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Interpreting Results

eftychios pnevmatikakis edited this page Jun 15, 2018 · 1 revision

Result variables for 2p batch analysis

The variables of interest are:

  • A: Set of spatial components. Saved as a sparse matrix with dimensions (# of pixels X # of components). Each column corresponds to a spatial component.
  • C: Set of temporal components. Saved as an array with dimensions (# of components X # of timesteps). Each row corresponds to a background component denoised and deconvolved.
  • b: Set of background spatial components. Saved as an array with dimensions (# of pixels X # of components). Each column corresponds to a spatial background component.
  • f: Set of temporal background components. Saved as an array with dimensions (# of background components X # of timesteps). Each row corresponds to a temporal background component.
  • S: Deconvolved neural activity (spikes) for each component. Saved as an array with dimensions (# of background components X # of timesteps). Each row corresponds to the deconvolved neural activity for the corresponding component.
  • YrA: Set or residual components. Saved as an array with dimensions (# of components X # of timesteps). Each row corresponds to the residual signal after denoising the corresponding component in C.
  • F_dff: Set of DF/F normalized temporal components. Saved as an array with dimensions (# of components X # of timesteps). Each row corresponds to the DF/F fluorescence for the corresponding component.

To view the spatial components, their corresponding vectors need first to be reshaped into 2d images. For example if you want to view the i-th component you can type

figure;imagesc(reshape(A(:,i-1), d1,d2))

where d1,d2 are the dimensions of the FOV. Similarly if you want to plot the trace for the i-th component you can simply type

figure;plot(C(i,:))

The commands plot_contours and plot_components_GUI can be used to visualize all the components.

Variables for component evaluation

If you use post-screening to evaluate the quality of the components and remove bad components the results are stored in the variable keep which is a binary vector indexing whether a component is kept or not.

These lists can be used to index the results. For example A[:,keep] or C[keep,:] will return the accepted spatial or temporal components, respectively. Similarly, A[:,~keep] or C[~keep,:] will return the accepted spatial or temporal components, respectively.