Electrical synapses between mushroom body neurons are critical for consolidated memory retrieval in Drosophila

Learning with sparse reward in a gap junction network inspired by the insect mushroom body

Animals can learn in real-life scenarios where rewards are often only available when a goal is achieved. This 'distal' or 'sparse' reward problem remains a challenge for conventional reinforcement learning algorithms. Here we investigate an algorithm for learning in such scenarios, inspired by the possibility that axo-axonal gap junction connections, observed in neural circuits with parallel fibres such as the insect mushroom body, could form a resistive network. In such a network, an active node represents the task state, connections between nodes represent state transitions and their connection to actions, and current flow to a target state can guide decision making. Building on evidence that gap junction weights are adaptive, we propose that experience of a task can modulate the connections to form a graph encoding the task structure. We demonstrate that the approach can be used for efficient reinforcement learning under sparse rewards, and discuss whether it is plausible as an account of the insect mushroom body.

Aversive conditioning information transmission in Drosophila

Animals rapidly acquire surrounding information to perform the appropriate behavior. Although social learning is more efficient and accessible than self-learning for animals, the detailed regulatory mechanism of social learning remains unknown, mainly because of the complicated information transfer between animals, especially for aversive conditioning information transmission. The current study revealed that, during social learning, the neural circuit in observer flies used to process acquired aversive conditioning information from demonstrator flies differs from the circuit used for self-learned classic aversive conditioning. This aversive information transfer is species dependent. Solitary flies cannot learn this information through social learning, suggesting that this ability is not an innate behavior. Neurons used to process and execute avoidance behavior to escape from electrically shocked flies are all in the same brain region, indicating that the fly brain has a common center for integrating external stimuli with internal states to generate flight behavior.

A subset of cholinergic mushroom body neurons blocks long-term memory formation in Drosophila

Long-term memory (LTM) requires learning-induced synthesis of new proteins allocated to specific neurons and synapses in a neural circuit. Not all learned information, however, becomes permanent memory. How the brain gates relevant information into LTM remains unclear. In Drosophila adults, weak learning after a single training session in an olfactory aversive task typically does not induce protein-synthesis-dependent LTM. Instead, strong learning after multiple spaced training sessions is required. Here, we report that pre-synaptic active-zone protein synthesis and cholinergic signaling from the early α/β subset of mushroom body (MB) neurons produce a downstream inhibitory effect on LTM formation. When we eliminated inhibitory signaling from these neurons, weak learning was then sufficient to form LTM. This bidirectional circuit mechanism modulates the transition between distinct memory phase functions in different subpopulations of MB neurons in the olfactory memory circuit.

The cellular architecture of memory modules in Drosophila supports stochastic input integration

The ability to associate neutral stimuli with valence information and to store these associations as memories forms the basis for decision making. To determine the underlying computational principles, we build a realistic computational model of a central decision module within the Drosophila mushroom body (MB), the fly's center for learning and memory. Our model combines the electron microscopy-based architecture of one MB output neuron (MBON-α3), the synaptic connectivity of its 948 presynaptic Kenyon cells (KCs), and its membrane properties obtained from patch-clamp recordings. We show that this neuron is electrotonically compact and that synaptic input corresponding to simulated odor input robustly drives its spiking behavior. Therefore, sparse innervation by KCs can efficiently control and modulate MBON activity in response to learning with minimal requirements on the specificity of synaptic localization. This architecture allows efficient storage of large numbers of memories using the flexible stochastic connectivity of the circuit.

Transient active zone remodeling in the Drosophila mushroom body supports memory

Elucidating how the distinct components of synaptic plasticity dynamically orchestrate the distinct stages of memory acquisition and maintenance within neuronal networks remains a major challenge. Specifically, plasticity processes tuning the functional and also structural state of presynaptic active zone (AZ) release sites are widely observed in vertebrates and invertebrates, but their behavioral relevance remains mostly unclear. We here provide evidence that a transient upregulation of presynaptic AZ release site proteins supports aversive olfactory mid-term memory in the Drosophila mushroom body (MB). Upon paired aversive olfactory conditioning, AZ protein levels (ELKS-family BRP/(m)unc13-family release factor Unc13A) increased for a few hours with MB-lobe-specific dynamics. Kenyon cell (KC, intrinsic MB neurons)-specific knockdown (KD) of BRP did not affect aversive olfactory short-term memory (STM) but strongly suppressed aversive mid-term memory (MTM). Different proteins crucial for the transport of AZ biosynthetic precursors (transport adaptor Aplip1/Jip-1; kinesin motor IMAC/Unc104; small GTPase Arl8) were also specifically required for the formation of aversive olfactory MTM. Consistent with the merely transitory increase of AZ proteins, BRP KD did not interfere with the formation of aversive olfactory long-term memory (LTM; i.e., 1 day). Our data suggest that the remodeling of presynaptic AZ refines the MB circuitry after paired aversive conditioning, over a time window of a few hours, to display aversive olfactory memories.

