Skip to main content
UKPMC Funders Author Manuscripts logoLink to UKPMC Funders Author Manuscripts
. Author manuscript; available in PMC: 2025 Dec 25.
Published in final edited form as: Cold Spring Harb Protoc. 2025 Aug 1;2025(8):pdb.top108567. doi: 10.1101/pdb.top108567

Twists to Classical Conditioning of Adult Drosophila

Zeynep Okray 1, Scott Waddell 1,1
PMCID: PMC7618529  EMSID: EMS211456  PMID: 39389621

Abstract

Memory has been extensively studied in Drosophila since the early 1970s. Straightforward aversive and appetitive conditioning paradigms train populations of flies to associate the pairing of one of two odors with either punishment or reward. After training, the flies show either preferential avoidance or approach behavior, to the appropriate odor, when given a choice between the two odors in a simple T-maze apparatus. These basic experimental approaches have proven useful in understanding the genetic, molecular, cellular, and neuronal network bases of various valence-specific memories in the fly brain. In addition, numerous modifications to these assays have permitted the study of a broad range of memory-related phenomena. Labile short-term avoidance and approach memories can be readily distinguished from more stable “consolidated” long-term memory equivalents. Prior or sub-sequent experience of the training cues, and manipulations of the flies’ condition, have revealed how parallel competing memories and incompatible states can temporarily interfere with memory retrieval, providing insight into mechanisms of forgetting. Recent studies have also modified the training and testing apparatus to allow simultaneous presentation of odors and colors, providing insight into mechanisms of multisensory learning.

Introduction

Investigation of Drosophila memory was first reported in the early 1970s by William G. “Chip” Quinn and William A. Harris under the tutelage of Seymour Benzer (Quinn et al. 1974). These studies were initiated with the goal of identifying genes that encode critical elements of the learning machinery. Over the years, approaches and goals have shifted. Thousands of individual fly lines are now available that allow investigators to precisely control gene expression in many (most, even) individual cell types in the fly brain, especially within memory-relevant networks of the mushroom bodies (Pfeiffer et al. 2010; Gohl et al. 2011; Jenett et al. 2012; Aso et al. 2014; Tirian and Dickson 2017; Luan et al. 2020). Using these “neuron-specific” lines with a variety of powerful effector transgenes permits one to label and visualize (Lee and Luo 1999; Sutcliffe et al. 2017), manipulate the expression of specific genes within (Dietzl et al. 2007; Hu et al. 2021), record from (Chamberland et al. 2017; Jing et al. 2020; Sun et al. 2020; Kannan et al. 2022; Abdelfattah et al. 2023; Zhang et al. 2023), and control the activity of (Kitamoto 2001; Lima and Miesenbock 2005; Hamada et al. 2008; Klapoetke et al. 2014; Mohamed et al. 2017; Ott et al. 2024) the neurons of interest. With these tools in hand, memory research in the fly now extends past traditional neuroscience boundaries to include molecular, cellular, systems, and behavioral studies (Cognigni et al. 2018; Modi et al. 2020). Our associated protocol describes the manufacture and use of a T-maze apparatus to test aversive and appetitive olfactory and multisensory learning and memory in Drosophila (see Protocol: Classical Conditioning of Adult Drosophila [Okray et al. 2024]).

Aversive Conditioning

The aversive conditioning assay that is used in many laboratories was initially devised by Tim Tully in Chip Quinn’s laboratory (Tully and Quinn 1985). Approximately 100 flies are trained for 1 min to associate one of two odors with 12 electric shocks. When later given a choice between two T-maze arms suffused with either the previously shock-paired odor (CS+) or the other odor (CS), the flies preferentially avoid the CS+. A single 1-min training session forms CS+ avoidance memory that is barely detectable when performance is measured this way 24 h afterwards.

It is generally appreciated that the perdurance of measurable memory depends on the training protocol. A seminal study showed that five to 10 repetitions of the 1-min aversive training session can extend the time in which “aversive” memory can be measured to >1 wk, and this was most apparent if the sessions are “spaced” with intervening rest intervals, rather than one after the other—”massed” (Tully et al. 1994). This work introduced the concept of two coexisting types of genetically and pharmacologically separable long-term aversive memory: anesthesia-resistant memory (ARM) and protein synthesis-dependent long-term memory (LTM). A later paper argued that ARM and LTM were mutually exclusive (Tully et al. 1994).

