Description Usage Arguments Details Value Note Author(s) References See Also Examples
Some mainly graphical tools to probe interactions between 2 neurons recorded in the presence of a repeated stimulation.
1 2 3 4 5 6 7 8 9 10 11  jsd(xRT, yRT, acquisitionWindow, xlab, ylab,
main, pch = ".", ...)
jpsth(xRT, yRT, xBreaks, yBreaks,
acquisitionWindow, nbEvtPerBin = 50)
## S3 method for class 'jpsth'
contour(x, xlab, ylab, main, ...)
## S3 method for class 'jpsth'
image(x, xlab, ylab, main, ...)
## S3 method for class 'jpsth'
persp(x, xlab, ylab, main, ...)
jpsth2df(object)

xRT 
a 
yRT 
a 
x, object 

xBreaks, yBreaks 
A single number (the bin width) or a vector defining bins boundaries on the X and Y axis. If missing a default is provided. 
acquisitionWindow 
a 2 elements vector specifying the begining
and the end of the acquisition. If missing values are obtained using
the 
nbEvtPerBin 
If both 
xlab 
a character (default value supplied). See 
ylab 
a character (default value supplied). See 
main 
a character (default value supplied). See 
pch 
the type of "points" displayed by 
... 
additional arguments passed to 
The joint scatter diagram was introduced by Gerstein and Perkel
(1972). The joint peristimulus time histogram is a binned version of
it (Aertsen et al, 1989). jpsth2df
allows the reformating of a jpsth
object in
order to compute a smooth version of it with
gssanova
, gssanova0
or gam
.
jsd
is used for its side effect, a plot is generated and
nothing is returned.
jpsth2df
returns a data.frame
with the following
variables: Count
, the counts per cell; X
, the position
of the cell on the X axis; Y
, the position of the cell on the Y
axis;
and attributes: xBreaks
, yBreaks
, xTotal
,
yTotal
, nbTrials
, acquisitionWindow
corresponding
to the components of its argument with the same name and
originalCall
corresponding to component call
.
jpsth
returns a list of class jpsth
with the following
components:
counts 
a matrix storing the counts per cell. 
density 
a matrix storing the density in each cell. 
xMids 
a vector containing the X positions of the cells. 
yMids 
a vector containing the Y positions of the cells. 
xBreaks 
a vector containing the bin boundaries of the cells along the X axis. 
yBreaks 
a vector containing the bin boundaries of the cells along the X axis. 
xTotal 
the total number of spikes of the "X" neuron. 
yTotal 
the total number of spikes of the "Y" neuron. 
xFreq 
the mean freqency of the "X" neuron. 
yFreq 
the mean freqency of the "Y" neuron. 
nbTrials 
the number of trials of 
acquisitionWindow 
the boundaries of the acquisition window. 
call 
the matched call. 
I use "joint scatter diagram" for what Gerstein and Perkel (1972) more properly call a "joint peristimulus time scatter diagram".
Christophe Pouzat christophe.pouzat@gmail.com
Gerstein, G. L. and Perkel, D. H. (1972) Mutual temporal relationships among neuronal spike trains. Statistical techniques for display and analysis. Biophys J 12: 453–473. http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=1484144
Aertsen, A. M., Gerstein, G. L., Habib, M. K., Palm, G. (1989) Dynamics of neuronal firing correlation: modulation of "effective connectivity". J Neurophysiol 61: 900–917. http://jn.physiology.org/cgi/content/abstract/61/5/900
lockedTrain
,
plot.lockedTrain
,
hist.lockedTrain
,
gsslockedTrain
,
plot.gsslockedTrain
,
gsslockedTrain0
,
plot.gsslockedTrain0
,
gamlockedTrain
,
plot.gamlockedTrain
,
contour
,
image
,
persp
,
attr
,
attributes
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  ## load e070528citronellal data
data(e070528citronellal)
## plot a jsd with neuron 1 on X and neuron 2 on Y
jsd(e070528citronellal[[1]],e070528citronellal[[2]])
## now make the jpsth
j1.2 < jpsth(e070528citronellal[[1]],e070528citronellal[[2]])
## make a contour plot
contour(j1.2)
## make an image plot
image(j1.2)
## make a persp plot
persp(j1.2)
## Not run:
## fit a gss model with interactions
## use a larger bin width for the jpsth
j1.2 < jpsth(e070528citronellal[[1]],e070528citronellal[[2]],0.2,0.2)
## get a data frame
j1.2DF < jpsth2df(j1.2)
## To save computation time start analyzing
## just before the stimulation time
j1.2DF < j1.2DF[j1.2DF$X > 6 & j1.2DF$Y>6,]
gf < gssanova(Count ~ X*Y, family="poisson", data=j1.2DF,seed=20061001)
## Use the project function of gss to check the significance
## of the interaction term
project(gf2,inc=c("X","Y"))
## End(Not run)
## Not run:
## fit a gam model assuming no interaction
## get a data frame
j1.2DF < jpsth2df(j1.2)
fitNoI < gam(Count ~ s(X,k=100,bs="cr") + s(Y,k=100,bs="cr"),data=j1.2DF,family=poisson())
## End(Not run)

Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.