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Differential mechanisms underlie trace and delay conditioning in Drosophila

Nature volume 603, pages 302–308 (2022)Cite this article

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A Publisher Correction to this article was published on 22 March 2022

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Abstract

Two forms of associative learning—delay conditioning and trace conditioning—have been widely investigated in humans and higher-order mammals1. In delay conditioning, an unconditioned stimulus (for example, an electric shock) is introduced in the final moments of a conditioned stimulus (for example, a tone), with both ending at the same time. In trace conditioning, a ‘trace’ interval separates the conditioned stimulus and the unconditioned stimulus. Trace conditioning therefore relies on maintaining a neural representation of the conditioned stimulus after its termination (hence making distraction possible2), to learn the conditioned stimulus–unconditioned stimulus contingency3; this makes it more cognitively demanding than delay conditioning4. Here, by combining virtual-reality behaviour with neurogenetic manipulations and in vivo two-photon brain imaging, we show that visual trace conditioning and delay conditioning in Drosophila mobilize R2 and R4m ring neurons in the ellipsoid body. In trace conditioning, calcium transients during the trace interval show increased oscillations and slower declines over repeated training, and both of these effects are sensitive to distractions. Dopaminergic activity accompanies signal persistence in ring neurons, and this is decreased by distractions solely during trace conditioning. Finally, dopamine D1-like and D2-like receptor signalling in ring neurons have different roles in delay and trace conditioning; dopamine D1-like receptor 1 mediates both forms of conditioning, whereas the dopamine D2-like receptor is involved exclusively in sustaining ring neuron activity during the trace interval of trace conditioning. These observations are similar to those previously reported in mammals during arousal5, prefrontal activation6 and high-level cognitive learning7,8.

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Fig. 1: Drosophila visual trace conditioning, but not delay conditioning, is distraction-sensitive, and both require ellipsoid body R2 and R4m ring neurons.
Fig. 2: Ellipsoid body ring neuron ratiometric calcium imaging during trace conditioning reveals an increasing, distraction-sensitive oscillatory component and persistence.
Fig. 3: Ellipsoid-body-projecting dopaminergic neurons are required for trace and delay conditioning, selectively active during the trace interval and negatively affected by distractions in trace conditioning.
Fig. 4: Dopamine receptor signalling in the ellipsoid body ring during delay and trace conditioning.

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Data availability

Datasets generated as part of this study are available from the corresponding author on reasonable request. Source data are provided with this paper.

Code availability

The source code for the different assays developed is available for download from the public repository at https://github.com/dgrover/flyCAVE.

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References

  1. Clark, R. E. & Squire, L. R. Classical conditioning and brain systems: the role of awareness. Science 280, 77–81 (1998).

    Article  ADS  CAS  PubMed  Google Scholar 

  2. Han, C. J. et al. Trace but not delay fear conditioning requires attention and the anterior cingulate cortex. Proc. Natl Acad. Sci. USA 100, 13087–13092 (2003).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  3. Garner, A. R. et al. Generation of a synthetic memory trace. Science 335, 1513–1516 (2012).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  4. Raybuck, J. D. & Lattal, K. M. Bridging the interval: theory and neurobiology of trace conditioning. Behav. Processes 101, 103–111 (2014).

    Article  PubMed  Google Scholar 

  5. Colgin, L. L. Mechanisms and functions of theta rhythms. Annu. Rev. Neurosci. 36, 295–312 (2013).

    Article  CAS  PubMed  Google Scholar 

  6. Koechlin, E. Prefrontal executive function and adaptive behavior in complex environments. Curr. Opin. Neurobiol. 37, 1–6 (2016).

    Article  CAS  PubMed  Google Scholar 

  7. Nichols, M. J. & Newsome, W. T. The neurobiology of cognition. Nature 402, C35–C38 (1999).

    Article  CAS  PubMed  Google Scholar 

  8. Milner, B., Squire, L. R. & Kandel, E. R. Cognitive neuroscience and the study of memory. Neuron 20, 445–468 (1998).

    Article  CAS  PubMed  Google Scholar 

  9. Knight, D. C., Cheng, D. T., Smith, C. N., Stein, E. A. & Helmstetter, F. J. Neural substrates mediating human delay and trace fear conditioning. J. Neurosci. 24, 218–228 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Kronforst-Collins, M. A. & Disterhoft, J. F. Lesions of the caudal area of rabbit medial prefrontal cortex impair trace eyeblink conditioning. Neurobiol. Learn. Mem. 69, 147–162 (1998).

    Article  CAS  PubMed  Google Scholar 

  11. Connor, D. A. & Gould, T. J. The role of working memory and declarative memory in trace conditioning. Neurobiol. Learn. Mem. 134, 193–209 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  12. LeDoux, J. E. & Lau, H. Seeing consciousness through the lens of memory. Curr. Biol. 30, R1018–R1022 (2020).

    Article  CAS  PubMed  Google Scholar 

  13. Venken, K. J. T., Simpson, J. H. & Bellen, H. J. Genetic manipulation of genes and cells in the nervous system of the fruit fly. Neuron 72, 202–230 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Haberkern, H. & Jayaraman, V. Studying small brains to understand the building blocks of cognition. Curr. Opin. Neurobiol. 37, 59–65 (2016).