Varying Test Odor Choice and Context

Recently, instead of giving flies a choice of CS+ versus CS after testing, flies were given a choice of CS+ versus a novel odor (one they had never experienced in training), or CS versus a novel odor. This work found that repetitive CS+/CS training trials actually allow flies to learn more information than just an odor–shock association (Jacob and Waddell 2020). Most evidently, the performance gain from spaced aversive training (CS+/CS trials) results from flies learning that the previously shock-paired CS+ should be avoided but also that the explicitly non-shock-paired CS odor is “safe.” Perhaps surprisingly, the CS safety memory appears to account for the most persistent odor LTM following spaced aversive training, whereas ARM represents the aversive memory for the CS+.

A similarly surprising discovery was made when investigators kept the “context” of the trained odors consistent between training and testing. In regular aversive training and testing, flies are trained in a “shock” tube whose walls are an electrifiable copper grid and are tested for odor preference in a different context: The two testing tubes are clear plastic. However, when Zhao et al. (2019) instead tested trained flies for their odor preference using two nonelectrified shock tubes, they observed that even a single 2-min aversive training session formed memory measurable for up to 2 wk! Therefore, a single training session forms long-lasting memories, but their retrieval is context-dependent. This finding suggests that repetitive training also permits flies to form odor valence memories that are “free” of the context constraints that are a property of memory following a single training trial.

Another recent study added additional evidence that the single training session forms long-lasting aversive memories. Up to 8 d after a single aversive training session, “forgotten” aversive memories could be reinstated by mild retraining, which is in itself insufficient to form measurable memory (Wang et al. 2023). This memory “savings” type of experiment (Ebbinghaus 1885) suggests that the new suboptimal learning adds to a memory that was there but could not be accessed.

Appetitive Conditioning

The standard appetitive conditioning assay was initially devised by Bruce Tempel in Chip Quinn’s laboratory (Tempel et al. 1983). Here, populations of food-deprived flies are trained for 2 min to associate one of two odors with sucrose reward (Krashes and Waddell 2008; Colomb et al. 2009).

When later tested in the T-maze for their preference between the two odors used in training, the flies preferentially approach the previously sugar-paired odor. A single 2-min training session with sucrose reward forms protein synthesis-dependent LTM that remains measurable for days after.

An advantage of the sucrose reward paradigm is that sugar is a physiologically relevant reinforcer. It is also simple to change the odor-paired sugar from sucrose to those with different properties, such as other naturally occurring sugars that are more or less sweet and/or nutritious, or nonmetabolizable L-sugars, synthetic sweeteners, etc., to investigate different forms of memory (Burke and Waddell 2011; Burke et al. 2012; Huetteroth et al. 2015; McGinnis et al. 2016).

Complexities of the sucrose reward assay arise when measuring extended memory. Long-term food deprivation is obviously lethal. Therefore, one can only test memory beyond 24 h in the few flies that remain alive (if they were starved for 16 h before and 24 h after training), or feed the flies after training (Krashes and Waddell 2008). Although it might seem trivial to include an after-training feed, there are two critical considerations if choosing to do so. First, feeding to satiety posttraining suppresses memory performance. This is, however, reversible by restarving the flies prior to testing (Krashes and Waddell 2008; Krashes et al. 2009). The clear state dependence of sugar reward memory expression means that it is critical to distinguish between partially satiated flies and those with poor memory. The second issue to consider if feeding flies after sugar reward training is that neural processing of the resulting memory can be different in hungry and satiated conditions (Chouhan et al. 2021).

Flies can also be appetitively conditioned when thirsty by pairing odor and water reward (Lin et al. 2014; Lee et al. 2020). Expression of water-reinforced appetitive memories is similarly deprivation state-dependent but is specifically promoted by thirst rather than hunger. In fact, flies that are trained when both hungry and thirsty by pairing odor A with water and odor B with sugar will subsequently selectively seek odor A when thirsty and odor B when hungry (Senapati et al. 2019). This impressive level of state-dependent control of memory expression arises from neural circuit integration of internal state information with that for the appropriate memory (Krashes et al. 2009; Albin et al. 2015; Perisse et al. 2016; Senapati et al. 2019; Meschi et al. 2024).

