Going over the optomotor responses with a fine comb revealed a bunch of flies where the algorithm wasn’t able to provide a proper fit for the OMR asymptote. Therefore, I will need more time to finish the data set. Here the current torque-learning PIs:

Clearly, the genetic controls learn while the flies with knocked-out aPKC in FoxP neurons fail to show a significant learning score. However, the OMR asymmetry effect in the genetic controls appears weaker than the one we discovered in WTB flies, as can be seen in the OMR traces after the self-learning:

Then again, at the .05 level, the asymmetry index is significant. Not the alpha level we commonly use, but also a lower N than we strive for (above is before training, below is after):

The transgenic experimental flies, in contrast, don’t seem to show much of an effect at all:

Just to have an example of yaw torque datasets and how they should avoid:

Finally have about half the number of flies needed. It looked like the flies that used the FoxP virgins didn’t fly as well as the other flies, so we dropped that branch and have stopped using them for the crosses. Pooling the FoxP>aPKC/CRISPR flies no increases the N in this group:

Compairison of the previous shown expression pattern (FoxP: red, D42: green) with the figures from Maniates-Selvin et. al. 2020.

Top row: dorsal view

Bottom row: dorsal view tilted to the right

Overlap of FoxP (red) with aPKC or 3 motor neuro lines (D42, C380, OK6) (green)

aPKC

D42

C380

OK6

Previous post: 6.8.21

By comparing the FoxP expression pattern with canidate neurons, VGlut-F-400630 could be an interaction point of FoxP-neurons with the MB.

Expression of aPKCdelta in FoxPiB positiv or motor neurons, the time of the experiment is half of the normal time.

Expression of aPKCdelta, in FoxPiB positiv neurons or motor neurons.

Cross of FoxPLexA (red) with diffrent GFP-Lines (green)

GMR65A06

GMR20H05

GMR11F02 (dose not overlap)

GMR52B10 not checked yet

aPKC (must be repeated)