    Article  CAS  PubMed  Google Scholar 

  15. Tully, T. & Quinn, W. G. Classical conditioning and retention in normal and mutant Drosophila melanogaster. J. Comp. Physiol. A 157, 263–277 (1985).

    Article  CAS  PubMed  Google Scholar 

  16. Owald, D. & Waddell, S. Olfactory learning skews mushroom body output pathways to steer behavioral choice in Drosophila. Curr. Opin. Neurobiol. 35, 178–184 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Busto, G. U., Cervantes-Sandoval, I. & Davis, R. L. Olfactory learning in Drosophila. Physiology 25, 338–346 (2010).

    Article  CAS  PubMed  Google Scholar 

  18. Galili, D. S., Lüdke, A., Galizia, C. G., Szyszka, P. & Tanimoto, H. Olfactory trace conditioning in Drosophila. J. Neurosci. 31, 7240–7248 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Shuai, Y., Hu, Y., Qin, H., Campbell, R. A. A. & Zhong, Y. Distinct molecular underpinnings of Drosophila olfactory trace conditioning. Proc. Natl Acad. Sci. USA 108, 20201–20206 (2011).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  20. Dill, M., Wolf, R. & Heisenberg, M. Visual pattern recognition in Drosophila involves retinotopic matching. Nature 365, 751–753 (1993).

    Article  ADS  CAS  PubMed  Google Scholar 

  21. Kamikouchi, A. et al. The neural basis of Drosophila gravity-sensing and hearing. Nature 458, 165–171 (2009).

    Article  ADS  CAS  PubMed  Google Scholar 

  22. Pacheco, D. A., Thiberge, S. Y., Pnevmatikakis, E. & Murthy, M. Auditory activity is diverse and widespread throughout the central brain of Drosophila. Nat. Neurosci. 24, 93–104 (2021).

    Article  CAS  PubMed  Google Scholar 

  23. Neuser, K., Triphan, T., Mronz, M., Poeck, B. & Strauss, R. Analysis of a spatial orientation memory in Drosophila. Nature 453, 1244–1247 (2008).

    Article  ADS  CAS  PubMed  Google Scholar 

  24. Ofstad, T. A., Zuker, C. S. & Reiser, M. B. Visual place learning in Drosophila melanogaster. Nature 474, 204–209 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Liu, G. et al. Distinct memory traces for two visual features in the Drosophila brain. Nature 439, 551–556 (2006).

    Article  ADS  CAS  PubMed  Google Scholar 

  26. Vogt, K. et al. Shared mushroom body circuits underlie visual and olfactory memories in Drosophila. eLife 3, e02395 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  27. Zhang, K., Guo, J. Z., Peng, Y., Xi, W. & Guo, A. Dopamine–mushroom body circuit regulates saliency-based decision-making in Drosophila. Science 316, 1901–1904 (2007).

    Article  ADS  CAS  PubMed  Google Scholar 

  28. Aso, Y. et al. Mushroom body output neurons encode valence and guide memory-based action selection in Drosophila. eLife 3, e04580 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  29. Cognigni, P., Felsenberg, J. & Waddell, S. Do the right thing: neural network mechanisms of memory formation, expression and update in Drosophila. Curr. Opin. Neurobiol. 49, 51–58 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Srinivasan, S., Greenspan, R. J., Stevens, C. F. & Grover, D. Deep(er) learning. J. Neurosci. 38, 7365–7374 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Mao, Z. & Davis, R. L. Eight different types of dopaminergic neurons innervate the Drosophila mushroom body neuropil: anatomical and physiological heterogeneity. Front. Neural Circuits 3, 5 (2009).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  32. Liang, X. et al. Morning and evening circadian pacemakers independently drive premotor centers via a specific dopamine relay. Neuron 102, 843–857 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Lebestky, T. et al. Two different forms of arousal in Drosophila are oppositely regulated by the dopamine D1 receptor ortholog DopR via distinct neural circuits. Neuron 64, 522–536 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Aso, Y. et al. The neuronal architecture of the mushroom body provides a logic for associative learning. eLife 3, e04577 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  35. Knudsen, E. I. Fundamental components of attention. Annu. Rev. Neurosci. 30, 57–78 (2007).

    Article  CAS  PubMed  Google Scholar 

  36. Carter, R. M. K., Hofstötter, C., Tsuchiya, N. & Koch, C. Working memory and fear conditioning. Proc. Natl Acad. Sci. USA. 100, 1399–1404 (2003).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  37. Kim, R. & Sejnowski, T. J. Strong inhibitory signaling underlies stable temporal dynamics and working memory in spiking neural networks. Nat. Neurosci. 24, 129–139 (2021).

    Article  CAS  PubMed  Google Scholar 

  38. Renn, S. C. P. et al. Genetic analysis of the Drosophila ellipsoid body neuropil: organization and development of the central complex. J. Neurobiol. 41, 189–207 (1999).

