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the default rdmfun behavior is to transpose a (voxel x condition) data matrix and then apply the pdist function to achieve a (condition x condition) RDM. however, in each monte carlo simulation, the signal and measurement variables already come in (condition x voxel) format, requiring each matrix to be transposed when passed to rdmfun() only to be re-transposed immediately afterward via rdmfun().
is there a reason for this double-transpose? if not, for clarity, we should consider removing both by modifying the line which sets the default rdmfun() and the line where rdmfun() is applied to signal and measurement.
The text was updated successfully, but these errors were encountered:
No real reason for the double transpose;it's just necessary for everytihng to work out. It just seems more natural for people to think in terms of "voxels x conditions x trials" as the standard format. Do you agree? If not, what do you suggest?
the default rdmfun behavior is to transpose a (voxel x condition) data matrix and then apply the pdist function to achieve a (condition x condition) RDM. however, in each monte carlo simulation, the signal and measurement variables already come in (condition x voxel) format, requiring each matrix to be transposed when passed to rdmfun() only to be re-transposed immediately afterward via rdmfun().
is there a reason for this double-transpose? if not, for clarity, we should consider removing both by modifying the line which sets the default rdmfun() and the line where rdmfun() is applied to signal and measurement.
The text was updated successfully, but these errors were encountered: