I have UNM dataset for Parkinson's disease which is publicly available in .mat format. I'm trying to work on it using MNE python and for that I need to get the spatial distribution of the electrodes to generate MNE object.
so far after using scipi.io to read the data I've got following format for each electrode
['FC5'] [] [[-69.332]] [[0.40823333]] [[28.76282344]] [[76.24736451]] [[24.16690699]] [[69.332]] [[16.518]] [[85]] [[6]] []
about last two entries 85 is same in all 63 electrodes and 6 here is electrode index but what all these other numbers supposed to mean? where are the coordinates? Can someone explain?
Hi,
You have the name of the sensor in your example. Therefore, you can try to use already existed layouts for sensors location. For example, in MATLAB you can use eeglab or FieldTrip frameworks.
Best regards, Alexey
Need to capture deep brain signals using Electrocorticography (ECoG). Further, FFT and Inter Electrode response may be helpful.
Based on the information you provided, it seems that you have obtained electrode information for each electrode in the UNM dataset for Parkinson's disease. However, the information provided does not seem to include the spatial coordinates of the electrodes.
The other numbers in the electrode information may represent various electrode properties or measurements, but without additional information or context, it is difficult to say for certain what they represent. For example, the first number in the third set of brackets may represent the electrode impedance or resistance, while the numbers in the other brackets may represent other electrical properties or measurements.
To obtain the spatial coordinates of the electrodes, you may need to consult additional documentation or metadata associated with the UNM dataset. This metadata may include information such as the electrode locations or the electrode montage used to acquire the data.
Alternatively, you may be able to infer the electrode locations from the electrode labels themselves. The electrode labels typically follow a standard naming convention, such as the 10-20 system, which specifies the approximate location of each electrode on the scalp. By using this information, you may be able to estimate the spatial coordinates of the electrodes.
Once you have obtained the spatial coordinates of the electrodes, you can use them to generate an MNE object in Python. The MNE Python library provides several functions for reading and importing electrode coordinates, such as mne.channels.read_custom_montage() and mne.channels.make_standard_montage(). By using these functions, you can create an MNE object that includes the electrode locations and can be used for further analysis.
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