Further Twists On Learning and Memory Paradigms

Recent studies have described protocols to train flies to associate a specific odor and color combination with sucrose reward or with electric shock punishment (Thiagarajan et al. 2022; Okray et al. 2023), allowing study of multisensory learning. Interestingly, multisensory training enhances memory performance for the combined and individual odor and color sensory cues.

Aversive and appetitive paradigms in the fly have also been used to investigate neural mechanisms of other classical learning phenomena. For example, pre-exposing flies to an odor, before appetitive training with that odor and sucrose, can produce a temporary and context-dependent latent inhibition (Jacob et al. 2021). The flies learn the new odor–sugar association, but the retrieval of that memory is temporarily suppressed by competition with the prior odor pre-exposure memory, so no memory performance can be measured. Similarly, re-exposure to the previously reinforced CS+ odor after training triggers memory extinction, where the flies form a parallel memory of opposite valence that competes with the original memory and so temporarily nullifies memory performance (Felsenberg et al. 2017,2018; Yang et al. 2023). In contrast, re-exposure to the CS after training can trigger reconsolidation of the original memory, where it temporarily returns to a “nonconsolidated” form that can be disrupted with anesthesia (Felsenberg et al. 2017). In addition, presenting flies with a distracting air puff, shocks, or bright light before testing can temporarily inhibit memory expression, or induce “transient forgetting” (Sabandal et al. 2021).

Last, flies can also be trained by pairing an odor with direct activation of sensory or reinforcing neurons, rather than with sugar or shock/bitter (Schroll et al. 2006; Claridge-Chang et al. 2009; Aso et al. 2010; Burke et al. 2012; Liu et al. 2012; Das et al. 2014; Huetteroth et al. 2015; Jovanoski et al. 2023). Training in these cases involves presenting one of the two odors with a hot air stream (thermogenetics) or the appropriate wavelength of light (optogenetics) to trigger the genetically encoded ion channels, and thereby neuronal activation.

The approaches outlined above have been instrumental to progress in the field, having been successfully used to discover genes and neural circuit principles directing learning and memory. For further information, we refer readers to reviews by Waddell and Quinn (2001), Keene and Waddell (2007), Cognigni et al. (2018), Modi et al. (2020), and Davis (2023).

Acknowledgments

Work in the Waddell laboratory is supported by an ERC Advanced grant (789274), Wellcome Collaborative Awards (203261 and 209235), and a Wellcome Discovery Award (225192).

