Description Usage Arguments Details Value Author(s) References See Also Examples
psth
computes and plot.psth
plots a peristimulus time histogram (called PST,
poststimulus time histogram by Gerstein and Kiang (1960)) from
repeated presentations of a stimulation. Confidence bands can be
obtained using the Poisson approximation.
1 2 3 4 5 6 
repeatedTrain 
a 
x 
a 
stimTimeCourse 

colStim 
the background color used for the stimulus. 
breaks 
a numeric. A single number is interpreted has the number of bins; a vector of length 2 is interpreted as the bin width and the step to use (see details); otherwise interpreted as the position of the "breaks" between bins. 
include.lowest 
corresponding argument of 
right 
corresponding argument of 
plot 
corresponding argument of 
CI 
The coverage probability of the confidence intervals. 
colCI 
if not 
xlim 
a numeric (default value supplied). See

ylim 
a numeric (default value supplied). See 
xlab 
a character (default value supplied). See 
ylab 
a character (default value supplied). See 
main 
a character (default value supplied). See 
lwd 
line width used to plot the estimated density. See 
col 
color used to plot the estimated density. See 
... 
see 
When confidence bands are requested they are obtained from the
qunatiles of the Poisson
distribution.
When a 2 elements vector is used as breaks
argument it is
interpreted as specifying a bin width (first element if elements are
unnamed, "bw"
element otherwise) and a step (second element if
elements are unnamed, "step"
element otherwise). The idea is
then to obtain a smoother looking PSTH by counting spikes within
overlapping bins. That is if the center of the ith bin is xi the one
of the (i+1)th bin will be xi + step.
When plot
is set to FALSE
in psth
, a list of
class psth
is returned and no plot
is generated. This list has the following components:
freq 
a vector containing the instantaneous firing rate. 
ciUp 
a vector with the upper limit of the confidence band. 
ciLow 
a vector with the lower limit of the confidence band. 
breaks 
a numeric vector with the breaks in between which spikes
were counted. Similar to the component of the same name returned by

mids 
a numeric vector with the mid points of

counts 
a matrix with as many rows as components in

nbTrials 
the number of stimulations. 
call 
the matched call. 
When plot
is set to TRUE
nothing is returned and a plot
is generated as a side effect. Of course the same occurs upon calling
plot.psth
with a psth
object argument.
Christophe Pouzat [email protected]
Gerstein, George L. and Kiang, Nelson Y.S. (1960) An Approach to the Quantitative Analysis of Electrophysiological Data from Single Neurons. Biophysical Journal 1: 15–28. http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pubmed&pubmedid=13704760
Kalbfleisch, J. G. (1985) Probability and Statistical Inference. Volume 2: Statistical Inference. SpringerVerlag.
as.repeatedTrain
,
is.repeatedTrain
,
print.repeatedTrain
,
summary.repeatedTrain
,
raster
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35  ## Load Vanillin responses data (first cockroach data set)
data(CAL1V)
## convert them into repeatedTrain objects
## The stimulus command is on between 4.49 s and 4.99s
CAL1V < lapply(CAL1V,as.repeatedTrain)
## look at the individual raster plots
plot(CAL1V[["neuron 1"]],stimTimeCourse=c(4.49,4.99),main="N1")
## Create a simple black and white PSTH for neuron 1
psth(CAL1V[["neuron 1"]],stimTimeCourse=c(4.49,4.99),breaks=20)
## Rebuilt the same PSTH but with red confidence bands
psth(CAL1V[["neuron 1"]],stimTimeCourse=c(4.49,4.99),breaks=20,colCI=2)
## Make the PSTH smoother
psth(CAL1V[["neuron 1"]],stimTimeCourse=c(4.49,4.99),breaks=c(bw=0.5,step=0.05),colCI=2)
## Make a plot with PSTHs from 4 neurons superposed
## First get lists containing PSTHs from each neuron
psth1 < psth(CAL1V[["neuron 1"]],breaks=c(bw=0.5,step=0.05),plot=FALSE)
psth2 < psth(CAL1V[["neuron 2"]],breaks=c(bw=1,step=0.1),plot=FALSE)
psth3 < psth(CAL1V[["neuron 3"]],breaks=c(bw=0.5,step=0.05),plot=FALSE)
psth4 < psth(CAL1V[["neuron 4"]],breaks=c(bw=2,step=0.2),plot=FALSE)
## Get the maximal frequency to display
maxFreq < max(max(psth1$ciUp),max(psth2$ciUp),max(psth3$ciUp),max(psth4$ciUp))
## Build plot
plot(c(0,10),c(0,75),type="n",
xaxs="i",yaxs="i",xlab="Time (s)",
ylab="Freq. (Hz)",
main="PSTHs from 4 simultaneously recorded neurons",
sub="20 stimulations with vanillin were used.")
## Add rectangle corresponding to stimulation command
rect(4.49,0,4.99,75,col="grey80",lty=0)
## Add the neurons PSTHs as confidence bands
polygon(c(psth1$mids,rev(psth1$mids)),c(psth1$ciLow,rev(psth1$ciUp)),col=1,border=NA)
polygon(c(psth2$mids,rev(psth2$mids)),c(psth2$ciLow,rev(psth2$ciUp)),col=2,border=NA)
polygon(c(psth3$mids,rev(psth3$mids)),c(psth3$ciLow,rev(psth3$ciUp)),col=3,border=NA)
polygon(c(psth4$mids,rev(psth4$mids)),c(psth4$ciLow,rev(psth4$ciUp)),col=4,border=NA)
legend(0.1,maxFreq,legend=paste("neuron",1:4),lty=1,col=1:4,bty="n")

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