Switch-like and persistent memory formation in individual Drosophila larvae

  1. Amanda Lesar
  2. Javan Tahir
  3. Jason Wolk
  4. Marc Gershow  Is a corresponding author
  1. Department of Physics, New York University, United States
  2. Center for Neural Science, New York University, United States
  3. NYU Neuroscience Institute, New York University Langone Medical Center, United States
4 figures, 5 tables and 2 additional files

Figures

Figure 1 with 3 supplements
Y-maze assay to quantify innate and learned preference.

(A) Image sequence of a larva making two consecutive decisions in the Y-maze assay. White arrows indicate direction of air flow; red arrow shows direction of larva’s head. (B) Probability of …

Figure 1—source data 1

Spreadsheet containing each individual animal’s decisions in temporal sequence.

https://cdn.elifesciences.org/articles/70317/elife-70317-fig1-data1-v1.xlsx
Figure 1—video 1
Recording of a larva making 2 decisions within the Y-maze.

The direction of airflow and the larva’s decisions are noted. Video was recorded at 20 frames per second; the playback speed of 25 fps represents 1.25x real time.

Figure 1—video 2
Recording of a larva before training, showing a sequence of decisions made at the Y-maze juncture.

Recordings show 12.5 s before and 12.5 s after each decision. Video was recorded at 20 frames per second; the playback speed of 100 fps represents 5x real time.

Figure 1—video 3
Recording of a larva after training, showing a sequence of decisions made at the Y-maze juncture.

Recordings show 12.5 s before and 12.5 s after each decision. Video was recorded at 20 frames per second; the playback speed of 100 fps represents 5x real time.

Dose dependence of learning DANi1>CsChrimson were given varying cycles of paired training (as in Figure 1C).

(A) Probability of choosing CO2 containing channel before and after training, as a function of amount of training. *** p<0.001. (B) Histograms of individual larva preferences after training, grouped …

Figure 2—source data 1

Spreadsheet containing each individual animal’s decisions in temporal sequence.

https://cdn.elifesciences.org/articles/70317/elife-70317-fig2-data1-v1.xlsx
Figure 3 with 3 supplements
Memory extinction (A) Testing and training protocols for B,C.

Training + Extinction: larvae were exposed to 18 cycles of alternating CO2 and air following training. Habituation + Training: larvae were exposed to 18 cycles of alternating CO2 and air prior to …

Figure 3—source data 1

Spreadsheet containing each individual animal’s decisions in temporal sequence.

https://cdn.elifesciences.org/articles/70317/elife-70317-fig3-data1-v1.xlsx
Figure 3—figure supplement 1
After extinction, larvae can be trained again.

(A) Testing and training protocol for B,C. Larvae were trained with three cycles of paired training, followed by 18 extinction cycles of alternating CO2 and air with no reward presented. After …

Figure 3—figure supplement 2
Larvae population average response following training.

(A) Larvae population average response in the first ten minutes following training (0–10 min), compared to the latter fifty minutes of testing (10–60 min), for larvae that had been given 2, 5, or 20 …

Figure 3—figure supplement 3
Larvae given additional training between testing periods.

(A) Testing and training protocols for experiments in B. All larvae are tested in the Y-maze for one hour to determine initial preference. Larvae were then trained with 10 cycles of paired training, …

Memory retention overnight.

