Resource
    Electronic Resource
    Springer
    Biological cybernetics 35 (1979), S. 213-220 
    ISSN: 1432-0770
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology , Computer Science , Physics
    Notes: Abstract An elementary model of neuronal activity involves temporal and spatial summation of postsynaptic currents that are elicited by presynaptic spikes and that, in turn, elicit postsynaptic potentials at a trigger zone; when the potential at the trigger zone exceeds a “threshold” level, a postsynaptic spike is generated. This paper describes three methods of estimating the “summation function”, that is, the function of time that converts the synaptic current into potential at the trigger zone: namely, maximum likelihood, cross-correlation analysis and cross-spectral analysis. All three methods, when applied to input-output data collected on various neurons of Aplysia californica, give comparable results. As estimated, the summation function involved in the explored cells has an early positive-going swing that is large and brief. In the cell L5, but not in R2, there was also a late negative-going swing of longer duration.
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  • 2
    Electronic Resource
    Electronic Resource
    Springer
    Biological cybernetics 22 (1976), S. 213-228 
    ISSN: 1432-0770
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology , Computer Science , Physics
    Notes: Abstract This paper studies the influence exerted by the presynaptic spike train on the postsynaptic one. It applies to synaptic exploration a novel method for characterization of point-process systems (Brillinger, 1974, 1975a), and draws from it physiologically meaningful conclusions. The departure point was a large data set of action potential trains from an Aplysia network whose neurons are connected by monosynaptic inhibitory or excitatory PSP's, and either discharged spontaneously or were driven by intracellular pulses. First, a sequence of “kernels” is estimated, each with a physiological connotation relevant to synaptic transmission. The kernel independent of time — of zero-order — measures the postsynaptic rate with no presynaptic discharge. That of a single time argument — of first-order — relates to the rate effect of the average PSP. Those of two, three, or more time arguments — of second, third or higher-order — relate to interactions between two, three, or more postsynaptic potentials (e.g. to facilitation) and/or spikes (e.g. to refractoriness). Then successive models are constructed recursively and based on the kernel of zero-order, on the kernels of zero and first order, on those of zero, first and second order, and so forth, until a desired approximation is achieved. The plausibilities of each kernel estimate and of each model are evaluated separately by way of spectra and coherences. The “linear” model based upon the zero and first-order kernel was tested (after that based exclusively on the zero-order one was proven inadequate). When presynaptic discharges are very irregular and at intermediate or low rates, it provides satisfactory description and prediction, and the first-order kernel is an uncontaminated display of the rate effects of the average presynaptic spike: this constitutes the “linear” domain. When presynaptic discharges are bursty, regular or very fast, the linear model is unsatisfyctory: this is referred to as “non-linear” domain. Reasons for non-linearity lie in PSP facilitation and anti-facilitation, conversion of membrane current into firing rate, after-spike excitability oscillations, and special pacemaker interactions. The model can be extended to three-neuron networks where partial coherences exract interactions between followers, even while submitted to a common driver. The basic and ubiquitous issues of spike train description and stability were discussed. The counting and the interval statistic of spike trains provide equivalent descriptions and their current opposition is conceptually meaningless. Concomitant short-term fluctuations in spike generation intensity at preand postsynaptic levels have funciional significance beyond changes in the overall average rate or interval: they are made precise by parameters whose definition, estimation and physiological interpretation are presented here. Some stability of the experimental preparation is presupposed by investigators, but variations (e.g. from cycles or deterioration) always exist. Hence, decisions as to the preparation's evolution and as to tolerable changes must be made, and based upon pre-existing knowledge, educated guesses and practical considerations. This study provided basic knowledge of the individual synapse considered the elementary building block of the nervous system when viewed as a network of interacting nerve cells. It also contributed generally applicable mathematical techniques which were illustrated by application to relatively well studied and simple networks.
