ssc-1 questions about imaging planes and volumes

Hi,

We are studying your ssc-1 data and would like to compensate the calcium traces for the scanning time-lags. With this in mind, I have a few questions:

(1) It appears that different sessions have different numbers of sub-volumes, and different imaging plane structures within each sub-volume:

        e.g.    an229719_2013_12_05_session.mat     has  6 sub-volumes, with a [3,3,3,3,3,3] plane structure

      but       an197522_2013_03_10_session   has 9 sub-volumes with a [3,1,1,2,3,3,3,3,2] plane structure

From your documentation, I understand that within a sub-volume the planes are separated by 15 microns. What is the separation between the bottom plane of a sub-volume and the top plane of the next deeper sub-volume? We would like to better understand which cortex layer each sub-volume is imaging.

(2)  Can you provide us with any detailed information about the scanning of the pixels, in particular with regards to the time lags associated with the scanning? In which order are the pixels scanned within an imaging plane?  How long does it take to scan a single plane? How long to switch to the next plane? Any information you can provide might help improve our analysis of the data.

(3) Do the time-stamps for the sub-volume scans in the time-series data indicate the start of the scan for that sub-volume?

Thank you for your time and help..

1) The separation is 15 um between adjacent subvolumes, give or take.  

2) pixels are scanned with fast movement along the X (horizontal) dimension and slow movement along the Y (vertical) dimension.  The line rate on the resonant galvanometer was 14.3kHz, and we scanned 512 lines per plane; there were 4 planes, 3 of which were imaged and 1 of which was the flyback for the piezo that was dropped.  so 1 2 3 F 1 2 3 F ... was the plane sequence.  So each plane takes 512/14300 seconds and the interval between revisiting the same point is 2048/14300 seconds (512 * 4, and for 512 of those lines you are not imaging as you are flying back axially along the piezo)

3) Yes.

Thank very much Simon

Is there any annotation in the data structure to indicate which cells are interneurons?

If my question is not clear, I am referring to the "red nuclear marker", which in some cases labels interneurons and in others excitatory neurons. This is apparently in the raw imaging data, but I do not see any annotations of it in the matlab data structure. Since the structure is fairly complex, I just want to verify that I am not missing it.