SMAP results

on Monday, October 9th, 2017 2:34 | by

These are the results of the SMAP for the TNTxWTB. I also have done a few for the c105;;c232xWTB but there is not much to say. I would say that the cleanest lines show a bigger slope, but prone to subjectiveness.

In addition, I have done some animations of the attractors that I have posted on slack because of size.

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Attractors for c105;;c232>TNT

on Monday, October 2nd, 2017 5:35 | by


This is what I showed about one fly from this line showing the attractor.

This graph is what I forgot to show in the lab meeting. There are the 6 best traces from this same line. All of them selected ad hoc subjectively. The three best of them to my eyes are exactly the three above in the graph (v8-this one is the one shown in the picture with the attractors-,v4,v2). What does this means? the ones with better traces (subjectively) have higher offset in the phi, this means that they are more predictable overall (maybe because more resolution?). In addition, they show higher slopes which means more nonlinearity.


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Measuring Wingstroke Amplitude with Strokelitude (V)

on Monday, December 14th, 2015 2:42 | by

For a further data analysis, we should have a minimum number of samples. During the last week, I have been measuring the wingstroke amplitude of the flies, to get at least 10 samples of each one(two controls and the experimental line). Here three examples of the different lines:

Males WTB x C105;;C232 (control)


Males UAS-TNT-E x C105;;C232


Males UAS-TNT-E x WTB (control)




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Measuring Wingstroke Amplitude with Strokelitude (IV)

on Monday, December 7th, 2015 2:56 | by

After getting good results in the measurement of the wingstroke, and solving problems with the sampling intervals (image below). I have started to measure flies for the experiments.

The time between samples was different depending on the background programs running on the background:

Figure 1


More differences in time within samples when more programs are running at the same time as strokelitude (3nd 1/3 of the plot), when just the display of the camera is running( 1st 1/3 of the plot), and everything shut down(2nd 1/3 of the plot).

The differences among sampling intervals was bigger but with an adjustment of the data, Christian Rohrsen managed to changed. The time between two samples could arise until 1.7 seconds and with the correlation, the time is not bigger than 0.05 seconds.

The strains of flies used fore the experiments are:

UAS-TNT-E, that express the tetanus toxin in the neural cells, using GAL4 system. Being Used as a control.

c105;;c232, that contains a promotor region to express the toxin. Being used as a control.

And the cross between both to have the expression of the tetanus toxin.

Some data from the control flies (UAS-TNT-E):


And some data of the spikes:






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Interpolations and Spike analysis

rawplot markeddeleted splineThis is just a proof of concept how useful the interpolation is for this purpose: and I would say it´s almost useless. If I delete from the raw data (1st graph) some pieces (2nd graph), and I make a spline interpolation (3rd graph) it doesn´t match that well. Linear interpolation was done in previous weeks with not much of a success. Anyway, the result of a linear interpolation can be imagined by eye just by joinning the two ends with a straight line, and this doesn´t occur in the fly behavior as we can see in the raw data (1st graph).

Ute spike1openloop1 spikesannotatedints spikesdatavsmyspikesThere could be two posibilities for spike detection: one is the one from Ute and the other one is the one from Maye. It seems to me that the one from Maye is more precise. I have run the script but I do not get so many spike detections as he gets. I did try several thresholds for spike detection and doesn´t change very much. So I have to work more on it to see what is really the important factor for a proper spike detection

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