A new path to mental disorders: Through gap junction channels and hemichannels

Behavioral disturbances related to emotional regulation, reward processing, cognition, sleep-wake regulation and activity/movement represent core symptoms of most common mental disorders. Increasing empirical and theoretical evidence suggests that normal functioning of these behavioral domains relies on fine graded coordination of neural and glial networks which are maintained and modulated by intercellular gap junction channels and unapposed pannexin or connexin hemichannels. Dysfunctions in these networks might contribute to the development and maintenance of psychopathological and neurobiological features associated with mental disorders. Here we review and discuss the evidence indicating a prominent role of gap junction channel and hemichannel dysfunction in core symptoms of mental disorders. We further discuss how the increasing knowledge on intercellular gap junction channels and unapposed pannexin or connexin hemichannels in the brain might lead to deeper mechanistic insight in common mental disorders and to the development of novel treatment approaches. We further attempt to exemplify what type of future research on this topic could be integrated into multidimensional approaches to understand and cure mental disorders.

Serotonin Signals Modulate Mushroom Body Output Neurons for Sustaining Water-Reward Long-Term Memory in Drosophila

Memory consolidation is a time-dependent process through which an unstable learned experience is transformed into a stable long-term memory; however, the circuit and molecular mechanisms underlying this process are poorly understood. The Drosophila mushroom body (MB) is a huge brain neuropil that plays a crucial role in olfactory memory. The MB neurons can be generally classified into three subsets: γ, αβ, and α′β′. Here, we report that water-reward long-term memory (wLTM) consolidation requires activity from α′β′-related mushroom body output neurons (MBONs) in a specific time window. wLTM consolidation requires neurotransmission in MBON-γ3β′1 during the 0–2 h period after training, and neurotransmission in MBON-α′2 is required during the 2–4 h period after training. Moreover, neurotransmission in MBON-α′1α′3 is required during the 0–4 h period after training. Intriguingly, blocking neurotransmission during consolidation or inhibiting serotonin biosynthesis in serotoninergic dorsal paired medial (DPM) neurons also disrupted the wLTM, suggesting that wLTM consolidation requires serotonin signals from DPM neurons. The GFP Reconstitution Across Synaptic Partners (GRASP) data showed the connectivity between DPM neurons and MBON-γ3β′1, MBON-α′2, and MBON-α′1α′3, and RNAi-mediated silencing of serotonin receptors in MBON-γ3β′1, MBON-α′2, or MBON-α′1α′3 disrupted wLTM. Taken together, our results suggest that serotonin released from DPM neurons modulates neuronal activity in MBON-γ3β′1, MBON-α′2, and MBON-α′1α′3 at specific time windows, which is critical for the consolidation of wLTM in Drosophila.

Mushroom body subsets encode CREB2-dependent water-reward long-term memory in Drosophila

Long-term memory (LTM) formation depends on the conversed cAMP response element-binding protein (CREB)-dependent gene transcription followed by de novo protein synthesis. Thirsty fruit flies can be trained to associate an odor with water reward to form water-reward LTM (wLTM), which can last for over 24 hours without a significant decline. The role of de novo protein synthesis and CREB-regulated gene expression changes in neural circuits that contribute to wLTM remains unclear. Here, we show that acute inhibition of protein synthesis in the mushroom body (MB) αβ or γ neurons during memory formation using a cold-sensitive ribosome-inactivating toxin disrupts wLTM. Furthermore, adult stage-specific expression of dCREB2b in αβ or γ neurons also disrupts wLTM. The MB αβ and γ neurons can be further classified into five different neuronal subsets including αβ core, αβ surface, αβ posterior, γ main, and γ dorsal. We observed that the neurotransmission from αβ surface and γ dorsal neuron subsets is required for wLTM retrieval, whereas the αβ core, αβ posterior, and γ main are dispensable. Adult stage-specific expression of dCREB2b in αβ surface and γ dorsal neurons inhibits wLTM formation. In vivo calcium imaging revealed that αβ surface and γ dorsal neurons form wLTM traces with different dynamic properties, and these memory traces are abolished by dCREB2b expression. Our results suggest that a small population of neurons within the MB circuits support long-term storage of water-reward memory in Drosophila.

Cellular and circuit mechanisms of olfactory associative learning in Drosophila

Recent years have witnessed significant progress in understanding how memories are encoded, from the molecular to the cellular and the circuit/systems levels. With a good compromise between brain complexity and behavioral sophistication, the fruit fly Drosophila melanogaster is one of the preeminent animal models of learning and memory. Here we review how memories are encoded in Drosophila, with a focus on short-term memory and an eye toward future directions. Forward genetic screens have revealed a large number of genes and transcripts necessary for learning and memory, some acting cell-autonomously. Further, the relative numerical simplicity of the fly brain has enabled the reverse engineering of learning circuits with remarkable precision, in some cases ascribing behavioral phenotypes to single neurons. Functional imaging and physiological studies have localized and parsed the plasticity that occurs during learning at some of the major loci. Connectomics projects are significantly expanding anatomical knowledge of the nervous system, filling out the roadmap for ongoing functional/physiological and behavioral studies, which are being accelerated by simultaneous tool development. These developments have provided unprecedented insight into the fundamental neural principles of learning, and lay the groundwork for deep understanding in the near future.