    Article  CAS  PubMed  Google Scholar 

  39. Hollerman, J. R. & Schultz, W. Dopamine neurons report an error in the temporal prediction of reward during learning. Nat. Neurosci. 1, 304–309 (1998).

    Article  CAS  PubMed  Google Scholar 

  40. Sutton, R. S. & Barto, A. G. Toward a modern theory of adaptive networks: Expectation and prediction. Psychol. Rev. 88, 135–170 (1981).

    Article  CAS  PubMed  Google Scholar 

  41. Schultz, W. Dopamine reward prediction error coding. Dialogues Clin. Neurosci. 18, 23–32 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  42. Tobler, P. N., Fiorillo, C. D. & Schultz, W. Adaptive coding of reward value by dopamine neurons. Science 307, 1642–1645 (2005).

    Article  ADS  CAS  PubMed  Google Scholar 

  43. Lak, A. et al. Dopaminergic and prefrontal basis of learning from sensory confidence and reward value. Neuron 105, 700–711 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Sabandal, J. M., Berry, J. A. & Davis, R. L. Dopamine-based mechanism for transient forgetting. Nature 591, 426–430 (2021).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  45. Seelig, J. D. & Jayaraman, V. Neural dynamics for landmark orientation and angular path integration. Nature 521, 186–191 (2015).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  46. Green, J., Vijayan, V., Mussells Pires, P., Adachi, A. & Maimon, G. A neural heading estimate is compared with an internal goal to guide oriented navigation. Nat. Neurosci. 22, 1460–1468 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Shih, C. T. et al. Connectomics-based analysis of information flow in the drosophila brain. Curr. Biol. 25, 1249–1258 (2015).

    Article  CAS  PubMed  Google Scholar 

  48. Franconville, R., Beron, C. & Jayaraman, V. Building a functional connectome of the drosophila central complex. eLife 7, e37017 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  49. Fisher, Y. E., Lu, J., D’Alessandro, I. & Wilson, R. I. Sensorimotor experience remaps visual input to a heading-direction network. Nature 576, 121–125 (2019).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  50. Mashour, G. A., Roelfsema, P., Changeux, J. P. & Dehaene, S. Conscious processing and the global neuronal workspace hypothesis. Neuron 105, 776–798 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Xie, T. et al. A genetic toolkit for dissecting dopamine circuit function in Drosophila. Cell Rep. 23, 652–665 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Baines, R. A., Uhler, J. P., Thompson, A., Sweeney, S. T. & Bate, M. Altered electrical properties in Drosophila neurons developing without synaptic transmission. J. Neurosci. 21, 1523–1531 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. McGuire, S. E., Mao, Z. & Davis, R. L. Spatiotemporal gene expression targeting with the TARGET and gene-switch systems in Drosophila. Sci. STKE 2004, pl6 (2004).

    Article  PubMed  Google Scholar 

  54. Klapoetke, N. C. et al. Independent optical excitation of distinct neural populations. Nat. Methods 11, 338–346 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Akerboom, J. et al. Optimization of a GCaMP calcium indicator for neural activity imaging. J. Neurosci. 32, 13819–13840 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Weir, P. T. & Dickinson, M. H. Functional divisions for visual processing in the central brain of flying Drosophila. Proc. Natl Acad. Sci. USA. 112, E5523–E5532 (2015).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  57. Savitzky, A. & Golay, M. J. E. Smoothing and differentiation of data by simplified least squares procedures. Anal. Chem. 36, 1627–1639 (1964).

    Article  ADS  CAS  Google Scholar 

  58. Wobbrock, J. O., Findlater, L., Gergle, D. & Higgins, J. J. The aligned rank transform for nonparametric factorial analyses using only ANOVA procedures. In Proc. SIGCHI Conference on Human Factors in Computing Systems 143–146 (Association for Computing Machinery, 2011).

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Acknowledgements

We thank F. Cardone and I. Freerkson for their assistance with designing and fabricating electronic and mechanical components; A. Calhoun, W. Joiner, M. Wu and V. Jayaraman for gifting fly stocks; T. Dawkins for advice and assistance with various experimental analyses; E. Huie for assistance with behavioural experiments; M. Nelson for assistance with in vivo imaging experiments; and T. Sejnowski for comments on the manuscript. This work was supported by the Air Force Office of Scientific Research grants FA9550-14-1-0211 and FA9550-19-1-0280 to D.G. and R.J.G.; awards from the Mathers Foundation 20154167 and National Science Foundation 1212778 to R.J.G.; and the European Union’s Horizon 2020 Framework Programme for Research and Innovation under specific grant agreement no. 945539 (Human Brain Project SGA3) and Kavli Institute for Brain and Mind International Faculty award to J.-P.C.