(A) Testing and training protocols. Except where indicated, larvae were tested, trained immediately after testing, tested again, then placed on food overnight and tested the following day. For …

Figure 4—source data 1

Spreadsheet containing each individual animal’s decisions in temporal sequence.

https://cdn.elifesciences.org/articles/70317/elife-70317-fig4-data1-v1.xlsx

Tables

Key resources table
Reagent type (species) or resourceDesignationSource or referenceIdentifiersAdditional information
Genetic reagent (D. melanogaster)w[1118]; P{y[+t7.7]w[+mC]=20XUAS-IVS-CsChrimson.mVenus}attP2 (w;;UAS-CsChrimson)Bloomington Stock CenterRRID:BDSC_55136
Genetic reagent (D. melanogaster)SS00864 split-Gal4 (DAN-i1-Gal4)Saumweber et al., 2018Gift of Marta Zlatic, Janelia Research Campus
Genetic reagent (D. melanogaster)w[*]; Gr63a[1]Bloomington Stock CenterRRID:BDSC_9941
Genetic reagent (D. melanogaster)w[1118]; P{y[+t7.7] w[+mC]=GMR58E02-GAL4}attP2 (GMR58E02-Gal4)Bloomington Stock CenterRRID:BDSC_41347
Genetic reagent (D. melanogaster)w;hs-dCREB2-b 17–2Yin et al., 1995FlyBase_ FBti0038019Gift of Jerry Chi-Ping Yin, University of Wisconsin, Madison
Genetic reagent (D. melanogaster)w[*]; P{w[+mW.hs]=GawB}ey[OK107]/In(4)ci[D], ci[D] pan[ciD] sv[spa-pol] (OK107-Gal4)Bloomington Stock CenterRRID:BDSC_854
Genetic reagent (D. melanogaster)w[*]; P{w[+mC]=UAS-Hsap\KCNJ2.EGFP}7 (UAS-kir2.1)Bloomington Stock CenterRRID:BDSC_6595
Genetic reagent (D. melanogaster)w[*]; P{w[+mC]=Gr21a-GAL4.C}133t52.1 (Gr21a-Gal4)Bloomington Stock CenterRRID:BDSC_23890
Software, algorithmlivetrackergithub.com/GershowLab/TrainingChamber (copy archived at URL swh:1:rev:e2a7ccc4e8d845e6cac59d3b2f344cca826c4727, Lesar, 2021)This work
Table 1
Crosses used to generate larvae for experiments throughout this work.

For strain information, see key resource table.

FigureDesignationFemale parentMale parent
1Gr63a1w;Gr63a1
1OK107>Kir2.1UAS-Kir2.1-GFPOK107-Gal4
1Gr21a>Kir2.1UAS-Kir2.1-GFPGr21a-Gal4
1-4DANi1>CsChrimsonw;;UAS-CsChrimsonSS00864
1Driver ctrlSS00864
1Effector ctrlw;;UAS-CsChrimson
158E02>CsChrimsonw;;UAS-CsChrimson58E02-Gal4
4hs-dcreb2-b;DANi1>CsChrimsonw;hs-dcreb2-b;UAS-CsChrimsonSS00864
Table 2
Data for experiments in Figure 1, Figure 2, Figure 3, and Figure 4.

# Larva: number of individual larvae tested for experiment type; # Approach Pre-Train: total number of times all larvae chose the channel containing air with CO2 prior to training; # Avoid …

