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matlab function gamrnd  (MathWorks Inc)


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    MathWorks Inc matlab function gamrnd
    Matlab Function Gamrnd, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/matlab function gamrnd/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    matlab function gamrnd - by Bioz Stars, 2026-03
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    Constant target rate templates. Surrogate data were constructed as rate templates with a constant target rate and low or high spiking regularity (LV of 0.1 or 1.5). We find that the average spike rate from 100 ASTs matches the target rate with only very small errors (see Table 2). The individual ASTs (blue traces) show large rate fluctuations due to the stochastic nature of the <t>gamma</t> spike train. These random rate fluctuations are much more pronounced for a highly irregular spike train target (Fig. 7b,​,d;d; LV=1.5) vs. a regular spike train target (Fig. 7a,​,c).c). <t>Individual</t> <t>AST</t> rates were constructed as aGLRs with a scale factor (sf, eq. 4) of 1.0 instead of 0.25 as used for physiological spike trains in order to more clearly show the contribution of single spikes to rate changes (Fig 4a,​,b;b; blue trace).
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    Constant target rate templates. Surrogate data were constructed as rate templates with a constant target rate and low or high spiking regularity (LV of 0.1 or 1.5). We find that the average spike rate from 100 ASTs matches the target rate with only very small errors (see Table 2). The individual ASTs (blue traces) show large rate fluctuations due to the stochastic nature of the <t>gamma</t> spike train. These random rate fluctuations are much more pronounced for a highly irregular spike train target (Fig. 7b,​,d;d; LV=1.5) vs. a regular spike train target (Fig. 7a,​,c).c). <t>Individual</t> <t>AST</t> rates were constructed as aGLRs with a scale factor (sf, eq. 4) of 1.0 instead of 0.25 as used for physiological spike trains in order to more clearly show the contribution of single spikes to rate changes (Fig 4a,​,b;b; blue trace).
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    Constant target rate templates. Surrogate data were constructed as rate templates with a constant target rate and low or high spiking regularity (LV of 0.1 or 1.5). We find that the average spike rate from 100 ASTs matches the target rate with only very small errors (see Table 2). The individual ASTs (blue traces) show large rate fluctuations due to the stochastic nature of the <t>gamma</t> spike train. These random rate fluctuations are much more pronounced for a highly irregular spike train target (Fig. 7b,​,d;d; LV=1.5) vs. a regular spike train target (Fig. 7a,​,c).c). <t>Individual</t> <t>AST</t> rates were constructed as aGLRs with a scale factor (sf, eq. 4) of 1.0 instead of 0.25 as used for physiological spike trains in order to more clearly show the contribution of single spikes to rate changes (Fig 4a,​,b;b; blue trace).
    Gamrnd Function Part Of Matlab's Statistics Toolbox, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/gamrnd function part of matlab's statistics toolbox/product/MathWorks Inc
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    Constant target rate templates. Surrogate data were constructed as rate templates with a constant target rate and low or high spiking regularity (LV of 0.1 or 1.5). We find that the average spike rate from 100 ASTs matches the target rate with only very small errors (see Table 2). The individual ASTs (blue traces) show large rate fluctuations due to the stochastic nature of the gamma spike train. These random rate fluctuations are much more pronounced for a highly irregular spike train target (Fig. 7b,​,d;d; LV=1.5) vs. a regular spike train target (Fig. 7a,​,c).c). Individual AST rates were constructed as aGLRs with a scale factor (sf, eq. 4) of 1.0 instead of 0.25 as used for physiological spike trains in order to more clearly show the contribution of single spikes to rate changes (Fig 4a,​,b;b; blue trace).

    Journal: Journal of computational neuroscience

    Article Title: A general method to generate artificial spike train populations matching recorded neurons

    doi: 10.1007/s10827-020-00741-w

    Figure Lengend Snippet: Constant target rate templates. Surrogate data were constructed as rate templates with a constant target rate and low or high spiking regularity (LV of 0.1 or 1.5). We find that the average spike rate from 100 ASTs matches the target rate with only very small errors (see Table 2). The individual ASTs (blue traces) show large rate fluctuations due to the stochastic nature of the gamma spike train. These random rate fluctuations are much more pronounced for a highly irregular spike train target (Fig. 7b,​,d;d; LV=1.5) vs. a regular spike train target (Fig. 7a,​,c).c). Individual AST rates were constructed as aGLRs with a scale factor (sf, eq. 4) of 1.0 instead of 0.25 as used for physiological spike trains in order to more clearly show the contribution of single spikes to rate changes (Fig 4a,​,b;b; blue trace).

    Article Snippet: The AST generation process starts at t=0 by selecting a random gamma interval using the Matlab gamrnd() function for a mean rate of 1, and a regularity of κ.

    Techniques: Construct