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Authors and Affiliations

  1. Kavli Institute for Brain and Mind, University of California, San Diego, La Jolla, CA, USA

    Dhruv Grover, Jen-Yung Chen, Jiayun Xie, Jinfang Li, Jean-Pierre Changeux & Ralph J. Greenspan

  2. CNRS UMR 3571, Institut Pasteur, Paris, France

    Jean-Pierre Changeux

  3. College de France, Paris, France

    Jean-Pierre Changeux

  4. Division of Biological Sciences, University of California, San Diego, La Jolla, CA, USA

    Ralph J. Greenspan

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Contributions

D.G. designed the behaviour and imaging assay hardware and software. D.G. and J.-Y.C. performed behaviour, neural and receptor silencing and optogenetic activation experiments. J.X., J.L. and D.G. acquired in vivo imaging data. J.-Y.C. performed immunostaining experiments. D.G., J.-Y.C., J.X. and J.L. analysed the data. D.G., J.-P.C., J.-Y.C. and R.J.G. drafted the manuscript. All authors reviewed and approved the final manuscript.

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Correspondence to Ralph J. Greenspan.

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Extended data figures and tables

Extended Data Fig. 1 Drosophila behaviour assay for visual trace and delay aversive conditioning.

a, Panoramic virtual-reality system components with real-time machine-vision based wingbeat amplitude tracking for tethered flying flies. 1) Projector, 2) 880 nm infrared diffused backlight, 3) Rear-projection coated acrylic sphere, 4) High-speed camera for wing tracking, 5) 850 nm long-pass optical filter, 6) photographic macro lens, 7) xyz-translation micro-manipulator, 8) Fly tether-rod, 9–10) Mirrors for re-directing projection patterns for panoramic visual stimulus presentation, 11) 808 nm infrared laser for delivery of heat punishment, 12) 850 nm long-pass dichroic filter (see Methods, ‘Tethered-flight behaviour assay’, for optical configurations used in optogenetic experiments). b, Sample display frame consisting of three orthogonal views of a virtually created sphere that is projected onto the curved spherical projection screen from frontal and two lateral sides. The virtual sphere with warped T’s is programmatically calibrated to fit the dimensions and curvature of the physical display screen. Top, inverted-T displayed 45° from front-centre in CW direction with upright-T 180° away. Bottom, inverted-T displayed 45° from front-centre in CCW direction with upright-T 180° away. c, Internal body temperature of a tethered fly when exposed to infrared-laser-based heat punishment. Red bars indicate 0.5 s of infrared laser exposure, power-level of which was optimized to cause an immediate and robust rise in temperature from ambient room temperature of 25 °C to 35 °C. d, Delay learning PI (n = 20 flies per group) measured as a factor of CS duration and number of training trials. PI > 0 indicates successful learning as the fly spends more time fixating on CS- than CS+. Peak learning (indicated with black arrow) occurred with CS duration of 10 s and 7 training trials. e, Change in flight orientation in the 5 s after air puff (0.5 s). See Methods, ‘Tethered-flight behaviour assay’, for experimental details. Binned is the fraction of time each fly (n = 40 flies) spent orienting towards or away from the stimulus (orientation change greater than 20°), or no change in flight orientation (less than or equal to 20°). f, Test of conditioning to distractor stimulus. Flies are subjected to full trace conditioning protocol (5-s TI) with distractors (n = 40 flies). Following training, same experimental protocol as e was followed to test distractor-only conditioning response. Binned is the fraction of time each fly spent orienting towards (attraction, positive conditioning) or away (aversion, negative conditioning) from the stimulus, or no change in flight orientation (neutral). Box plot centre (median), edges (IQR), whiskers (1.5x IQR). Groups were compared using a Kruskal–Wallis and post-hoc unpaired two-sided Mann–Whitney U-tests with Bonferroni corrected multiple comparisons. ** indicates p-value < 0.01, exact P values in Supplementary Table 1. Scatters represent individual fly PI scores.

Extended Data Fig. 2 Conditioning-related experimental controls.

a, Delay and trace conditioning experimental control protocols tested in b, c. b, PI (mean with s.e.m., n = 20 flies per group) for flies tested with US-only presentation (no CS), CS-only presentation (no US), reverse trace conditioning wherein US precedes CS+ presentation with a gap of 2 s. PI = 0 indicates no learning as the fly spends an equal amount of time fixating on CS- and CS+ during the test trial. Groups were compared using Kruskal–Wallis and post-hoc unpaired two-sided Mann–Whitney U-tests with Bonferroni corrected multiple comparisons. No significant differences were observed between groups. c, PI (mean with s.e.m., n = 40 flies per group) for delay and trace conditioning (5–40-s TI) where CS+ precedes CS- presentation (blue) and CS- precedes CS+ (red). Group comparisons were performed using a two-factor ART-ANOVA test. No significant difference was observed between groups. Scatters represent individual fly PI scores.

