new stimulation method and bitAcc transfer for stimulation weight update

Author: ulziiutas

bci_Process_FreeMode.m

@@ -64,6 +64,8 @@ function bci_Process_FreeMode()
         if isTrialEnd
             if bitAcc > 0
                 bitACCs = [bitACCs,bitAcc];
+                
+                vepstim.updateWeights(bitAcc);
             end
             % clear remote buffer
             if strcmp(settings.modelType,'remote')

example1.m

@@ -15,8 +15,8 @@
 settings = struct();
 settings.monitorResolution = [1920,1080];
 settings.monitorRefreshRate = 60;
-settings.stimulation = 'random';
-settings.layout = 'keyboard';
+settings.stimulation = 'optimal';
+settings.layout = 'qwertz';
 settings.windowSize = 'fullscreen';
 settings.startWait = 0;
 settings.trialTime = 10;
@@ -28,6 +28,13 @@
 max_correlation_coef = 0.6;
 seq_generator(sequence_number, bit_size, max_correlation_coef);
 
+settings.stimSettings.monitorRefreshRate = 60;
+settings.stimSettings.framesPerStimulus = 1;
+
+layout.numTargets = 55.0;
+stimulation = feval(['stimulation_' settings.stimulation],layout.numTargets,settings.stimSettings);
+stimulation.setTargetSequences();
+
 % initialize experiment object without TCP/IP server and debug enabled
 experiment = vep_experiment(screenNumber,'tcpip',false,'settings',settings,'debug',false);
 % Save screenshot

seq_generator.asv

@@ -1,13 +1,12 @@
 function seq_generator(sequence_number, bit_size, max_correlation_coef)
-    
-    if ~bit_size, bit_number = 20; end
-    if ~sequence_number, sequence_number = 20; end
-    if ~max_correlation_coef, max_correlation_coef = 0.8; end
+        
+    if ~bit_size, bit_number = 20; end                          %number of bits in one sequence
+    if ~sequence_number, sequence_number = 200; end             %number of sequences generated
+    if ~max_correlation_coef, max_correlation_coef = 0.8; end   %maximum correlation coefficient between seqs
 
 
     randomBinaryNumbers = transpose(randi([0, 1], sequence_number, bit_size));
-    R = corrcoef(randomBinaryNumbers);
-    
+    R = corrcoef(randomBinaryNumbers);    
     [row, column, ]  = find(triu(R,1) > max_correlation_coef);
 
     while ~isempty(row)
@@ -18,7 +17,8 @@ function seq_generator(sequence_number, bit_size, max_correlation_coef)
         R = corrcoef(randomBinaryNumbers);
         [row, column, ]  = find(triu(R,1) > max_correlation_coef);
     end       
-    randomBinaryNumbers = transpose(randomBinaryNumbers);    
-    csvwrite('random_seq_pool.csv', randomBinaryNumbers);
+    randomBinaryNumbers = transpose(randomBinaryNumbers);
 
+    csvwrite('random_seq_pool.csv', randomBinaryNumbers);
+    csvwrite('random_seq_weights.csv', cat(1,ones(1,sequence_number)./sequence_number,zeros(1,sequence_number)));  
 end

seq_generator.m

@@ -0,0 +1,71 @@
+classdef stimulation_optimal < stimulation
+%STIMULATION_PREDEFINED - stimulation using predefined sequences
+    
+    properties
+        randstream; %the random stream
+        sequences;  %sequence pool
+        weights;    %sequence weigths and occurances
+        targetseq;  %sequences assigned to targets
+    end
+    
+    methods
+        function this = stimulation_optimal(numTargets,varargin)
+        %STIMULATION_PREDEFINED - stimulation using predefined sequences
+        %   STIMULATION_PREDIFINED(numTargets,csvfile,seed)
+        %       CSVFILE - csv file with sequences
+        %       SEED - random seed used to randomly assign sequences to targets
+            this@stimulation(numTargets,varargin{:});
+            p = inputParser;
+            p.StructExpand = true;
+            p.KeepUnmatched = true;
+            addParameter(p,'sequencePool','random_seq_pool.csv',@(x) ischar(x) && exist(x, 'file') == 2);
+            addParameter(p,'sequenceWeights','random_seq_weights.csv',@(x) ischar(x) && exist(x, 'file') == 2);
+            addParameter(p,'randomseed',1,@(x) helper.isint(x) && length(x) == 1);
+            parse(p,varargin{:});
+            
+            this.randstream = RandStream('mt19937ar','Seed',p.Results.randomseed);
+            this.sequences = csvread(p.Results.sequencePool)';
+            this.weights = csvread(p.Results.sequenceWeights)';
+        end
+        
+        function setTargetSequences(this)
+        %SETTARGETSEQUENCES - assign random sequence of the sequence pool to each target
+            if size(this.sequences,2) > this.numTargets
+                % get random subset if pool has more sequences as targets
+%                 tmp_weights = this.weights(:,1)./size(this.weights,1);
+                tmp_weights = this.weights(:,1);
+                subset = zeros(1, this.numTargets);
+%                 subset = randsample( size(this.sequences,2), this.numTargets, false, this.weights(1,:)./size(this.weights,2));
+                for i = 1:this.numTargets
+                    subnet_new_idx = randsample(this.randstream, size(this.sequences,2), 1, true, tmp_weights);
+                    tmp_weights(subnet_new_idx) = 0;
+                    subset(i) = subnet_new_idx;
+                end
+                
+            elseif size(this.sequences,2) == this.numTargets
+                % if number of sequences equals number of targets
+                subset = 1:this.numTargets;
+            else
+                error('setTargetSequences: too few sequences in sequence pool');
+            end
+            this.weights(subset,2) = this.weights(subset, 2) + 1;
+            this.targetseq = this.sequences(:,subset);
+        end
+        
+        function updateWeights(this, bitAcc)
+        %UPDATEWEIGHTS - update weights using newest bit prediction
+        %accuracy
+            this.weights(:, 1) = this.weights(:, 1) .* bitAcc;
+        end
+        
+        function bits = next(this,lostBits)
+        %NEXT - returns the next bits of the sequence pool for each target
+            %call super method
+            next@stimulation(this,lostBits);
+            if mod(this.stimPos-1,size(this.sequences,1))+1 == 1, this.setTargetSequences(); end
+            bits = this.targetseq(mod(this.stimPos-1,size(this.sequences,1))+1,:);
+        end
+    end
+    
+end
+

vepstim/stimulations/stimulation_optimal.m

@@ -287,6 +287,12 @@ function endTrial(this)
             this.stimulation.endTrial();
         end
 
+        function updateWeights(this,bitAcc)
+        %updateWeights  - update weights in stimulation using
+        %updateWeights() function
+            this.stimulation.updateWeights(bitAcc);
+        end        
+        
         function setInfoText(this,text,duration)
         %SETINFOTEXT - shows a info text on the screen
         %   SETINFOTEXT(text,duration) - shows TEXT for DURATION seconds

vepstim/vep_experiment.m

@@ -162,6 +162,12 @@ function console(this,text)
             this.send('console',text);
         end
 
+        function updateWeights(this, bitAcc)
+        %UPDATEWEIGHTS - send bit prediction accuracy to vep_experiment and
+        %update weights
+            this.send('updateWeights', bitAcc);
+        end
+        
         function info(this,text,varargin)
         %INFO - shows a info text on the screen
         %   INFO(text) - show TEXT for 10 seconds