update on self learning&longterm memory

on Monday, April 3rd, 2017 1:44 | by

longterm test:

1 from sitter,  8 from wtb, 3 from rover (total N = 12)

mean(test): 0.248          SD(test): 0.7

Longterm test Control

1 from sitter, 2 from rover (N=3)

mean(test):-0.386           SD(test):0.79

Two Sample:

Based on 50%(20%) of statistical power, the minimum sample size is 7 (17)for both group.

One Sample (assume control group has the average of PI is 0):

Based on 50% (20%) of statistical power, the minimum sample size is 22 (49)for both group.

https://www.dssresearch.com/KnowledgeCenter/toolkitcalculators/samplesizecalculators.aspx

 

Self learning test:

sitter N=5

wtb N= 4

 

 

 

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PKG rover update

on Monday, March 6th, 2017 10:17 | by

There is the result of 20 measurements on PKG rover.

pretest:-0.45

train1:0.56

train2:0.71

test1:0.47

train3:0.83

train4:0.87

test2:0.39

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Laser power/angle adjustment

on Monday, February 20th, 2017 10:15 | by

After camera and punish laser adjusted, flies showed a high avoidence in the trail. Especially, when the fly was hit by punish laser in the first time of each training block. Unfortunately, there was a huge drift in the last trace after adjustment, but it shows a good avoidence in each training block.

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PKG rover from last week

on Monday, February 13th, 2017 9:37 | by

Generally, PKG drosophila were flying much better when they hatched from normal temperature. There is the result from 10 PKG drosophila.

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Update on PKG sitter/rover PI

on Monday, February 6th, 2017 9:41 | by

There is a short update on summerized previous PI. Still, PKG transgenic drosophila is hardly testable, and the results seems not so promising. I’m going to focus on testing WTB this week, to compare the difference of PI between WTB and PKG

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First glance at PKG effect on self-learning and long term memory

on Monday, January 23rd, 2017 2:51 | by

There are two strains of drosophila prepared: PKG-rover(R), PKG-sitter(S). Each strain is supposed to test PI in 3 phases: no training, training, long term+no training. The following data show PKG-sitter flying trace and PI. Since there weren’t many flies in the first week, and they pause flying very often in the experiment, so there is only one single fly was tested successfully. Since the torque meter drifted on the next day, the long term result is quite debatable.

 

 

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Wild Type Drosophila memory ability test

on Monday, November 7th, 2016 11:07 | by

There were 6 more flies were tested, and PI from two tests are focused this time.  The inconstancy in PI (#23, #33)  from test1 and test2 indicates the learning or memory function in wild type during test.

  • PI from all 6 groups

wtb33_bar

 

  • fly trace(#33)

wtb-33

  • test1 (#33)

wtb33-test1

  • test2(#33)

wtb33-test2

 

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Wild type Drosophila flying trace

on Monday, October 31st, 2016 12:03 | by

 

Wild Type Drosophila were used for single fly trace testing. The basic ideal is to record the spontaneous behavior (flying trace) after punishment training by heat. The followings are 3 subjects were test with performance index (PI).

  •  wtb_08 (right punishment).
pretest(PI1) training1(PI2) training2(PI3) test1(PI4) training3(PI5) traing4PI(PI6) test2/3(PI7)
10000 10000 10000 9984 9117 8113 10000

wtb_08

  • wtb_10 (left punishment).
pretest training1 training2 test1 training3 traing4 test2/3
1121 2583 2397 -4310 9433 9458 9960

wtb_10

  • wtb_14 (left punishment).
pretest training1 training2 test1 training3 traing4 test2/3
-832 -9510 -8339 -9903 -813 -574 -9887

wtb_14

  • Average.
pretest1/2 training1 training2 test1 training3 traing4 test2/3
all 3429 1024 1352 -1409 5912 5665 3357
left punishment 144 -3463 -2971 -7106 4310 4442 36

PS: From Julien’s paper, he demonstrates that there are 7 blocks were included in PI ( one pretest:PI1; four training test: PI2, PI3, PI5,PI6; two memory test: PI4,PI7)

 

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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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