Sleep is a fundamental behavioral state important for survival and is universal in animals with sufficiently complex nervous systems. As a highly conserved neurobehavioral state, sleep has been described in species ranging from jellyfish to humans. Biogenic amines like dopamine, serotonin and norepinephrine have been shown to be critical for sleep regulation across species but the precise circuit mechanisms underlying how amines control persistence of sleep, arousal and wakefulness remain unclear. The fruit fly,
Nitric oxide acts as a cotransmitter in a subset of dopaminergic neurons to diversify memory dynamics
Animals employ diverse learning rules and synaptic plasticity dynamics to record temporal and statistical information about the world. However, the molecular mechanisms underlying this diversity are poorly understood. The anatomically defined compartments of the insect mushroom body function as parallel units of associative learning, with different learning rates, memory decay dynamics and flexibility (Aso and Rubin, 2016). Here, we show that nitric oxide (NO) acts as a neurotransmitter in a subset of dopaminergic neurons in Drosophila. NO’s effects develop more slowly than those of dopamine and depend on soluble guanylate cyclase in postsynaptic Kenyon cells. NO acts antagonistically to dopamine; it shortens memory retention and facilitates the rapid updating of memories. The interplay of NO and dopamine enables memories stored in local domains along Kenyon cell axons to be specialized for predicting the value of odors based only on recent events. Our results provide key mechanistic insights into how diverse memory dynamics are established in parallel memory systems.
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- Award ID(s):
- 1707398
- NSF-PAR ID:
- 10174308
- Date Published:
- Journal Name:
- eLife
- Volume:
- 8
- ISSN:
- 2050-084X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Drosophila melanogaster , provides a powerful model system for the study of sleep and circuit mechanisms underlying state transitions and persistence of states to meet the organisms motivational and cognitive needs. InDrosophila , two neuropils in the central brain, the mushroom body (MB) and the central complex (CX) have been shown to influence sleep homeostasis and receive aminergic neuromodulator input critical to sleep–wake switch. Dopamine neurons (DANs) are prevalent neuromodulator inputs to the MB but the mechanisms by which they interact with and regulate sleep- and wake-promoting neurons within MB are unknown. Here we investigate the role of subsets of PAM-DANs that signal wakefulness and project to wake-promoting compartments of the MB. We find that PAM-DANs are GABA responsive and require GABAA-Rdl receptor in regulating sleep. In mapping the pathways downstream of PAM neurons innervating γ5 and β′2 MB compartments we find that wakefulness is regulated by both DopR1 and DopR2 receptors in downstream Kenyon cells (KCs) and mushroom body output neurons (MBONs). Taken together, we have identified and characterized a dopamine modulated sleep microcircuit within the mushroom body that has previously been shown to convey information about positive and negative valence critical for memory formation. These studies will pave way for understanding how flies balance sleep, wakefulness and arousal. -
Block random access memories (BRAMs) are the storage houses of FPGAs, providing extensive on-chip memory bandwidth to the compute units implemented using logic blocks and digital signal processing slices. We propose modifying BRAMs to convert them to CoMeFa (more » « less
Co mpute-in-Me mory Blocks forF PGA s) random access memories (RAMs). These RAMs provide highly parallel compute-in-memory by combining computation and storage capabilities in one block. CoMeFa RAMs utilize the true dual-port nature of FPGA BRAMs and contain multiple configurable single-bit bit-serial processing elements. CoMeFa RAMs can be used to compute with any precision, which is extremely important for applications like deep learning (DL). Adding CoMeFa RAMs to FPGAs significantly increases their compute density while also reducing data movement. We explore and propose two architectures of these RAMs: CoMeFa-D (optimized for delay) and CoMeFa-A (optimized for area). Compared to existing proposals, CoMeFa RAMs do not require changing the underlying static RAM technology like simultaneously activating multiple wordlines on the same port, and are practical to implement. CoMeFa RAMs are especially suitable for parallel and compute-intensive applications like DL, but these versatile blocks find applications in diverse applications like signal processing and databases, among others. By augmenting an Intel Arria 10–like FPGA with CoMeFa-D (CoMeFa-A) RAMs at the cost of 3.8% (1.2%) area, and with algorithmic improvements and efficient mapping, we observe a geomean speedup of 2.55× (1.85×) across microbenchmarks from various applications and a geomean speedup of up to 2.5× across multiple deep neural networks. Replacing all or some BRAMs with CoMeFa RAMs in FPGAs can make them better accelerators of DL workloads. -
Morrison, Abigail (Ed.)The Drosophila mushroom body exhibits dopamine dependent synaptic plasticity that underlies the acquisition of associative memories. Recordings of dopamine neurons in this system have identified signals related to external reinforcement such as reward and punishment. However, other factors including locomotion, novelty, reward expectation, and internal state have also recently been shown to modulate dopamine neurons. This heterogeneity is at odds with typical modeling approaches in which these neurons are assumed to encode a global, scalar error signal. How is dopamine dependent plasticity coordinated in the presence of such heterogeneity? We develop a modeling approach that infers a pattern of dopamine activity sufficient to solve defined behavioral tasks, given architectural constraints informed by knowledge of mushroom body circuitry. Model dopamine neurons exhibit diverse tuning to task parameters while nonetheless producing coherent learned behaviors. Notably, reward prediction error emerges as a mode of population activity distributed across these neurons. Our results provide a mechanistic framework that accounts for the heterogeneity of dopamine activity during learning and behavior.more » « less
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null (Ed.)Abstract Memory consolidation involves the reactivation of memory traces during sleep. If different memories are reactivated each night, how much do they interfere with one another? We examined whether reactivating multiple memories incurs a cost to sleep-related benefits by contrasting reactivation of multiple memories versus single memories during sleep. First, participants learned the on-screen location of different objects. Each object was part of a semantically coherent group comprised of either one, two, or six items (e.g., six different cats). During sleep, sounds were unobtrusively presented to reactivate memories for half of the groups (e.g., “meow”). Memory benefits for cued versus non-cued items were independent of the number of items in the group, suggesting that reactivation occurs in a simultaneous and promiscuous manner. Intriguingly, sleep spindles and delta-theta power modulations were sensitive to group size, reflecting the extent of previous learning. Our results demonstrate that multiple memories may be consolidated in parallel without compromising each memory’s sleep-related benefit. These findings highlight alternative models for parallel consolidation that should be considered in future studies.more » « less
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Abstract Relapse, a critical issue in alcohol addiction, can be attenuated by disruption of alcohol-associated memories. Memories are thought to temporarily destabilize upon retrieval during the reconsolidation process. Here, we provide evidence for unique transcriptional dynamics underpinning alcohol memory reconsolidation. Using a mouse place-conditioning procedure, we show that alcohol-memory retrieval increases the mRNA expression of immediate-early genes in the dorsal hippocampus and medial prefrontal cortex, and that alcohol seeking is abolished by post-retrieval non-specific inhibition of gene transcription, or by downregulating ARC expression using antisense-oligodeoxynucleotides. However, since retrieval of memories for a natural reward (sucrose) also increased the same immediate-early gene expression, we explored for alcohol-specific transcriptional changes using RNA-sequencing. We revealed a unique transcriptional fingerprint activated by alcohol memories, as the expression of this set of plasticity-related genes was not altered by sucrose-memory retrieval. Our results suggest that alcohol memories may activate two parallel transcription programs: one is involved in memory reconsolidation in general, and another is specifically activated during alcohol-memory processing.
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.7554/eLife.49257