References

  1. Abdelfattah AS, Zheng J, Singh A, Huang YC, Reep D, Tsegaye G, Tsang A, Arthur BJ, Rehorova M, Olson CVL, et al. Sensitivity optimization of a rhodopsin-based fluorescent voltage indicator. Neuron. 2023;111:1547–1563.:e9. doi: 10.1016/j.neuron.2023.03.009. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Albin SD, Kaun KR, Knapp JM, Chung P, Heberlein U, Simpson JH. A subset of serotonergic neurons evokes hunger in adult Drosophila. Curr Biol. 2015;25:2435–2440. doi: 10.1016/j.cub.2015.08.005. [DOI] [PubMed] [Google Scholar]
  3. Aso Y, Siwanowicz I, Bräcker L, Ito K, Kitamoto T, Tanimoto H. Specific dopaminergic neurons for the formation of labile aversive memory. Curr Biol. 2010;20:1445–1451. doi: 10.1016/j.cub.2010.06.048. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Aso Y, Hattori D, Yu Y, Johnston RM, Iyer NA, Ngo TT, Dionne H, Abbott LF, Axel R, Tanimoto H, et al. The neuronal architecture of the mushroom body provides a logic for associative learning. eLife. 2014;3:e04577. doi: 10.7554/eLife.04577. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Burke CJ, Waddell S. Remembering nutrient quality of sugar in Drosophila. Curr Biol. 2011;21:746–750. doi: 10.1016/j.cub.2011.03.032. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Burke CJ, Huetteroth W, Owald D, Perisse E, Krashes MJ, Das G, Gohl D, Silies M, Certel S, Waddell S. Layered reward signalling through octopamine and dopamine in Drosophila. Nature. 2012;492:433–437. doi: 10.1038/nature11614. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Chamberland S, Yang HH, Pan MM, Evans SW, Guan S, Chavarha M, Yang Y, Salesse C, Wu H, Wu JC, et al. Fast two-photon imaging of subcellular voltage dynamics in neuronal tissue with genetically encoded indicators. eLife. 2017;6:e25690. doi: 10.7554/eLife.25690. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Chouhan NS, Griffith LC, Haynes P, Sehgal A. Availability of food determines the need for sleep in memory consolidation. Nature. 2021;589:582–585. doi: 10.1038/s41586-020-2997-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Claridge-Chang A, Roorda RD, Vrontou E, Sjulson L, Li H, Hirsh J, Miesenböck G. Writing memories with light-addressable reinforcement circuitry. Cell. 2009;139:405–415. doi: 10.1016/j.cell.2009.08.034. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Cognigni P, Felsenberg J, Waddell S. Do the right thing: neural network mechanisms of memory formation, expression and update in Drosophila. Curr Opin Neurobiol. 2018;49:51–58. doi: 10.1016/j.conb.2017.12.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Colomb J, Kaiser L, Chabaud MA, Preat T. Parametric and genetic analysis of Drosophila appetitive long-term memory and sugar motivation. Genes Brain Behav. 2009;8:407–415. doi: 10.1111/j.1601-183X.2009.00482.x. [DOI] [PubMed] [Google Scholar]
  12. Das G, Klappenbach M, Vrontou E, Perisse E, Clark CM, Burke CJ, Waddell S. Drosophila learn opposing components of a compound food stimulus. Curr Biol. 2014;24:1723–1730. doi: 10.1016/j.cub.2014.05.078. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Davis RL. Learning and memory using Drosophila melanogaster: a focus on advances made in the fifth decade of research. Genetics. 2023;224:iyad085. doi: 10.1093/genetics/iyad085. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Dietzl G, Chen D, Schnorrer F, Su KC, Barinova Y, Fellner M, Gasser B, Kinsey K, Oppel S, Scheiblauer S, et al. A genome-wide transgenic RNAi library for conditional gene inactivation in Drosophila. Nature. 2007;448:151–156. doi: 10.1038/nature05954. [DOI] [PubMed] [Google Scholar]
  15. Ebbinghaus H. Über das gedächtnis: untersuchungen zur experimentellen psychologie. Duncker & Humblot; Berlin: 1885. [Google Scholar]