Extended Data Fig. 3 Testing the effects of multi-modality distractors on conditioning.

a, Delay and trace conditioning protocols under different sets of (air puff and optogenetic) distractor conditions tested in b–e. b, PI (mean with s.e.m., n = 40 flies per group) for flies tested under delay and trace conditioning (5–40-s TI) without (air puff) distractors (black), multiple distractors including during the TI (distractor set #1, blue), single distractor during the TI (distractor set #2, red), multiple distractors except during the TI (distractor set #3, grey). Groups were compared using a two-factor ART-ANOVA test. ** indicates p-value < 0.01, comparing no distractor conditions with corresponding distractor set #1 conditions (blue), and corresponding distractor set #2 conditions (red). Exact P values in Supplementary Table 1. c, PI (mean with s.e.m., n = 40 flies per group) for flies tested under delay and trace conditioning (5-s TI) testing the effect of amplified (air puff) distractions - distractor set #1 (white, control), distractor set #4 with double the normal air flow rate (regulated at a rate of 100 ml min−1) (grey), distractor set #5 with double the normal air puff duration (1 s) (blue), and distractor set #6 with double the number of air puffs with an inter-pulse interval of 0.5 s, starting at times shown in a. Groups were compared using a Kruskal–Wallis and post-hoc unpaired two-sided Mann–Whitney U-tests with Bonferroni corrected multiple comparisons. d, PI (mean with s.e.m., n = 20 flies per group) delay and trace conditioning (5-s TI), with (distractor set #1, grey) and without distractors (white) by varying the number of training trials used for conditioning. Groups were compared using a two-factor ART-ANOVA test. e, Delay and trace learning (5-s TI) in flies where optogenetic activation (red-light pulse) of auditory sensory neurons (JO_AB-Gal4>>UAS-CsChrimson) was used as distractors in-lieu of the air puff, as shown in a. PI (mean with s.e.m., n = 20 flies per group) raised on standard food (white bars), and food supplemented with all-trans-retinal (grey). Gal4 control activation (pBDPGal4>>UAS-CsChrimson) with no brain expression included as a secondary control. Groups were compared using a Kruskal–Wallis and post-hoc unpaired two-sided Mann–Whitney U-tests with Bonferroni corrected multiple comparisons. ** indicates p-value < 0.01, exact P values in Supplementary Table 1. Scatters in all panels represent either individual fly probability or PI scores.

Extended Data Fig. 4 Effect of neural silencing of central complex and mushroom body structures on delay and trace conditioning.

a, Individual flies were tested under delay and trace conditioning (5 and 10-s TI). b, Top-left, illustration of implicated learning and memory structures in the fly brain, ellipsoid body (yellow), fan-shaped body (purple) and mushroom body (red). PI for delay conditioning, and trace conditioning with c, 5-s TI, and d, 10-s TI. Shown are flies with neural activity silenced (UAS-Kir2.1,Tub-Gal80ts) in the ellipsoid body ring neurons – R1 (c105-Gal4), R3 and R4d (c232-Gal4) and R2 and R4m (EB1-Gal4), fan-shaped body columnar neurons – dorsal layers (c205-Gal4), dorsal and central layers (R38E07-Gal4), and dorsal and ventral layers (104y-Gal4), and neurons projecting to the mushroom body lobes – α and β lobes (17d-Gal4), α’ and β’ lobes (c305a-Gal4) and γ lobes (MB009B-Gal4), along with respective driver-less and effector-less controls. PI (mean with s.e.m., n = 20 flies per group) for flies with intact Gal80 repression of Kir2.1 (white), and warm-induction of Kir2.1 (grey). Scatters represent individual fly PI scores. Groups were compared (to both driver-less and effector-less controls) using a Kruskal–Wallis and post-hoc unpaired two-sided Mann–Whitney U-tests with Bonferroni corrected multiple comparisons. ** indicates p-value < 0.01, exact P values in Supplementary Table 1.

Extended Data Fig. 5 Ratiometric calcium imaging of ellipsoid body ring neurons during trace conditioning reveals an increased oscillatory component and slower decline with repeated training that is susceptible to distractions.

a, Ratiometric imaging of an EB1-Gal4, UAS-GCaMP6f.myr-tdTomato female during a single trace conditioning (5-s TI) experiment without (air puff) distractors (left), and with distractors (right). Shown, raw dFratio/Fratio activity traces (where Fratio = FGCaMP6f/FtdTomato) for trials 1, 4, and 7. Red curve fits are single-term exponential model fits through the raw dFratio/Fratio activity traces starting at the end of CS presentation. b, Scree plots of cumulative variance explained by each of the top 50 principal components for all trace conditioning trials without distractors (blue), and with distractors (red). c, Cumulative variance explained by the top 12 components per trial for trace conditioning without distractors (blue), and with distractors (red). d, Exponential curve fit decay rates of EB1 neural activity post-CS for trials without distractors (blue), and with distractors (red). e, Normalized relative power of EB1 neural activity for trials 1, 4 and 7 (left to right) during CS. Shown are the detected frequencies at maximum relative power for trials without distractors (blue), and with distractors (red), greater than peak mean baseline frequency. Black line represents mean baseline frequency spectrum (from n = 51 flies). f, Frequency (at maximum relative power) of EB1 neural activity during CS for trials without distractors (blue), and with distractors (red) (see Methods, ‘Frequency and decay rate computation’). g, Normalized relative power of EB1 neural activity for trials 1, 4 and 7 (left to right) during the 5-s TI. Shown are the detected frequencies at maximum relative power for trials without distractors (blue), and with distractors (red), greater than peak mean baseline frequency. Black line represents mean baseline frequency spectrum (from n = 51 flies). h, Frequency (at maximum relative power) of EB1 neural activity across trials during the 5-s TI for trials without distractors (blue), and with distractors (red) (see Methods, ‘Frequency and decay rate computation’). No distractor trials (n = 16 flies), distractor trials (n = 16 flies). Box plot centre (median), edges (IQR), whiskers (1.5x IQR). Scatters represent individual fly activity scores. Group comparisons were performed using a two-factor ART-ANOVA test. ** indicates p-value < 0.01, exact P values in Supplementary Table 1.