ExperimentGenotype# Larva# Approach Pre-Train# Avoid Pre-Train# Approach Post-Train# Avoid Post-Train# Approach Next Day# Avoid Next Day
Figure 1B
Gr63a1Gr63a144831745----
DANi1> CsChrimson, ATR+DANi1> CsChrimson15917144978----
DANi1> CsChrimson, ATR-DANi1> CsChrimson16256614----
Figure 1D
PairedDANi1> CsChrimson645611760936868--
Offset AfterDANi1> CsChrimson20288757316305--
Reverse PairedDANi1> CsChrimson293151022154530--
Offset BeforeDANi1> CsChrimson19218512136315--
Paired, ATR-DANi1> CsChrimson16256614127307--
No TrainingDANi1> CsChrimson5057815994791295--
DAN w/o CO2DANi1> CsChrimson16260597161354--
Driver ctrlSS0086417110289158358--
Effector ctrlUAS-CsChrimson18214516114294--
58E02> CsChrimson58E02> CsChrimson21380912493501--
Figure 1EDANi1> CsChrimson
Forward Paired22181496350337--
Backwards Paired18181438124320--
Btw CO223272652165283--
Figure 1FDANi1> CsChrimson
6.5%19361568319290--
8%27256567295255--
15%19170368249233--
18%645611760936868--
Figure 2ADANi1> CsChrimson
0 Cycles5057815994791295--
1 Cycles35218606317495--
2 Cycles87840255210811292--
3 Cycles31310930686686--
4 Cycles32245712493511--
5 Cycles638632491975993--
10 Cycles14100287154144--
20 Cycles645611760936868--
Figure 3BDANi1> CsChrimson
2 Cycles, Training87840255210811292--
2 Cycles, Habituation + Training303851127422554--
2 Cycles, Training + Extinction30336946375793--
3 Cycles, Training30308924675679--
3 Cycles, Habituation + Training18222591260294--
3 Cycles, Training + Extinction26279695195416--
4 Cycles, Training30225659490502--
4 Cycles, Habituation + Training18239701372352--
4 Cycles, Training + Extinction273841074394475--
5 Cycles, Training638632491975993--
6 Cycles, Habituation + Training19266758367324--
6 Cycles, Training + Extinction18253687309317--
10 Cycles, Training14100287154144--
10 Cycles, Habituation + Training304061193607503--
10 Cycles, Training + Extinction304261180401386--
Figure 4BDANi1> CsChrimson
20x283801172509499459409
20x (Only Test Next Day)14224768--296250
5x294721427488480404461
2x425141537594693201548
2x (Only Test Next Day)22209696--213283
No Train20316889187544104337
RP 20x21282905121430109361
Ext Post-Train23181477--158365
Ext Pre-Test314171002--385429
Figure 4CDANi1> CsChrimson
M 20x (CXM+/ATR+)20110282252237237272
M 20x (CXM-/ATR+)17159419271236228235
S 20x (CXM+/ATR+)23191486--150316
S 20x (CXM-/ATR+)20197511--254264
M 10x (CXM+/ATR+)23136345--331344
M 10x (CXM-/ATR+)20175454--419375
Figure 4DDANi1> hs-dCREB2-b;CsChrimson
M 10x HS21175434392370253246
M 10x No HS22248656367353451490
S 10x HS2417242068156153339
S 10x No HS22294736212184335352
Table 3
p-Values for experiments in Figure 1, Figure 2, Figure 3, and Figure 4.

P-values for experiments were calculated: Bootstrap - p-values calculated as explained in Materials and methods; Fisher - p-values calculated using Fisher’s exact test; U-test - p-values calculated …

