Connectivity image size is not matched with no of EEG channels

Hi sir,
I have created the connectivity matrix (correlation, coherence) based on 20 channels of EEG. So it is obvious that the resultant connectivity matrix size should be 20x20 (one pixel/connection), however after computing the connectivity matrix the image size is 873x710. How this can happen (20x20->873x710)? How is the image size big for 20 channels connectivity?
I have attached the image and .excel file of correlation connectivity.
Please help me out.THMS_MA_CorrMat_20Channels.csv (6.4 KB) Corr_Matrix_20channels

The screen capture of the figure that you posted shows a 20x20 connectivity matrix. Click anywhere on the figure to see the name of the row/column in the legent.
The CSV you posted is also 20x20.

Are you getting mixed up with with number of pixels in your screen capture?

Thanks for the update.
Actually I know its a 20x 20 connectivity matrix and each cell (row/column) represents the connectivity value between channels. However the figure size is 873x710 pixels. So my question is how the brainstorm map each connection value to pixels?
Actually I have tried to run a deep convolutional model (2DCNN) that enforces a connection from that image pixels size.

[quote="ddaschakladar, post:3, topic:31739"]

However the figure size is 873x710 pixels. So my question is how the brainstorm map each connection value to pixels?

Actually I have tried to run a deep convolutional model (2DCNN) that enforces a connection from that image pixels size.

You should never use the displayed values from the figure.
Use the real data, saved in the TF matrix of the file.

Thanks sir for the information.