  16. Felsenberg J, Barnstedt O, Cognigni P, Lin S, Waddell S. Re-evaluation of learned information in Drosophila. Nature. 2017;544:240–244. doi: 10.1038/nature21716. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Felsenberg J, Jacob PF, Walker T, Barnstedt O, Edmondson-Stait AJ, Pleijzier MW, Otto N, Schlegel P, Sharifi N, Perisse E, et al. Integration of parallel opposing memories underlies memory extinction. Cell. 2018;175:709–722.:e15. doi: 10.1016/j.cell.2018.08.021. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Gohl DM, Silies MA, Gao XJ, Bhalerao S, Luongo FJ, Lin CC, Potter CJ, Clandinin TR. A versatile in vivo system for directed dissection of gene expression patterns. Nat Methods. 2011;8:231–237. doi: 10.1038/nmeth.1561. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Hamada FN, Rosenzweig M, Kang K, Pulver SR, Ghezzi A, Jegla TJ, Garrity PA. An internal thermal sensor controlling temperature preference in Drosophila. Nature. 2008;454:217–220. doi: 10.1038/nature07001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Hu Y, Comjean A, Rodiger J, Liu Y, Gao Y, Chung V, Zirin J, Perrimon N, Mohr SE. FlyRNAi.org—the database of the Drosophila RNAi screening center and transgenic RNAi project: 2021 update. Nucleic Acids Res. 2021;49:D908–D915. doi: 10.1093/nar/gkaa936. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Huetteroth W, Perisse E, Lin S, Klappenbach M, Burke C, Waddell S. Sweet taste and nutrient value subdivide rewarding dopaminergic neurons in Drosophila. Curr Biol. 2015;25:751–758. doi: 10.1016/j.cub.2015.01.036. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Jacob PF, Waddell S. Spaced training forms complementary long-term memories of opposite valence in Drosophila. Neuron. 2020;106:977–991.:e4. doi: 10.1016/j.neuron.2020.03.013. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Jacob PF, Vargas-Gutierrez P, Okray Z, Vietti-Michelina S, Felsenberg J, Waddell S. Prior experience conditionally inhibits the expression of new learning in Drosophila. Curr Biol. 2021;31:3490–3503.:e3. doi: 10.1016/j.cub.2021.05.056. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Jenett A, Rubin GM, Ngo TT, Shepherd D, Murphy C, Dionne H, Pfeiffer BD, Cavallaro A, Hall D, Jeter J, et al. A GAL4-driver line resource for Drosophila neurobiology. Cell Rep. 2012;2:991–1001. doi: 10.1016/j.celrep.2012.09.011. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Jing M, Li Y, Zeng J, Huang P, Skirzewski M, Kljakic O, Peng W, Qian T, Tan K, Zou J, et al. An optimized acetylcholine sensor for monitoring in vivo cholinergic activity. Nat Methods. 2020;17:1139–1146. doi: 10.1038/s41592-020-0953-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Jovanoski KD, Duquenoy L, Mitchell J, Kapoor I, Treiber CD, Croset V, Dempsey G, Parepalli S, Cognigni P, Otto N, et al. Dopaminergic systems create reward seeking despite adverse consequences. Nature. 2023;623:356–365. doi: 10.1038/s41586-023-06671-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Kannan M, Vasan G, Haziza S, Huang C, Chrapkiewicz R, Luo J, Cardin JA, Schnitzer MJ, Pieribone VA. Dual-polarity voltage imaging of the concurrent dynamics of multiple neuron types. Science. 2022;378:eabm8797. doi: 10.1126/science.abm8797. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Keene AC, Waddell S. Drosophila olfactory memory: single genes to complex neural circuits. Nat Rev Neurosci. 2007;8:341–354. doi: 10.1038/nrn2098. [DOI] [PubMed] [Google Scholar]
  29. Kitamoto T. Conditional modification of behavior in Drosophila by targeted expression of a temperature-sensitive shibire allele in defined neurons. J Neurobiol. 2001;47:81–92. doi: 10.1002/neu.1018. [DOI] [PubMed] [Google Scholar]