Extended Data Fig. 6 Ratiometric calcium imaging of ellipsoid body ring neurons during delay conditioning reveals an increased oscillatory component and steady decline with repeated training that is not susceptible to distractions.

a, Ratiometric imaging of an EB1-Gal4, UAS-GCaMP6f.myr-tdTomato female during a single delay conditioning experiment without (air puff) distractors (left), and with distractors (right). Shown, raw dFratio/Fratio activity traces (where Fratio = FGCaMP6f/FtdTomato) for trials 1, 4, and 7. Red curve fits are single-term exponential model fits through the raw dFratio/Fratio activity traces starting at the end of CS. b, Scree plots of cumulative variance explained by each of the top 50 principal components for all delay conditioning trials without distractors (blue), and with distractors (red). c, Cumulative variance explained by the top 12 components per trial for delay conditioning without distractors (blue), and with distractors (red). d, Exponential curve fit decay rates of EB1 neural activity post-CS for trials without distractors (blue), and with distractors (red). e, Normalized relative power of EB1 neural activity for trials 1, 4 and 7 (left to right) during CS. Shown are the detected frequencies at maximum relative power for trials without distractors (blue), and with distractors (red), greater than peak mean baseline frequency. Black line represents mean baseline frequency spectrum (from n = 51 flies). f, Frequency (at maximum relative power) of EB1 neural activity across delay conditioning trials during CS for trials without distractors (blue), and with distractors (red) (see Methods, ‘Frequency and decay rate computation’). No distractor trials (n = 9 flies), distractor trials (n = 9 flies). g, Frequency (from f) as a function of learning performance (see Methods, ‘Correlating physiological and behavioural metrics’) for trace conditioning with (red, R2 0.72) and without (blue, R2 0.77) distractors. Curve fits are second degree polynomials through the median activity for each of the no distractor (blue) and distractor (red) trials. Box plot centre (median), edges (IQR), whiskers (1.5x IQR). Scatters represent individual fly activity scores. Group comparisons were performed using a two-factor ART-ANOVA test. No significant difference was observed between groups.

Extended Data Fig. 7 Ratiometric calcium imaging of ellipsoid body ring neuron activity in CS-only and US-only conditions.

a, Ratiometric imaging of EB1-Gal4, UAS-GCaMP6f.myr-tdTomato female during a single CS-only presentation (no US) experiment. Shown, raw dFratio/Fratio activity traces (where Fratio = FGCaMP6f/FtdTomato) for trials 1, 4, and 7. Red curve fits are single-term exponential model fits through the raw dFratio/Fratio activity traces starting at the end of CS. b, Exponential curve fit decay rates of EB1 neural activity post-CS. c, Normalized relative power of EB1 neural activity for trials 1, 4 and 7 (left to right) during CS. Shown are the detected frequencies at maximum relative power greater than peak mean baseline frequency. Black line represents mean baseline frequency spectrum (from n = 51 flies). d, Frequency (at maximum relative power) of EB1 neural activity during CS (see Methods, ‘Frequency and decay rate computation’). e, Normalized relative power of EB1 neural activity for trials 1, 4 and 7 (left to right) during the 5 s post-CS period. Shown are the detected frequencies at maximum relative power greater than peak mean baseline frequency. Black line represents mean baseline frequency spectrum (from n = 51 flies). f, Frequency (at maximum relative power) of EB1 neural activity during the 5 s post-CS period (see Methods, ‘Frequency and decay rate computation’). CS-only presentation trials, n = 17 flies. Box plot centre (median), edges (IQR), whiskers (1.5x IQR). Scatters represent individual fly activity scores. Friedman’s repeated measure ANOVA test was used for comparisons between trials. No significant difference was observed. g, Ratiometric imaging of an EB1-Gal4, UAS-GCaMP6f.myr-tdTomato female during a single US-only presentation (no CS) experiment. Shown, raw dFratio/Fratio activity traces (where Fratio = FGCaMP6f/FtdTomato) for trials 1, 4, and 7. No notable calcium activity was detected. h, Normalized relative power of EB1 neural activity for trials 1, 4 and 7 (left to right) during the 10 s CS fictitious presentation (5–15 s). No frequencies of maximum relative power greater than peak mean baseline frequency were detected. Black line represents mean baseline frequency spectrum (from n = 51 flies). i, Normalized relative power of EB1 neural activity for trials 1, 4 and 7 (left to right) during the 5 s post-fictitious-CS presentation (15–20 s). No frequencies of maximum relative power greater than peak mean baseline frequency were detected. Black line represents mean baseline frequency spectrum (from n = 51 flies). US-only presentation trials, n = 8 flies.

Extended Data Fig. 8 Ratiometric calcium imaging of ellipsoid-body-projecting dopaminergic neurons during delay conditioning.

