[FieldTrip] clustering, spatial neighbors and minnbchan

[Clara A. Scholl]

Hi,

I have a question about how to identify appropriate parameters for
neighbor distance in ft_neighbourselection and how to set minnbchan
for space-time cluster analysis.

I identified a neighbor distance based on our sensor layout, so that
spatially adjacent channels were defined as neighbors, and spatially
non-adjacent channels were not defined as neighbors.  I then ran
space-time cluster analysis and identified a cluster with a large
spatial and temporal extent which appears to be the continuation of
several effects lumped together.  I subsequently increased minnbchan,
so that this cluster gets separated into separate clusters following
the logic in this discussion thread:
http://mailman.science.ru.nl/pipermail/fieldtrip/2011-February/003501.html

However now a new problem appears: it seems that channels near the
periphery of the sensor layout, which have few adjacent spatial
neighbors, are not included in the clusters when minnbchan has a value
greater than the number of neighbors the channels have according to
the neighbor distance used in ft_neighbourselection.  Is this correct?
 Put differently, increasing minnbchan appears to bias clusters toward
including only channels at the center of the sensor layout, with many
adjacent other channels (and channels at the periphery of the layout,
which have fewer spatial neighbors, are excluded from the identified
clusters).

Obviously I want a principled, data-independent selection of cluster
identification parameters so I want to ask what the "correct" way to
identify these parameters (neighbor distance, and minnbchan) is.
Should minnbchan be used differently for channel-time cluster analysis
(what I'm doing) compared to channel-time-frequency cluster analysis?

Thanks,
Clara