These are chat archives for thunder-project/thunder
X1for the stimulus and
X2for the directions, then I do circular tuning model on the
betas. I am trying this code, but the spread I get back is zero for all my neurons. Am I doing something wrong or are my neurons not direction sensitive ?
L = len(data.index) X1= np.zeros((1, L),dtype=np.int) X1[0,0:30] = 1 X2= np.zeros((2, L),dtype=np.int) X2[0,0:15] = 1 X2[1,15:30] = 1 bilinreg = RegressionModel.load((X1,X2), "bilinear") results = bilinreg.fit(data) circ = np.array([-pi, pi]) model = TuningModel.load(circ , "circular") params = model.fit(results.select('betas')) plt.plot(params.select('spread').values().collect())
circularversion of the
TuningModel, you need more than just two directions. The tuning model will try to fit a function of response vs angle, and just having forward/backward won't be enough to get a meaningful fit there.