Confocal fluorescence images of a, TH-Gal4>>UAS-myr-EGFP, b, MB504b-Gal4>>UAS-myr-EGFP, c, c346-Gal4>>UAS-myr-EGFP, and d, c346-Gal4, TH-FLP>>UAS-FRT-stop-FRT-mCD8-GFP expression in female Drosophila brains staining the pattern of dopaminergic neurons in most of the brain (does not include the PAM cluster), PPL1 dopaminergic cluster projecting to the mushroom bodies, and PPM3 dopaminergic cluster projecting to the ellipsoid body, respectively. In a, left and right images correspond to different z-planes across the brain highlighting dopaminergic neuron subsets targeting the central complex and mushroom body structures. Scale bar is 50 μm. At least three brains were immunostained per genotype presented in a–d. e, Ratiometric imaging of a c346-Gal4, UAS-GCaMP6m.myr-tdTomato female during a single delay conditioning experiment without (air puff) distractors (left), and with distractors (right). Shown, raw dFratio/Fratio activity traces (where Fratio = FGCaMP6m/FtdTomato) for each training trial. f, Peak dFratio/Fratio activity of ellipsoid body DANs during CS (left), and post-US (right), across trials, without distractors (blue, n = 5 flies), and with distractors (red, n = 5 flies). Box plot centre (median), edges (IQR), whiskers (1.5x IQR). Scatters represent individual fly activity scores. Group comparisons were performed using a two-factor ART-ANOVA test. No significant difference was observed between groups.

Extended Data Fig. 9 Ratiometric calcium imaging of ellipsoid-body-projecting dopaminergic neurons in CS-only and US-only conditions.

a, Ratiometric imaging of a c346-Gal4, UAS-GCaMP6m.myr-tdTomato female during a single CS-only presentation (no US) experiment without (air puff) distractors (left), and with distractors (right). Shown, raw dFratio/Fratio activity traces (where Fratio = FGCaMP6m/FtdTomato) for each training trial. b, Peak dFratio/Fratio activity of ellipsoid body DANs during CS (top), and post-CS (bottom), across trials, without distractors (blue, n = 5 flies), and with distractors (red, n = 5 flies). c, Ratiometric imaging of a c346-Gal4, UAS-GCaMP6m.myr-tdTomato female during a single US-only (no CS) experiment without (air puff) distractors (left), distractors with US in a simulated delay conditioning setting (middle), and distractors with US in a simulated trace conditioning (5-s TI) setting (right). Shown, raw dFratio/Fratio activity traces (where Fratio = FGCaMP6m/FtdTomato) for each training trial. d, Peak dFratio/Fratio activity of ellipsoid body DANs prior to US (left), and post-US (right), across trials, without distractors (black, n = 5 flies), distractors with US in simulated delay conditioning setting (blue, n = 5 flies), and distractors with US in simulated trace conditioning (5-s TI) setting (red, n = 5 flies). Box plot centre (median), edges (IQR), whiskers (1.5x IQR). Scatters represent individual fly activity scores. Group comparisons were performed using a two-factor ART-ANOVA test. No significant difference was observed between groups.

Extended Data Fig. 10 Role of Dop1R2 and DopEcR dopamine receptor signalling in ellipsoid body ring neurons during delay and trace conditioning.

a, Frequency (with maximum power, see Methods, ‘Frequency and decay rate computation’) of EB1 neural activity with either Dop1R2 or DopEcR dopamine receptor signalling impairment across trials for delay conditioning during CS for EB1-Gal4, UAS-GCaMP6f.myr-tdTomato flies (black), EB1-Gal4, UAS-GCaMP6f.myr-tdTomato, UAS-Dop1R2RNAi flies (red), and EB1-Gal4, UAS-GCaMP6f.myr-tdTomato, UAS-DopEcRRNAi flies (blue). n = 9 flies (black), n = 5 flies (red), n = 5 flies (blue). b, Frequency of EB1 neural activity with either Dop1R2 or DopEcR signalling impairment across trials for trace conditioning (5-s TI) (during CS, left; during TI, right) for EB1-Gal4, UAS-GCaMP6f.myr-tdTomato flies (black), EB1-Gal4, UAS-GCaMP6f.myr-tdTomato, UAS-Dop1R2RNAi flies (red), and EB1-Gal4, UAS-GCaMP6f.myr-tdTomato, UAS-DopEcRRNAi flies (blue) (see Methods, ‘Frequency and decay rate computation’). n = 16 flies (black), n = 5 flies (red), n = 5 flies (blue). Box plot centre (median), edges (IQR), whiskers (1.5x IQR). Scatters represent individual fly metrics. Group comparisons were performed using a two-factor ART-ANOVA test. No significant difference was observed between groups.

Supplementary information

Reporting Summary

Supplementary Table 1

Statistical comparisons and exact P values for each experiment presented in the main and Extended Data figures.

