function fit = myact( params )

% Split vector of parameters into different components
  dc 	        = params(1);
  di	        = params(2);
  d	        = params(3);
  nr	        = params(4);
  t           = params(5);
  threshold   = params(6);
  beta 	     = params(7);
  rehearsals  = params(8);
  interval    = params(9);
  
  rehearsals = round(rehearsals);
  
  % Prevent division by zero
  if (d == 1.0) 
    d = 0.99999;
  end 
  if (dc == 0) 
    dc = 0.001;
  end

  % INITIALIZE
  fit = 0;
  predict=zeros(1,11);

  timeInSecPerPresentation = interval;
  
  % DATA
  global VERBOSE;
  global OBS;
  global DIFF;
  global OUTFILE;
  
  obs = OBS;
  diff = DIFF;

  lvec = length(diff);

  saliency = (diff / dc) - di;
  
  global EXTBL;
  
  %if (length(EXTBL) == 1) 
     EXTBL = normalBaseLevel((1:nr)*(t/nr),d,((1:lvec)-1)*timeInSecPerPresentation);
  	  EXTBL = EXTBL + beta;   
  %end
  externalBaseLevels = EXTBL;

  % GO THROUGH ALL OF THE 10 CONDITIONS
  if (VERBOSE)
    fprintf(OUTFILE,'Dis Salience ( priorOdd +   expOdd )= combAct  Total  Retr? Obs MisScore\n\n');
 end
 
 %priorBaselevel = optimizedBaseLevel(nr,t,d) + beta;
  
  timeSinceStart = 0;
  
  for i = 1:lvec
     
    prevRetrievals = sum(predict(1:i));
    
    if (prevRetrievals > 0)
       prevRef = repmat(setdiff(((i-(1:(i-1)))*timeInSecPerPresentation) .* (predict(1:(i-1))),0),1,rehearsals);
       expBaselevel = normalBaseLevel(prevRef, d, 0) + beta;
       total = log(exp(externalBaseLevels(i)) + exp(expBaselevel)) + saliency(i); 	   
    else
       total = externalBaseLevels(i) + saliency(i);
       expBaselevel = -9;
    end
   
    retrieved = (total >= threshold);

    if (retrieved | (timeSinceStart > 0)) 
      timeSinceStart = timeSinceStart + timeInSecPerPresentation;
    end
    
    if (retrieved ~= obs(i))
       % functie straft fouten aan het einde zwaarder dan aan het begin, 
       % en gebruikt daarnaast een (expected-observed)^2 maat voor 
       % mismatch berekening.
       mismatch = (0.5*(lvec-i)) + ((threshold - total))^2;
    else
      mismatch = 0;
    end

    predict(i) = retrieved;
    fit = fit + mismatch;
    
    if (VERBOSE)
       if (expBaselevel ~= -9) 
          eBL = exp(expBaselevel);
       else
          eBL = 0;
       end
       fprintf(OUTFILE,'%3d %8.5f ( %8.5f + %8.4f )= %8.5f %7.4f %5d %3d %8.5f\n', ...
       diff(i), saliency(i), exp(externalBaseLevels(i)), eBL, ...
       log(exp(externalBaseLevels(i))+eBL), total, retrieved, obs(i), mismatch);  
    end
  end

  if (VERBOSE)
    fprintf(OUTFILE,'\n\nTotal mismatch: %f\n\n',fit);
    
    fprintf(OUTFILE,'Parameters:\n\n');
    fprintf(OUTFILE,'dc:         %12.6f\n',dc);
    fprintf(OUTFILE,'di:         %12.6f\n',di);
    fprintf(OUTFILE,'d:          %12.6f\n',d);
    fprintf(OUTFILE,'nr:         %12.6f\n',nr);
    fprintf(OUTFILE,'t:          %12.6f\n',t);
    fprintf(OUTFILE,'threshold:  %12.6f\n',threshold);
    fprintf(OUTFILE,'beta:       %12.6f\n',beta);
    fprintf(OUTFILE,'rehearsals: %12.6f\n',rehearsals);
    fprintf(OUTFILE,'interval:   %12.6f\n',interval);
  end