ExperimentGenotypeHierarchical BootstrapBootstrap Animal OnlyFisherU-test
Figure 1B
Gr63a1/DANi1> CsChrimson, ATR+<10−4<10−4<10−4<10−4
Gr63a1/DANi1> CsChrimson, ATR-<10−4<10−4<10−4<10−4
Figure 1D
PairedDANi1> CsChrimson<10−4<10−4<10−4<10−4
Offset AfterDANi1> CsChrimson<10−4<10−4<10−4<10−4
Reverse PairedDANi1> CsChrimson0.34290.26890.61660.9379
Offset BeforeDANi1> CsChrimson0.44790.43730.94790.9770
Paired, ATR-DANi1> CsChrimson0.47620.43151.0000.2658
No TrainingDANi1> CsChrimson0.40660.36640.77260.9835
DAN w/o CO2DANi1> CsChrimson0.39350.31020.71730.4852
Driver ctrlSS008640.31060.03130.34110.3977
Effector ctrlUAS-CsChrimson0.33830.23610.63360.8366
58E02> CsChrimson58E02> CsChrimson<10−4<10−4<10−4<10−4
Figure 1CDANi1> CsChrimson
Forward Paired<10−4<10−4<10−4<10−4
Backwards Paired0,33680.1630.68010.1939
Btw CO20.01070.00010.0065430.0003257
Figure 1DDANi1> CsChrimson
6.5%<10−4<10−4<10−4<10−4
8%<10−4<10−4<10−4<10−4
15%<10−4<10−4<10−4<10−4
18%<10−4<10−4<10−4<10−4
Figure 2ADANi1> CsChrimson
0 Cycles0.41320.36470.77260.9835
1 Cycles0.0003<10−4<10−40.0591
2 Cycles<10−4<10−4<10−4<10−4
3 Cycles<10−4<10−4<10−4<10−4
4 Cycles<10−4<10−4<10−4<10−4
5 Cycles<10−4<10−4<10−4<10−4
10 Cycles<10−4<10−4<10−4<10−4
20 Cycles<10−4<10−4<10−4<10−4
Figure 3BDANi1> CsChrimson
2 Cycles, Training<10−4<10−4<10−4<10−4
2 Cycles, Habituation + Training<10−4<10−4<10−4<10−4
2 Cycles, Training + Extinction0.01170.00200.0013390.04743
3 Cycles, Training<10−4<10−4<10−4<10−4
3 Cycles, Habituation + Training<10−4<10−40.0007459<10−4
3 Cycles, Training + Extinction0.11330.01760.17630.03069
4 Cycles, Training<10−4<10−4<10−4<10−4
4 Cycles, Habituation + Training<10−4<10−4<10−4<10−4
4 Cycles, Training + Extinction<10−4<10−4<10−4<10−4
5 Cycles, Training<10−4<10−4<10−4<10−4
6 Cycles, Habituation + Training<10−4<10−4<10−4<10−4
6 Cycles, Training + Extinction<10−4<10−4<10−4<10−4
10 Cycles, Training<10−4<10−4<10−4<10−4
10 Cycles, Habituation + Training<10−4<10−4<10−4<10−4
10 Cycles, Training + Extinction<10−4<10−4<10−4<10−4
Figure 4BDANi1> CsChrimson
20x Pre-Test/Post-Test<10−4<10−4<10−4<10−4
20x Pre-Test/Next Day<10−4<10−4<10−4<10−4
20x (Only Test Next Day) Pre-Test/Next Day<10−4<10−4<10−4<10−4
5x Pre-Test/Post-Test<10−4<10−4<10−4<10−4
5x Pre-Test/Next Day<10−4<10−4<10−4<10−4
2x Pre-Test/Post-Test<10−4<10−4<10−4<10−4
2x Pre-Test/Next Day0.20860.05010.35240.07216
2x (Only Test Next Day) Pre-Test/Next Day<10−4<10−4<10−4<10−4
No Train Pre-Test/Post-Test0.40350.33190.78930.2003
No Train Pre-Test/Next Day0.15830.05300.30710.8884
RP 20x Pre-Test/Post-Test0.26770.15070.42760.7396
RP 20x Pre-Test/Next Day0.42050.34810.84740.3765
Ext Post-Train Pre-Test/Next Day0.18010.01460.33150.01336
Ext Pre-Test Pre-Test/Next Day<10−4<10−4<10−4<10−4
Figure 4CDANi1> CsChrimson
M 20x (CXM+/ATR+) Pre-Test/Post-Test<10−4<10−4<10−4<10−4
M 20x (CXM+/ATR+) Pre-Test/Next Day<10−4<10−4<10−4<10−4
M 20x (CXM-/ATR+) Pre-Test/Post-Test<10−4<10−4<10−4<10−4
M 20x (CXM-/ATR+) Pre-Test/Next Day<10−4<10−4<10−4<10−4
S 10x (CXM+/ATR+) Pre-Test/Next Day0.10990.0140.16710.02985
S 10x (CXM-/ATR+) Pre-Test/Next Day<10−4<10−4<10−4<10−4
M 10x (CXM+/ATR+) Pre-Test/Next Day<10−4<10−4<10−4<10−4
M 10x (CXM-/ATR+) Pre-Test/Next Day<10−4<10−4<10−4<10−4
Figure 4DDANi1> hs-dCREB2-b;CsChrimson
M 10x, HS Pre-Test/Post-Test<10−4<10−4<10−4<10−4
M 10x, HS Pre-Test/Next Day<10−4<10−4<10−4<10−4
M 10x, No HS Pre-Test/Post-Test<10−4<10−4<10−4<10−4
M 10x, No HS Pre-Test/Next Day<10−4<10−4<10−4<10−4
S 10x, HS Pre-Test/Post-Test0.38040.28300.73100.2750
S 10x, HS Pre-Test/Next Day0.26450.088600.46500.3802
S 10x, No HS Pre-Test/Post-Test<10−4<10−4<10−4<10−4
S 10x, No HS Pre-Test/Next Day<10−4<10−4<10−4<10−4
Table 4
Model fits to data in Figure 2.

