1. Core#

Core functions used to run the pipeline.

convertScanImageTiffToVolume(data_path, varargin)#

Convert ScanImage .tif files into a 4D volume.

Convert raw scanimage multi-roi .tif files from a single session into a single 4D volumetric time-series (x, y, z, t). It’s designed to process files for the ScanImage Version: 2016 software.

Parameters:
data_pathchar

The directory containing the raw .tif files. Only raw .tif files from one session should be in the directory.

save_pathchar, optional

The directory where processed files will be saved. It is created if it does not exist. Defaults to the data_path directory.

dsstring, optional

Name of the group (h5 dataset) to save the assembled data. Default is ‘/Y’. Must contain a leading slash.

debug_flagdouble, logical, optional

If set to 1, the function displays the files in the command window and does not continue processing. Defaults to 0.

do_figureslogical, optional

If set to 1, mean image and single frame figures are generated and saved to save_path. Defaults to 1. Note, figures will impact performance, particularly on datasets with many ROI’s.

overwritelogical, optional

Whether to overwrite existing files. In many instances, entire file will be deleted. Default is 0.

fix_scan_phaselogical, optional

Whether to correct for bi-directional scan artifacts. Default is true.

trim_roidouble, optional

Pixels to trim from [left, right, top, bottom] edge of each INDIVIDUAL ROI before horizontally concatenating the ROI’s within an image. Default is [0 0 0 0]. Only applies to ScanImage multi-ROI recordings.

trim_imagedouble, optional

Pixels to trim from [left, right, top, bottom] edge of each TILED IMAGE before horizontally concatenating the ROI’s within an image. Default is [0 0 0 0]. Only applies to ScanImage multi-ROI recordings.

z_plane_orderdouble, optional

If interleaved z-planes are not ordered from 1-n_planes, reorder the stack using this array as index.

motionCorrectPlane(data_path, varargin)#

Perform motion correction on imaging data.

Each motion-corrected plane is saved as a .h5 group containing the 2D shift vectors in x and y. The raw movie is saved in ‘/Y’ and the

Parameters:
data_pathchar

Path to the directory containing the files assembled via convertScanImageTiffToVolume.

save_pathchar

Path to the directory to save the motion vectors.

dschar, optional

Group path within the hdf5 file that contains raw data. Default is ‘/Y’.

debug_flagdouble, logical, optional

If set to 1, the function displays the files in the command window and does not continue processing. Defaults to 0.

do_figuresdouble, integer, positive

If true, correlation metrics will be saved to save_path/figures.

overwritelogical, optional

Whether to overwrite existing files (default is 0).

num_coresdouble, integer, positive

Number of cores to use for computation. The value is limited to a maximum of 24 cores.

start_planedouble, integer, positive

The starting plane index for processing.

end_planedouble, integer, positive

The ending plane index for processing. Must be greater than or equal to start_plane.

optionsstruct

NormCorre Params Object,

Notes

  • Only .h5 files containing processed volumes should be in the file_path.

segmentPlane(data_path, varargin)#

Segment imaging data using CaImAn CNMF.

This function applies the CaImAn algorithm to segment neurons from motion-corrected, pre-processed and ROI re-assembled MAxiMuM data. The processing is conducted for specified planes, and the results are saved to disk.

Parameters:
data_pathchar

Path to the directory containing the files assembled via convertScanImageTiffToVolume.

save_pathchar

Path to the directory to save the motion vectors.

dsstring, optional

Group path within the hdf5 file that contains raw data.

debug_flagdouble, logical, optional

If set to 1, the function displays the files in the command window and does not continue processing. Defaults to 0.

do_figuresdouble, integer, positive

If true, correlation metrics will be saved to save_path/figures.

overwritelogical, optional

Whether to overwrite existing files (default is 0).

num_coresdouble, integer, positive

Number of cores to use for computation. The value is limited to a maximum of 24 cores.

start_planedouble, integer, positive

The starting plane index for processing.

end_planedouble, integer, positive

The ending plane index for processing. Must be greater than or equal to start_plane.

optionsstruct

key:value pairs of all of your CNMF parameters. See the example parameters in the LBM_demo_pipeline.

Notes

T_keep : neuronal time series [Km, T]. single

Ac_keep : neuronal footprints [2*tau+1, 2*tau+1, Km]. single

C_keep : denoised time series [Km, T]. single

Km : number of neurons found. single

Cn : correlation image [x, y]. single

b : background spatial components [x*y, 3]. single

f : background temporal components [3, T]. single

acx : centroid in x direction for each neuron [1, Km]. single

acy : centroid in y direction for each neuron [1, Km]. single

acm : sum of component pixels for each neuron [1, Km]. single

collatePlanes(data_path, varargin)#

Parameters :param data_path: Path to the directory containing the files assembled via convertScanImageTiffToVolume. :type data_path: char :param save_path: Path to the directory to save the motion vectors. :type save_path: char :param ds: Group path within the hdf5 file that contains raw data. :type ds: string, optional :param debug_flag: If set to 1, the function displays the files in the command window and does

not continue processing. Defaults to 0.

Parameters:

  • do_figures (double, integer, positive) – If true, correlation metrics will be saved to save_path/figures.

  • overwrite (logical, optional) – Whether to overwrite existing files (default is 0).

  • num_cores (double, integer, positive) – Number of cores to use for computation. The value is limited to a maximum of 24 cores.

  • start_plane (double, integer, positive) – The starting plane index for processing.

  • end_plane (double, integer, positive) – The ending plane index for processing. Must be greater than or equal to start_plane.

  • num_features (double, positive) – The number of neurons to select for the lateral offset correction between z-planes. Default is 1 feature/neuron.

  • options (struct) – Struct containing key-value pairs for ‘min_SNR’ and ‘merge_thresh’.

  • motion_corrected_path (string) – Path to motion corrected data. Default is data_path/../motion_corrected/,

calculateZOffset(data_path, varargin)#
Parameters:
data_pathstring

Path to the directory containing the image data and calibration files. The function expects to find ‘pollen_sample_xy_calibration.mat’ in this directory along with each caiman_output_plane_N.

motion_corrected_path: string

Path to motion corrected data. Default is data_path/../motion_corrected/,

debug_flagdouble, logical, optional

If set to 1, the function displays the files in the command window and does not continue processing. Default is 0.

overwritelogical, optional

Whether to overwrite existing files. Default is 0.

start_planedouble, integer, positive

The starting plane index for processing. Default is 1.

end_planedouble, integer, positive

The ending plane index for processing. Must be greater than or equal to start_plane. Default is 1.

num_featuresdouble, integer, positive

The number of features to identify and use in each plane for calculating offsets. Default is 2 features (neurons) compared across z-plane/z-plane+1.

Returns:
offsetsNx2 array

An array of offsets between consecutive planes, where N is the number of planes processed. Each row corresponds to a plane, and the two columns represent the calculated offset in pixels along the x and y directions, respectively.

metadata: struct

Notes

  • This function requires calibration data in input datapath: - pollen_sample_xy_calibration.mat

  • The function uses MATLAB’s ginput function for manual feature selection on the images. It expects the user to manually select the corresponding points on each plane.

  • The function assumes that the consecutive images will have some overlap and that features will be manually identifiable and trackable across planes.

Examples

[offsets, metadata] = calculateZOffset(‘C:/data/images/’, metadata, 1, 10, 5);