c105 Gal4 test

on Wednesday, November 21st, 2012 8:34 | by

Currently I am testing C105-Gal4 line and two groups seem to fly so weak(8/24 so far). I will be testing them until I have reasonable number.

Alongside,  writing results and nearing completion on this chapter (thesis).But yet to prepare quality figures.

By the way, tag cloud is awesome !


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log sathish

on Wednesday, October 31st, 2012 7:14 | by

1. Very relevant nature news on two layers of behavioural variability


This article argues about the presence of variability during the onset of stimuli.

2. detailed the formulae behind the fft function and relevant mathematical equations.

3. Started writing introduction part of my thesis; finished writing material and methods section except  some cartoons.

May be I should start writing the results section alongside.

3. Third round of cross for self learning experiment with c105-c232 gal4 lines under way.


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c232,105yx UAS-TNT self learning

on Saturday, October 27th, 2012 4:44 | by

none of the group learn. Flies are quite weak. The two groups with UAS show a clear problem in operant behavior (low score during learning phases)…

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Torque distribution

on Wednesday, October 24th, 2012 2:17 | by

I had seen beautiful bell shaped distribution of torque (around 0) from the Heisenberg’s lab. We thus checked the data we have (the 6 minutes data we produced with the same flies for the torque meter and compensator. Data produced on the same day, or later (when sathish was mastering the preparation a bit better).
Here is the distributions:

Our distribution are close enough to the bell shape obtain by the Heisenberg’s group. The wing beat analyser seem to lead to different torque calculation, though.
PS: no difference seen in the frequency of spikes on the other hand.

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SMap before and after self-learning: no difference

on Friday, October 19th, 2012 6:33 | by

small but significantly different from 0 slope in the S-Map procedure, both before and after self-learning.

No difference in the slope while comparing before and after learning for each fly.

n>130 for each group.

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grip analysis on Buridan activity data

on Wednesday, October 17th, 2012 7:49 | by

Grip analysis on:

1. Interval between activities (temporal)

2.Difference between the subsequent activity (temporal) like  [X2-X1,X3-X2]

3.Difference between the subsequent distance travelled during the activity period (spatial)

4.Pysolo midline crossing data. Data sampling at 1 min interval. number of time fly crosses the virtual midline over the period of 60 s.

Bar: 1.c105;c232-wtb


3. Wtb-TNT


Inter-activity interval of buridan activity


2.Difference between the subsequent activity

Difference between the subsequent distance travelled during the activity period

pysolo midlines crossing



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oct 16 log

on Tuesday, October 16th, 2012 9:29 | by


1.New data acquired from Julien for pretest and memory test differentiation, seems 2 min is not sufficient enough. Scripts are running and soon will post all the figures.

2. Buridan data analysis codes compiled and running grip analysis on the inter activity interval (temporal ) data.

3.Prepared scripts to run the difference between individual activity like Xt2-Xt1,Xt3-Xt2.,,.. To see  the randomness on  generated matrix. Yet to get the plots.

4.working on the midline crossing data in order to cross insert into the gripburidan analysis.

Log end



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15 Oct Sathish’ log

on Monday, October 15th, 2012 6:43 | by


Since its lab notebook, I write in such a way that I could easily understand the tasks and rest could follow up. I will post figures with explanation and results whenever available.


1. working on the scripts to differentiate initial 2 min and last 2 min of self learning exp. to see the learning effect.

dataset suffix numbered in random fashion, unable to create handle to embed in struct field. Cell array conversion was possible but cant identify the fly specificities. Waiting to get updated version of data from Julien.

21 Hz corrected to 20 hz using interp1 method written and saved in home/character/Julien/

rest of code compiled and saved in same loc.

2. Buridan data – after analysis .csv file data is arranged on basis of activity and non activity.

wrote codes to extract each fly data out of .csv and place in .mat file to enable easy loop over. error due to presence of 2 activity log subsequently due to bursts inside activity matrix. troubled files isolated.

interval between each activity is considered as IAI .  Even number logic is used in script. data(m,n)*ones(M)

sprintf(‘sol%d’,’iteration’) leaves only string ,convert using str2num and call the metafile.Yet to compile.

3.Altered the Grip code such that grip does not try to convert the location of activity(spikes) to time domains.saved as griburidan.m only used with buridan and pysolo data.yet to compile to function


1.crosses under way for self learning with crowd control

2.c819 Gal4 arrived from Bloomington n quarantined.

Log end

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News from Neurofly

on Tuesday, September 11th, 2012 6:50 | by

A lot of things I learned at the neurofly. First my old friend Benjamin is doing a great postdoc in Bruno van Swinderen lab. It was great to see his data on isoflurane effects and the correlation between sleep disorder and sensitivity to anesthesia.

More related to our interests, I learned that Paul Tchénio has now a prototype to visualize neuronal activity in about half of the fly brain at a decent frequency. It may be interesting to get in touch with him again.

Andre Fiala is doing/has already done the TDC-Flp construct and is using his own UAS-stop-TRPA1 line to get a subset of octopaminergic neurons. Christine will contact him soon to have more information and maybe start a collaboration with him. The student was not at his/her poster when we went there, and we could not talk directly to him/her.

I nice talk by F. Mohammad (Singapore) showed that centrophobism can be associated with anxiety: the majority of treatments used with mices (for instance immobilisation in a pipet tip) also induce more (or less for some treatments) centrophobisms in flies. I told him about the CeTrAn, he said he will look at it. (his flies were in a squared box, with their wings untouched).

Jhl21 (receptor for JH) change of larval behavior at the  wandering stage (go slower and turn more): it acts at the NMJ to change the clustering of glutamate receptors. Similar thing may happen during the first hour of life of the fly, when they become phototactic ?

A nice poster from the Heisenberg’s lab show that flies do have a preferred 0 torque. Even when giving some closed loop drift, the histogram of torque suggest that the preference for the 0 torque is still there (non-uniform distribution around the +1 torque which stabilize the drift. It seems the distribution around the 0 torque is seen only if you have long enough data, I told them I would ask Satish to look at his distributions. This emphasizes why we need to be very careful in preparing the fly for our experiments…

I may have to look at the OK6 Gal4 line for motorneurons, and new RNAi lines seem to be available for PKC53e and FoxP…

I also talked to Flybase people, David was there. It seems the Buridan results should lead to 2 different entries: one linking each genotype to a dichotomic description of the phenotype (“mutant1” – “has larger”- “median_speed”) and one to the raw data and analysis. This will not be easy to automatize, but looks interesting.

I am probably forgetting a couple of things in addition to my discussion with Anette Schenk and her student Anna about FoxP..

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LED arena set up guide updated under lab resources

on Friday, January 27th, 2012 12:24 | by