  30. Klapoetke NC, Murata Y, Kim SS, Pulver SR, Birdsey-Benson A, Cho YK, Morimoto TK, Chuong AS, Carpenter EJ, Tian Z, et al. Independent optical excitation of distinct neural populations. Nat Methods. 2014;11:338–346. doi: 10.1038/nmeth.2836. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Krashes MJ, Waddell S. Rapid consolidation to a radish and protein synthesis-dependent long-term memory after single-session appetitive olfactory conditioning in Drosophila. J Neurosci. 2008;28:3103–3113. doi: 10.1523/JNEUROSCI.5333-07.2008. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Krashes MJ, DasGupta S, Vreede A, White B, Armstrong JD, Waddell S. A neural circuit mechanism integrating motivational state with memory expression in Drosophila. Cell. 2009;139:416–427. doi: 10.1016/j.cell.2009.08.035. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Lee T, Luo L. Mosaic analysis with a repressible cell marker for studies of gene function in neuronal morphogenesis. Neuron. 1999;22:451–461. doi: 10.1016/s0896-6273(00)80701-1. [DOI] [PubMed] [Google Scholar]
  34. Lee WP, Chiang MH, Chang LY, Lee JY, Tsai YL, Chiu TH, Chiang HC, Fu TF, Wu T, Wu CL. Mushroom body subsets encode CREB2-dependent water-reward long-term memory in Drosophila. PLoS Genet. 2020;16:e1008963. doi: 10.1371/journal.pgen.1008963. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Lima SQ, Miesenböck G. Remote control of behavior through genetically targeted photostimulation of neurons. Cell. 2005;121:141–152. doi: 10.1016/j.cell.2005.02.004. [DOI] [PubMed] [Google Scholar]
  36. Lin S, Owald D, Chandra V, Talbot C, Huetteroth W, Waddell S. Neural correlates of water reward in thirsty Drosophila. Nat Neurosci. 2014;17:1536–1542. doi: 10.1038/nn.3827. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Liu C, Plaçais PY, Yamagata N, Pfeiffer BD, Aso Y, Friedrich AB, Siwanowicz I, Rubin GM, Preat T, Tanimoto H. A subset of dopamine neurons signals reward for odour memory in Drosophila. Nature. 2012;488:512–516. doi: 10.1038/nature11304. [DOI] [PubMed] [Google Scholar]
  38. Luan H, Diao F, Scott RL, White BH. The Drosophila split Gal4 system for neural circuit mapping. Front Neural Circ. 2020;14:603397. doi: 10.3389/fncir.2020.603397. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. McGinnis JP, Jiang H, Agha MA, Sanchez CP, Lange J, Yu Z, Marion-Poll F, Si K. Immediate perception of a reward is distinct from the reward’s long-term salience. eLife. 2016;5:e22283. doi: 10.7554/eLife.22283. [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Meschi E, Duquenoy L, Otto N, Dempsey G, Waddell S. Compensatory enhancement of input maintains aversive dopaminergic reinforcement in hungry Drosophila. Neuron. 2024;112:2315–2332.:e8. doi: 10.1016/j.neuron.2024.04.035. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Modi MN, Shuai Y, Turner GC. The Drosophila mushroom body: from architecture to algorithm in a learning circuit. Annu Rev Neurosci. 2020;43:465–484. doi: 10.1146/annurev-neuro-080317-0621333. [DOI] [PubMed] [Google Scholar]
  42. Mohamed GA, Cheng RK, Ho J, Krishnan S, Mohammad F, Claridge-Chang A, Jesuthasan S. Optical inhibition of larval zebrafish behaviour with anion channelrhodopsins. BMC Biol. 2017;15:103. doi: 10.1186/s12915-017-0430-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Okray Z, Jacob PF, Stern C, Desmond K, Otto N, Talbot CB, Vargas-Gutierrez P, Waddell S. Multisensory learning binds neurons into a cross-modal memory engram. Nature. 2023;617:777–784. doi: 10.1038/s41586-023-06013-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Okray Z, Jacob PF, Moszynski JP, Talbot CB, Wadell S. Classical conditioning of adult Drosophila. Cold Spring Harb Protoc. 2024 doi: 10.1101/pdb.prot108566. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Ott S, Xu S, Lee N, Hong I, Anns J, Suresh DD, Zhang Z, Zhang X, Harion R, Ye W, et al. Kalium channelrhodopsins effectively inhibit neurons. Nat Commun. 2024;15:3480. doi: 10.1038/s41467-024-47203-w. [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Perisse E, Owald D, Barnstedt O, Talbot CB, Huetteroth W, Waddell S. Aversive learning and appetitive motivation toggle feed-forward inhibition in the Drosophila mushroom body. Neuron. 2016;90:1086–1099. doi: 10.1016/j.neuron.2016.04.034. [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. Pfeiffer BD, Ngo TT, Hibbard KL, Murphy C, Jenett A, Truman JW, Rubin GM. Refinement of tools for targeted gene expression in Drosophila. Genetics. 2010;186:735–755. doi: 10.1534/genetics.110.119917. [DOI] [PMC free article] [PubMed] [Google Scholar]
