Dopaminergic clusters are differently targeted by the different Gal4s. Some of the express faintly, others stronger. Here I try to see if the dose-response curve (or expression-PI curve) seems to be linear or not. Here I put two examples from the 17 clusters, where the first two seem to have nonlinear curves, with and optimal expression level, and the last two seem to have a linear response curve.

This will be important for the modelling in order to decide to make a linear/nonlinear model. Down below I show the results from a linear model and it´s statistics. From Aso et al. 2012, one could see that activating the lines with TrpA1 shows a linear response curve. But in this case it does not necessarily seem to be the case. Therefore, light intensities might have an effect, as well as the expression level, and conclusion needs to be taken carefully.

In addition it is difficult to calculate this for all the clusters with just one single light intensity test, because not all clusters are expressed in several Gal4s to different level, so that we can estimate from there. So for the interesting lines we might need to make several experiments at different intensities, and see the dose response curve.

The G4s I have used for the modelling are the ones shown here.

This is just to show that I am trying to find  a new ratio so that all graphs have from -1 to +1 ranges. That is why now the difference in occupancy time is divided by the total time. The same with the speed. Because speed differences are so subtle, the Y axis scale has to be lower

the first graph shows Bar plot of Mean and standard deviation of PIs for Genetic control (n=9) and Positive control (n=5).
The second graph shows weighted mean and weighted standard deviation of the same.

Weighted mean is calculated by multiplying the weights (total number of flies in that experiment/total number of flies in all the experiments) with the PI for that experiment, and taking the sum thereafter for all the experiments.

Self-learning of Rover/sitter from flight simulator

Long-term memroy from self-learning

Self-learning training/tests from transgeneic flies

NorpA; Chrimson/Gr28 (N=12, ATR)

NorpA; Chrimson/Gr28 (N012, No ATR)

NorpA;Chrimson/+ (N=11, ATR)

TrpA1 self learning test, N= 47

TrpA1 long term memory, N= 39

Wtb long term memory (previous on fly simulator), N= 16

N= 31

30 from each lines, no statistially difference among them. I will keeping testing on flight simultor before transgenic flies hatch.