[R] finding "clusters" in 2-dimensional data

[Nathan Weisz]

hi,

i have done a time-frequency analysis on magnetencephalographic data
under different conditions. the matrices for each condition are three
dimensional: frequency x time x subject.
to identify time-frequency "areas" of interest i would first calculate a
simple t-test for each time frequency point. this is straightforward and
for each comparison i have a frequency x time representation of
t-values. using an alpha threshold "candidate" time-frequency regions
can be identified. I will just call them clusters for simplicity. the
t-values within each cluster are added (T).
to find out which clusters can be considered significant i would like to
implement a randomization test to generate a distribution of Tmax with
which I could compare my original Ts with.

However I'm stuck at the lowest possible level ... well the second
lowest level (the t.test is easy) :-)
starting from the time x frequency representation of t-values, masked so
that all values with p's below some magical number are set to 0: is
there some ready-made function in R that can help me identifying the
clusters (i.e. returning the array-indexes)?

the general idea outlined here is implemented under Matlab in the
Fieldtrip toolbox. however, the relevant function relies on functions
from the Image Processing toolbox (which i don't have). furthermore i
would really like to outsource statistics from Matlab to R whenever I
can.

Thanks ins advance for any help,
nathan