Shifting Mean and σ~, shifting fraction, and exponential fraction models are presented in Figure 2. Model name: name of the model. Formula: expression for the probability of the data given the model …

Model nameFormula# paramsΔlog(P)ΔAICΔBIC
Shifting Mean (fixed σ~)Pnc(0,1,2,3,4,5,10,20)j𝒩(p(nc,j),μ(nc),σ~μ(nc)*(1-μ(nc))n(nc,j))9−42.784.86104.45
Shifting Mean and σ
(Graded learning)
Pnc(0,1,2,3,4,5,10,20)j𝒩(p(nc,j),μ(nc),σ(nc)n(nc,j))16−12.939.386.3
Shifting Fraction
(Quantized learning)
Pnc(0,1,2,3,4,5,10,20)jfu(nc)𝒩(p(nc,j),μu,σ~μu*(1-μu)n(nc,j))+
(1-fu(nc))𝒩(p(nc,j),μt,σ~μt*(1-μt)n(nc,j))
11−3.9311.338.7
Shifting Fraction
(3 clusters)
Pnc(0,1,2,3,4,5,10,20)jf1(nc)𝒩(p(nc,j),μ1,σ~μ1*(1-μ1)n(nc,j))+
f2(nc)𝒩(p(nc,j),μ2,σ~μ2(1μ2)n(nc,j))+
(1-f1(nc)-f2(nc))𝒩(p(nc,j),μ3,σ~μ3*(1-μ3)n(nc,j))
20021.484.1
Exponential Fraction
(All-or-none)
Pnc(0,1,2,3,4,5,10,20)jλnc𝒩(p(nc,j),μu,σ~μu*(1-μu)n(nc,j))+
(1-λnc)𝒩(p(nc,j),μt,σ~μt*(1-μt)n(nc,j))
4−5.300
SymbolDefinitionSymbolDefinition
ncnumber of training cyclesp(nc,j)fraction of times jth larva chose CO2 after nc cycles
μ(nc)mean probability of choosing CO2 after nc training cyclesn(nc,j)# choices made by jth larva after nc training cycles
σ~global adjustment to binomial standard deviationσ(nc)training dependent standard deviation
μuprobability of larva in untrained group choosing CO2μtprobability of larva in trained group choosing CO2
fu(nc)fraction of larvae in untrained group after nc cyclesμ1,μ2,μ3probability of larva in group 1,2,3 choosing CO2
f1(nc),f2(nc)fraction of larvae in groups 1,2 after nc cyclesλfraction of larvae not trained after one cycle
𝒩(x,μ,σ)normal cdf: 12πσ2e-(x-μ)22σ2Δlog(P)relative log probability of data given model
AICAikake Information Criterion: 2k-2log(P), k = # paramsΔAICAIC - lowest AIC
BICBayes Information Criterion: klog(nA)-2log(P), k = # params, nA = # animalsΔBICBIC - lowest BIC

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