Supplementary Video 1

EB ring neuron activity during trace conditioning. In vivo ratiometric calcium imaging in an EB1-Gal4, UAS-GCaMP6f.myr-tdTomato female during trace conditioning (5 s trace interval). Left, tdTomato channel with a pseudocolour Fratio = FGCaMP6f/FtdTomato representation of the GCaMP6f signal. Frames with squares on top-right indicate CS (blue), and US (red). Right, dFratio/Fratio activity traces for the corresponding trial. Each row corresponds to a single training trial, wherein CS (blue) and US (red) are presented. Frame rate is 1.5x recording speed (9 Hz).

Supplementary Video 2

EB ring neuron activity during trace conditioning with distractions. In vivo ratiometric calcium imaging in an EB1-Gal4, UAS-GCaMP6f.myr-tdTomato female during trace conditioning (5 s trace interval) with (air puff) distractions. Left, tdTomato channel with a pseudocolour Fratio = FGCaMP6f/FtdTomato representation of the GCaMP6f signal. Frames with squares on top-right indicate CS (blue), US (red), and distractors (grey). Right, dFratio/Fratio activity traces for the corresponding trial. Each row corresponds to a single training trial, wherein CS (blue), US (red), and distractors (grey) are presented. Frame rate is 1.5x recording speed (9 Hz).

Supplementary Video 3

EB ring neuron activity during delay conditioning. In vivo ratiometric calcium imaging in an EB1-Gal4, UAS-GCaMP6f.myr-tdTomato female during delay conditioning. Left, tdTomato channel with a pseudocolour Fratio = FGCaMP6f/FtdTomato representation of the GCaMP6f signal. Frames with squares on top-right indicate CS (blue), and US (red). Right, dFratio/Fratio activity traces for the corresponding trial. Each row corresponds to a single training trial, wherein CS (blue) and US (red) are presented. Frame rate is 1.5x recording speed (9 Hz).

Supplementary Video 4

EB ring neuron activity during delay conditioning with distractions. In vivo ratiometric calcium imaging in an EB1-Gal4, UAS-GCaMP6f.myr-tdTomato female during delay conditioning with (air puff) distractions. Left, tdTomato channel with a pseudocolour Fratio = FGCaMP6f/FtdTomato representation of the GCaMP6f signal. Frames with squares on top-right indicate CS (blue), US (red), and distractors (grey). Right, dFratio/Fratio activity traces for the corresponding trial. Each row corresponds to a single training trial, wherein CS (blue), US (red), and distractors (grey) are presented. Frame rate is 1.5x recording speed (9 Hz).

Supplementary Video 5

EB-projecting dopaminergic neuron activity during trace conditioning. In vivo ratiometric calcium imaging in a c346-Gal4, UAS-GCaMP6m.myr-tdTomato female during trace conditioning (5 s trace interval). Left, tdTomato channel with a pseudocolour Fratio = FGCaMP6m/FtdTomato representation of the GCaMP6m signal. Frames with squares on top-right indicate CS (blue), and US (red). Right, dFratio/Fratio activity traces for the corresponding trial. Each row corresponds to a single training trial, wherein CS (blue) and US (red) are presented. Frame rate is 1.5x recording speed (9 Hz).

Supplementary Video 6

EB-projecting dopaminergic neuron activity during trace conditioning with distractions. In vivo ratiometric calcium imaging in a c346-Gal4, UAS-GCaMP6m.myr-tdTomato female during trace conditioning (5 s trace interval) with (air puff) distractions. Left, tdTomato channel with a pseudocolour Fratio = FGCaMP6m/FtdTomato representation of the GCaMP6m signal. Frames with squares on top-right indicate CS (blue), US (red), and distractors (grey). Right, dFratio/Fratio activity traces for the corresponding trial. Each row corresponds to a single training trial, wherein CS (blue), US (red), and distractors (grey) are presented. Frame rate is 1.5x recording speed (9 Hz).

Supplementary Video 7

EB-projecting dopaminergic neuron activity during delay conditioning. In vivo ratiometric calcium imaging in a c346-Gal4, UAS-GCaMP6m.myr-tdTomato female during delay conditioning. Left, tdTomato channel with a pseudocolour Fratio = FGCaMP6m/FtdTomato representation of the GCaMP6m signal. Frames with squares on top-right indicate CS (blue), and US (red). Right, dFratio/Fratio activity traces for the corresponding trial. Each row corresponds to a single training trial, wherein CS (blue) and US (red) are presented. Frame rate is 1.5x recording speed (9 Hz).

Supplementary Video 8

EB-projecting dopaminergic neuron activity during delay conditioning with distractions. In vivo ratiometric calcium imaging in a c346-Gal4, UAS-GCaMP6m.myr-tdTomato female during delay conditioning with (air puff) distractions. Left, tdTomato channel with a pseudocolour Fratio = FGCaMP6m/FtdTomato representation of the GCaMP6m signal. Frames with squares on top-right indicate CS (blue), US (red), and distractors (grey). Right, dFratio/Fratio activity traces for the corresponding trial. Each row corresponds to a single training trial, wherein CS (blue), US (red), and distractors (grey) are presented. Frame rate is 1.5x recording speed (9 Hz).

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Grover, D., Chen, JY., Xie, J. et al. Differential mechanisms underlie trace and delay conditioning in Drosophila. Nature 603, 302–308 (2022). https://doi.org/10.1038/s41586-022-04433-6

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