isiHistFit: ISI Histogram With Fitted Model and CI

In STAR: Spike Train Analysis with R

Description

Fits a duration model to isis from a spike train. Confidence intervals are also drawn.

Usage

isiHistFit(spikeTrain, model, nbins = 10, CI = 0.95, ...)

Arguments

spikeTrain	a spikeTrain object or a numeric vector that can be coerced to such an object.
model	a character vector whose elements are selected among: "invgauss", "lnorm", "gamma", "weibull", "llogis", "rexp".
nbins	the number of bins to use.
CI	the confidence coefficient.
...	additional arguments passed to hist, see hist.

Details

Assuming that the train is reasonably well described by a renewal process, a model distribution is fitted to the inter-spike intervals (isis) obtained from spikeTrain. The fitted distribution is then used to set the histogram breaks such that a uniform bin count would be expected if the fitted distribution was the true one. Confidence segments are also obtained from the binomial distribution. The histogram is build and the fitted density together with confidence intervals are drawn.

Value

Nothing returned, isiHistFit is used for its side effect, a plot is generated on the current graphic device.

Author(s)

Christophe Pouzat [e-mail]

See Also

compModels, hist

Examples

## Not run: 
## load spontaneous data of 4 putative projection neurons
## simultaneously recorded from the cockroach (Periplaneta
## americana) antennal lobe
data(CAL1S)
## convert data into spikeTrain objects
CAL1S <- lapply(CAL1S,as.spikeTrain)
## look at the individual trains
## first the "raw" data
CAL1S[["neuron 1"]]
## next some summary information
summary(CAL1S[["neuron 1"]])
## next the renewal tests
renewalTestPlot(CAL1S[["neuron 1"]])
## It does not look too bad so let fit simple models
compModels(CAL1S[["neuron 1"]])
## the best one is the invgauss. Let's look at
## it in detail
isiHistFit(CAL1S[["neuron 1"]],"invgauss",xlim=c(0,0.5))

## End(Not run)

Example output

Loading required package: survival
Loading required package: mgcv
Loading required package: nlme
This is mgcv 1.8-28. For overview type 'help("mgcv-package")'.
Loading required package: R2HTML
Loading required package: gss
Loading required package: codetools
A spike train with 195 events, starting at: 0.318 and ending at: 30.379 (s).
The mean ISI is: 0.155 and its SD is: 0.283 (s).
The mean log(ISI) is: -2.838 and its SD is: 1.291
The shortest interval is: 0.007
 and the longest is: 1.99 (s).
 invgauss     lnorm    llogis   weibull     gamma      rexp 
-477.1587 -448.4228 -444.7260 -387.0661 -364.5763 -348.6731 
Warning messages:
1: In rep(yi[si > 0], each = ni[si > 0]) :
  first element used of 'each' argument
2: In rep(yi[si > 0], each = si[si > 0]) :
  first element used of 'each' argument
3: In rep(yi[si > 0], each = si[si > 0]) :
  first element used of 'each' argument
4: In rep(yi[si > 0], each = si[si > 0]) :
  first element used of 'each' argument
5: In rep(yi[si > 0], each = si[si > 0]) :
  first element used of 'each' argument
6: In rep(yi[si > 0], each = si[si > 0]) :
  first element used of 'each' argument
7: In rep(yi[si > 0], each = si[si > 0]) :
  first element used of 'each' argument

STAR documentation built on May 2, 2019, 4:53 p.m.