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We've seen a couple of occasions where people use a typical 1P or 2P setup to acquire a static image, particularly of anatomical structure
The usual recommendation has been to use the existing time-dependent data types with only a single frame and a rate of 0.0, possibly starting_time=NaN if the time it was acquired wasn't recorded or relevant
However, it would be better if there was a specific neurodata type that by definition was time-independent; essentially like the types found in the Images module of the NWB schema, but can allow for ophys metadata (imaging planes, optic channels, etc.) to be attached as they normally would be for the time-varying series
The text was updated successfully, but these errors were encountered:
We've seen a couple of occasions where people use a typical 1P or 2P setup to acquire a static image, particularly of anatomical structure
The usual recommendation has been to use the existing time-dependent data types with only a single frame and a
rate
of0.0
, possiblystarting_time=NaN
if the time it was acquired wasn't recorded or relevantHowever, it would be better if there was a specific neurodata type that by definition was time-independent; essentially like the types found in the Images module of the NWB schema, but can allow for ophys metadata (imaging planes, optic channels, etc.) to be attached as they normally would be for the time-varying series
The text was updated successfully, but these errors were encountered: