SummaryDuring olfactory learning in fruit flies, dopaminergic neurons assign value to odor representations in the mushroom body Kenyon cells. Here we identify a class of downstream glutamatergic mushroom body output neurons (MBONs) called M4/6, or MBON-β2β′2a, MBON-β′2mp, and MBON-γ5β′2a, whose dendritic fields overlap with dopaminergic neuron projections in the tips of the β, β′, and γ lobes. This anatomy and their odor tuning suggests that M4/6 neurons pool odor-driven Kenyon cell synaptic outputs. Like that of mushroom body neurons, M4/6 output is required for expression of appetitive and aversive memory performance. Moreover, appetitive and aversive olfactory conditioning bidirectionally alters the relative odor-drive of M4β′ neurons (MBON-β′2mp). Direct block of M4/6 neurons in naive flies mimics appetitive conditioning, being sufficient to convert odor-driven avoidance into approach, while optogenetically activating these neurons induces avoidance behavior. We therefore propose that drive to the M4/6 neurons reflects odor-directed behavioral choice.
SummaryAccurately predicting an outcome requires that animals learn supporting and conflicting evidence from sequential experience. In mammals and invertebrates, learned fear responses can be suppressed by experiencing predictive cues without punishment, a process called memory extinction. Here, we show that extinction of aversive memories in Drosophila requires specific dopaminergic neurons, which indicate that omission of punishment is remembered as a positive experience. Functional imaging revealed co-existence of intracellular calcium traces in different places in the mushroom body output neuron network for both the original aversive memory and a new appetitive extinction memory. Light and ultrastructural anatomy are consistent with parallel competing memories being combined within mushroom body output neurons that direct avoidance. Indeed, extinction-evoked plasticity in a pair of these neurons neutralizes the potentiated odor response imposed in the network by aversive learning. Therefore, flies track the accuracy of learned expectations by accumulating and integrating memories of conflicting events.
HighlightsRecurrent connectivity is anatomically and functionally prevalent in fly memory circuits.Sustained reverberant activity is necessary for memory consolidation.Feedforward inhibitory neurons impose state control on memory retrieval and behavior.Recurrent circuits enable re-evaluation and updating of memory.
SummaryMemories are stored in the fan-out fan-in neural architectures of the mammalian cerebellum and hippocampus and the insect mushroom bodies. However, whereas key plasticity occurs at glutamatergic synapses in mammals, the neurochemistry of the memory-storing mushroom body Kenyon cell output synapses is unknown. Here we demonstrate a role for acetylcholine (ACh) in Drosophila. Kenyon cells express the ACh-processing proteins ChAT and VAChT, and reducing their expression impairs learned olfactory-driven behavior. Local ACh application, or direct Kenyon cell activation, evokes activity in mushroom body output neurons (MBONs). MBON activation depends on VAChT expression in Kenyon cells and is blocked by ACh receptor antagonism. Furthermore, reducing nicotinic ACh receptor subunit expression in MBONs compromises odor-evoked activation and redirects odor-driven behavior. Lastly, peptidergic corelease enhances ACh-evoked responses in MBONs, suggesting an interaction between the fast- and slow-acting transmitters. Therefore, olfactory memories in Drosophila are likely stored as plasticity of cholinergic synapses.
Animals constantly reassess the reliability of learned information to optimize their behavior. On retrieval, consolidated long-term memory can be neutralized by extinction if the learned prediction was inaccurate 1. Alternatively, retrieved memory can be maintained, following a period of reconsolidation during which it is labile 2. Although extinction and reconsolidation provide opportunities to alleviate problematic human memories 3–5, we lack a detailed mechanistic understanding of memory updating processes. Here we identify neural operations underpinning re-evaluation of memory in Drosophila. Reactivation of sugar-reinforced olfactory memory can lead to either extinction or reconsolidation, depending on prediction accuracy. Each process recruits activity in specific parts of the mushroom body output network and distinct subsets of reinforcing dopaminergic neurons. Memory extinction requires output neurons with dendrites in the α and α′ lobes of the mushroom body, which drive negatively reinforcing dopaminergic neurons that innervate neighbouring zones. The aversive valence of these new extinction memories neutralizes previously learned odor preference. Memory reconsolidation requires the γ2α′ 1 mushroom body output neurons. This pathway recruits negatively reinforcing dopaminergic neurons innervating the same compartment and re-engages positively reinforcing dopaminergic neurons to reconsolidate the original reward memory. These data establish that recurrent and hierarchical connectivity between mushroom body output neurons and dopaminergic neurons enables memory re-evaluation driven by reward prediction error.
