%This script uses the HMM Matlab toolbox to train an HMM on multiple-trial
%data
function [observ] = Extract_Observ(spk_vec,time_vec,cell_nums),

spk_vec;            %Multiple-trial matrix of spike vectors from MEA
time_vec;           %Time vector associated with spk_vec
cell_nums;          %Vector of [First_Cell Last_Cell] to train with

%Truncate spk_vec to contain only desired cells
spk_vec = spk_vec(:,:,cell_nums(1):cell_nums(2));

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%Determine observation made at each timestep
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

	%Create observation vector (only 1 observation allowed per step!)
	observ = zeros(size(spk_vec,1),size(spk_vec,2));
	
	%For each of the trials
	for i = 1:size(spk_vec,1),
        
        %For each of the relevant channels
        for j = 1:size(spk_vec,3),
        
            %Find spikes in channel i
            tmp = find(spk_vec(i,:,j));
            
            %Assign channel # to proper observation slot and
            %overwrite any previous channel in that timeslot
            %(only 1 allowed!!)
            observ(i,tmp) = j;
            
        end;
		
	end;
    
    %A zero observation ruins indexing below...shift all up by 1
    observ = observ + 1;
    
return;