Hello,

is there a handy index available to read out the distances between electrodes in the Biosemi caps? For instance, I have data from the Biosemi 128 cap, with A1-32, B1-32, C1-32, D1-32 electrodes. If I want to define a region of interest in Matlab, I must select specific sets of electrodes because labels which are adjacent in number are often NOT adjacent in topography and vice versa, e.g. A8-12 is adjacent to D29-32. A1 is adjacent to A2, B1, C1, D1 and D15. And it can be quite arbitrary to decide what is adjacent and what not, a better solution would be to just define a radius within which all electrodes are included.

Thus it would be really handy to have a table giving the distance between every pair of electrodes, so that one could iterate through all electrodes and for each one, easily pick all adjacent electrodes, or electrodes within X mm, etc.

Any body have any promising leads?

## Electrode proximity/distance

### Re: Electrode proximity/distance

Addendum: of course I would also be happy to see a method for calculating the proximity table myself based on spherical or XYZ coordinates.

### Re: Electrode proximity/distance

Hmm, not sure if this is a *good* solution, but once I thought of it the rest was easy so here it is:

function [epmap rownm colnm] = electrodeProximity( EEG )

%% Calculates the Euclidean distances between all pairs of electrodes given

%

% Note: The function disregards "non-EEG" channels. These are taken as specified

% in the channel location structure/file (anything not labeled EEG or

% "empty" is considered non-EEG). It is highly recommended that you define

% a channel type for each channel, when you define your channel location file.

%

% Syntax:

% epmap = electrodeProximity( EEG )

%

% Parameters

% EEG

eegChan = strcmp('EEG',{EEG.chanlocs.type}) | strcmp('',{EEG.chanlocs.type});

eegchs = sum(eegChan);

epmap = zeros(eegchs);

rownm = cell(eegchs,1);

colnm = cell(1,eegchs);

for i = 1:eegchs

rownm(i) = EEG.chanlocs(i).labels;

for k = i+1:eegchs

A = [EEG.chanlocs(i).X; EEG.chanlocs(i).Y; EEG.chanlocs(i).Z];

B = [EEG.chanlocs(k).X; EEG.chanlocs(k).Y; EEG.chanlocs(k).Z];

epmap(i,k) = eucl_dist(A, B);

if i == 1, colnm(k) = EEG.chanlocs(k).labels; end

end

end

end

function d = eucl_dist(a,b)

aa=sum(a.*a,1); bb=sum(b.*b,1); ab=a'*b;

d = sqrt(abs(repmat(aa',[1 size(bb,2)]) + repmat(bb,[size(aa,2) 1]) - 2*ab));

function [epmap rownm colnm] = electrodeProximity( EEG )

%% Calculates the Euclidean distances between all pairs of electrodes given

%

% Note: The function disregards "non-EEG" channels. These are taken as specified

% in the channel location structure/file (anything not labeled EEG or

% "empty" is considered non-EEG). It is highly recommended that you define

% a channel type for each channel, when you define your channel location file.

%

% Syntax:

% epmap = electrodeProximity( EEG )

%

% Parameters

% EEG

eegChan = strcmp('EEG',{EEG.chanlocs.type}) | strcmp('',{EEG.chanlocs.type});

eegchs = sum(eegChan);

epmap = zeros(eegchs);

rownm = cell(eegchs,1);

colnm = cell(1,eegchs);

for i = 1:eegchs

rownm(i) = EEG.chanlocs(i).labels;

for k = i+1:eegchs

A = [EEG.chanlocs(i).X; EEG.chanlocs(i).Y; EEG.chanlocs(i).Z];

B = [EEG.chanlocs(k).X; EEG.chanlocs(k).Y; EEG.chanlocs(k).Z];

epmap(i,k) = eucl_dist(A, B);

if i == 1, colnm(k) = EEG.chanlocs(k).labels; end

end

end

end

function d = eucl_dist(a,b)

aa=sum(a.*a,1); bb=sum(b.*b,1); ab=a'*b;

d = sqrt(abs(repmat(aa',[1 size(bb,2)]) + repmat(bb,[size(aa,2) 1]) - 2*ab));

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