Conditioned behavior as observed during classical conditioning in a group of identically treated animals provides insights into the physiological process of learning and memory formation. However, several studies in vertebrates found a remarkable difference between the group-average behavioral performance and the behavioral characteristics of individual animals. Here, we analyzed a large number of data (1640 animals) on olfactory conditioning in the honeybee (Apis mellifera). The data acquired during absolute and differential classical conditioning differed with respect to the number of conditioning trials, the conditioned odors, the intertrial intervals, and the time of retention tests. We further investigated data in which animals were tested for spontaneous recovery from extinction. In all data sets we found that the gradually increasing group-average learning curve did not adequately represent the behavior of individual animals. Individual behavior was characterized by a rapid and stable acquisition of the conditioned response (CR), as well as by a rapid and stable cessation of the CR following unrewarded stimuli. In addition, we present and evaluate different model hypotheses on how honeybees form associations during classical conditioning by implementing a gradual learning process on the one hand and an all-or-none learning process on the other hand. In summary, our findings advise that individual behavior should be recognized as a meaningful predictor for the internal state of a honeybee-irrespective of the group-average behavioral performance.Learning and memory formation in vertebrates and invertebrates have been studied on the basis of a large range of classical and operant conditioning paradigms. Typically, the interpretation of experimental results relies on performance measures that were derived by averaging over behavioral observations from identically treated animals. However, several studies have recognized the inadequacy of group-average measures to capture the characteristics of individual behavior and, consequently, the learninginduced changes in individual brains (Krechevsky 1932;Restle 1965;Hanson and Killeen 1981;Estes 2002;Brown and Heathcote 2003;Cousineau et al. 2003). Most notably, Gallistel et al. (2004) found that the gradually increasing learning curve observed in many vertebrate learning paradigms reflected an artifact of group averaging. The behavioral performance of individuals appeared to be characterized by an abrupt and often step-like increase in the level of response.To our knowledge and in contrast to the vertebrate literature (see Gallistel et al. 2004), surprisingly little is known of a possibly heterogeneous expression of behavior for the most frequently applied invertebrate conditioning paradigms. For the fruit fly (Drosophila melanogaster) it appears to be common sense that the group-average behavioral measures adequately represent the probabilistic expression of behavior in individuals-a notion that goes back to an early study by Quinn et al. (1974).In the following,...
Honeybees (Apis mellifera) are well known for their communication and orientation skills and for their impressive learning capability 1,2 . Because the survival of a honeybee colony depends on the exploitation of food sources, forager bees learn and memorize variable flower sites as well as their profitability. Forager bees can be easily trained in natural settings where they forage at a feeding site and learn the related signals such as odor or color. Appetitive associative learning can also be studied under controlled conditions in the laboratory by conditioning the proboscis extension response (PER) of individually harnessed honeybees 3,4 . This learning paradigm enables the study of the neuronal and molecular mechanisms that underlie learning and memory formation in a simple and highly reliable way [5][6][7][8][9][10][11][12] . A behavioral pharmacology approach is used to study molecular mechanisms. Drugs are injected systemically to interfere with the function of specific molecules during or after learning and memory formation [13][14][15][16] .Here we demonstrate how to train harnessed honeybees in PER conditioning and how to apply drugs systemically by injection into the bee flight muscle. Video LinkThe video component of this article can be found at https://www.jove.com/video/2282/ Protocol 1. Catching Bees from the Hive 1. One day before the experiment starts, between 2 and 4 p.m., bees leaving the hive are caught. To do so, a UV light-permeable plexiglass pyramid (height = 30 cm, apex 3,5 x 3, 5 cm, base 18 x 18 cm), which is closable at the apex and the base, is held at a 20-30 cm distance in front of the hive entrance with the base open and the apex closed so that bees leaving the hive enter the base of the pyramid. The base is then closed and the captured bees are brought into the lab for further handling. Transferring Bees from the Pyramid Into Glass Vials1. In the lab, the pyramid is placed on its base. The walls of the pyramid are darkened (e.g. with a towel) but the apex is left uncovered. Because of their positive phototaxis, bees will leave the pyramid through the apex when opened. One by one, bees are transferred from the pyramid into glass vials by holding the vials over the open apex. One vial is used per bee. Therefore, the apex is closed when one bee enters the vial. Harnessing Bees in Tubes1. Bees are immobilized by cooling them in the glass vials on ice for 2.5-3.5 min. It is advisable to watch the bee and remove it from the ice as soon as it stops moving. 2. A single immobilized bee is harnessed in a small plastic tube with sticky tape, such that it is able to move its proboscis freely but not its head, thorax or legs. It is important that the neck is not compressed. 3. Every bee fixed in a plastic tube is put into a numbered borehole on a rack for better handling and identification. After it has been removed for conditioning or memory retrieval the tube is always returned to the exact same borehole.
Protein degradation is known to affect memory formation after extinction learning. We demonstrate here that an inhibitor of protein degradation, MG132, interferes with memory formation after extinction learning in a classical appetitive conditioning paradigm. In addition, we find an enhancement of memory formation when the same inhibitor is applied after initial learning. This result supports the idea that MG132 targets an ongoing consolidation process. Furthermore, we demonstrate that the sensitivity of memory formation after initial learning and extinction learning to MG132 depends in the same way on the number of CS-US trials and the intertrial interval applied during initial learning. This supports the idea that the learning parameters during acquisition are critical for memory formation after extinction and that protein degradation in both learning processes might be functionally linked.
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