  48. Quinn WG, Harris WA, Benzer S. Conditioned behavior in Drosophila melanogaster. Proc Natl Acad Sci. 1974;71:708–712. doi: 10.1073/pnas.71.3.708. [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Sabandal JM, Berry JA, Davis RL. Dopamine-based mechanism for transient forgetting. Nature. 2021;591:426–430. doi: 10.1038/s41586-020-03154-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
  50. Schroll C, Riemensperger T, Bucher D, Ehmer J, Voller T, Erbguth K, Gerber B, Hendel T, Nagel G, Buchner E, et al. Light-induced activation of distinct modulatory neurons triggers appetitive or aversive learning in Drosophila larvae. Curr Biol. 2006;16:1741–1747. doi: 10.1016/j.cub.2006.07.023. [DOI] [PubMed] [Google Scholar]
  51. Senapati B, Tsao CH, Juan YA, Chiu TH, Wu CL, Waddell S, Lin S. A neural mechanism for deprivation state-specific expression of relevant memories in Drosophila. Nat Neurosci. 2019;22:2029–2039. doi: 10.1038/s41593-019-0515-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
  52. Sun F, Zhou J, Dai B, Qian T, Zeng J, Li X, Zhuo Y, Zhang Y, Wang Y, Qian C, et al. Next-generation GRAB sensors for monitoring dopaminergic activity in vivo. Nat Methods. 2020;17:1156–1166. doi: 10.1038/s41592-020-00981-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  53. Sutcliffe B, Ng J, Auer TO, Pasche M, Benton R, Jefferis GS, Cachero S. Second-generation Drosophila chemical tags: sensitivity, versatility, and speed. Genetics. 2017;205:1399–1408. doi: 10.1534/genetics.116.199281. [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Tempel BL, Bonini N, Dawson DR, Quinn WG. Reward learning in normal and mutant Drosophila. Proc Natl Acad Sci. 1983;80:1482–1486. doi: 10.1073/pnas.80.5.1482. [DOI] [PMC free article] [PubMed] [Google Scholar]
  55. Thiagarajan D, Eberl F, Veit D, Hansson BS, Knaden M, Sachse S. Aversive bimodal associations differently impact visual and olfactory memory performance in Drosophila. iScience. 2022;25:105485. doi: 10.1016/j.isci.2022.105485. [DOI] [PMC free article] [PubMed] [Google Scholar]
  56. Tirian L, Dickson BJ. The VT GAL4, LexA, and split-GAL4 driver line collections for targeted expression in the Drosophila nervous system. bioRxiv. 2017 doi: 10.1101/198648. [DOI] [Google Scholar]
  57. Tully T, Quinn WG. Classical conditioning and retention in normal and mutant Drosophila melanogaster. J Comp Physiol. 1985;157:263–277. doi: 10.1007/BF01350033. [DOI] [PubMed] [Google Scholar]
  58. Tully T, Preat T, Boynton SC, Del VM. Genetic dissection of consolidated memory in Drosophila. Cell. 1994;79:35–47. doi: 10.1016/0092-8674(94)90398-0. [DOI] [PubMed] [Google Scholar]
  59. Waddell S, Quinn WG. Flies, genes, and learning. Annu Rev Neurosci. 2001;24:1283–1309. doi: 10.1146/annurev.neuro.24.1.1283. [DOI] [PubMed] [Google Scholar]
  60. Wang CM, Wu CY, Lin CE, Hsu MC, Lin JC, Huang CC, Lien TY, Lin HK, Chang TW, Chiang HC. Forgotten memory storage and retrieval in Drosophila. Nat Commun. 2023;14:7153. doi: 10.1038/s41467-023-42753-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  61. Yang Q, Zhou J, Wang L, Hu W, Zhong Y, Li Q. Spontaneous recovery of reward memory through active forgetting of extinction memory. Curr Biol. 2023;33:838–848.:e3. doi: 10.1016/j.cub.2023.01.022. [DOI] [PubMed] [Google Scholar]
  62. Zhang Y, Rózsa M, Liang Y, Bushey D, Wei Z, Zheng J, Reep D, Broussard GJ, Tsang A, Tsegaye G, et al. Fast and sensitive GCaMP calcium indicators for imaging neural populations. Nature. 2023;615:884–891. doi: 10.1038/s41586-023-05828-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  63. Zhao B, Sun J, Zhang X, Mo H, Niu Y, Li Q, Wang L, Zhong Y. Long-term memory is formed immediately without the need for protein synthesis-dependent consolidation in Drosophila. Nat Commun. 2019;10:4550. doi: 10.1038/s41467-019-12436-7. [DOI] [PMC free article] [PubMed] [Google Scholar]

RESOURCES