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  • 3
    Electronic Resource
    Electronic Resource
    Oxford, UK : Blackwell Publishing Ltd
    Journal of the American Water Resources Association 21 (1985), S. 0 
    ISSN: 1752-1688
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Architecture, Civil Engineering, Surveying , Geography
    Notes: Fourier inference is a collection of analytic techniques and philosophic attitudes, for the analysis of data, wherein essential use is made of empirical Fourier transforms. This paper sets down some basic results concerning the finite Fourier transforms of stationary process data and then, to illustrate the approach, uses those results to develop procedures for: 1) estimating cloud and storm motion, 2) passive sonar and 3) fitting finite parameter models to nonGaussian time series via bispectral fitting. This last procedure is illustrated by an analysis of a stretch of Mississippi River runoff data. Examples 1), 2) refer to data having the form Y(xj, yj, t) for j = 1, …, J and t = 0, …, T-l say, and view that data as part of a realization of a spatial-temporal process. Such data has become common in geophysics generally and in hydrology particularly. The goal of this paper is to present some new statistical procedures pertinent to problems in the water sciences, equally it is to illustrate the genesis of those procedures and how their properties may be approximated.
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  • 4
    Electronic Resource
    Electronic Resource
    Springer
    Journal of theoretical probability 10 (1997), S. 429-443 
    ISSN: 1572-9230
    Keywords: Drift ; great circle path ; likelihood ratio ; pole-seeking ; skew product ; spherical Brownian motion ; stochastic differential equation ; travel time
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract Consider a particle moving on the surface of the unit sphere in R 3 and heading towards a specific destination with a constant average speed, but subject to random deviations. The motion is modeled as a diffusion with drift restricted to the surface of the sphere. Expressions are set down for various characteristics of the process including expected travel time to a cap, the limiting distribution, the likelihood ratio and some estimates for parameters appearing in the model.
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  • 5
    Electronic Resource
    Electronic Resource
    Springer
    Annals of biomedical engineering 16 (1988), S. 3-16 
    ISSN: 1573-9686
    Keywords: Causal connections ; Maximum likelihood ; Model fitting ; Neuronal firing ; Neuronal networks ; Parameter estimation ; Point process ; Quadratic kernel ; Spike trains ; System identification ; Threshold element
    Source: Springer Online Journal Archives 1860-2000
    Topics: Medicine , Technology
    Notes: Abstract The concern of this work is the identification of the (nonlinear) system of a neuron firing under the influence of a continuous input in one case, and firing under the influence of two other neurons in a second case. In the first case, suppose that the data consist of sample values Xt, Yt, t=0, ±1, ±2, ... with Yt=1 if the neuron fires in the time interval t to t+1 and Yt=0 otherwise, and with Xt denoting the (sampled) noise value at time t. Suppose that Ht denotes the history of the process to time t. Then, in this case the model fit has the form $$Prob\{ Y_t = 1|H_t \} = \Phi (U_t - \theta )$$ where $$U_t = \sum\limits_{u = 0}^{\gamma _t - 1} {a_u } X_{t - u} + \sum\limits_{u = 0}^{\gamma _t - 1} { \sum\limits_{\nu = 0}^{\gamma _t - 1} {b_{u,\nu } } X_{t - u} X_{t - \nu } } $$ where γ t denotes the time elapsed since the neuron last fired and ϕ denotes the normal cumulative. This model corresponds to quadratic summation of the stimulus followed by a random threshold device. In the second case, a network of three neurons is studied and it is supposed that $$U_t = \sum\limits_{u = 0}^{\gamma _t - 1} {a_u } X_{t - u} + \sum\limits_{u = 0}^{\gamma _t - 1} {b_u } X_{t - u} $$ with Xt and Zt zero-one series corresponding to the firing times of the two other neurons. The models are fit by the method of maximum likelihood toAplysia californica data collected in the laboratory of Professor J.P. Segundo. The paper also contains some general comments of the advantages of the maximum likelihood method for the identification of nonlinear systems.
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  • 6
    Publication Date: 1979-01-01
    Print ISSN: 0340-1200
    Electronic ISSN: 1432-0770
    Topics: Biology , Computer Science , Physics
    Published by Springer
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  • 7
    Publication Date: 1976-12-01
    Print ISSN: 0340-1200
    Electronic ISSN: 1432-0770
    Topics: Biology , Computer Science , Physics
    Published by Springer
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  • 8
    Publication Date: 1962-01-01
    Print ISSN: 0006-3444
    Electronic ISSN: 1464-3510
    Topics: Biology , Mathematics , Medicine
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  • 9
    Publication Date: 1969-01-01
    Print ISSN: 0006-3444
    Electronic ISSN: 1464-3510
    Topics: Biology , Mathematics , Medicine
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  • 10
    Publication Date: 1966-12-01
    Print ISSN: 0006-3444
    Electronic ISSN: 1464-3510
    Topics: Biology , Mathematics , Medicine
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