Self-learning of Rover/sitter from flight simulator

Long-term memroy from self-learning

Self-learning training/tests from transgeneic flies

After getting a new spectrometer, we confirmed that the first one was faulty. Comparison of old (1st and 3rd measures) and new (2nd and 4th) spectrometer. Now much more sensitive and the right spectrum measured for the green LED present in the spectrometer itself and for the light comming out of the light guide coupled with the red LED (whose spectrum does not seem to change after travelling through the light guide)

This is the first line I completed from the screen. What it is more important is that I found out that NorpA;UAS-Chrimson has orange eyes, when it should be red. So I think I will start to do the line again and meanwhile test the contaminated line to see what the phenotype looks like

We need a student to finish up experiments

Example of ON/OFF traces.  And then the wiggling was measured in both conditions (with and without light). It seems like they move more when they are in the light side. I also did measure the derivative with a tau=2 (in case the sampling is over the temporal frequency of fly behavior)

Comparing scores in both setups show some lines that match their scores and other lines that have opposite scores. This filters the ones that are context dependent to the ones that show a context independent reinforcement valence.

It seems that there is something more there. There were 5 batches of 3 flies per side reinforced. I put the intensity higher than ever before. I will try to get the maximum intensity for the next experiment and see what it looks like.

I have decreased the light intensity to around half of what it previously was. The result do not show any clear phenotype. The ‘logical PI’ looks kind of inverted because I actually have plotted it so that positive means light, negative means no light. A total of 30 flies were tested: some of them with right, other with left reinforcement