In response to cell death signals, an active apoptosome is assembled from Apaf-1 and procaspase-9 (pc-9). Here we report a near atomic structure of the active human apoptosome determined by cryo-electron microscopy. The resulting model gives insights into cytochrome c binding, nucleotide exchange and conformational changes that drive assembly. During activation an acentric disk is formed on the central hub of the apoptosome. This disk contains four Apaf-1/pc-9 CARD pairs arranged in a shallow spiral with the fourth pc-9 CARD at lower occupancy. On average, Apaf-1 CARDs recruit 3 to 5 pc-9 molecules to the apoptosome and one catalytic domain may be parked on the hub, when an odd number of zymogens are bound. This suggests a stoichiometry of one or at most, two pc-9 dimers per active apoptosome. Thus, our structure provides a molecular framework to understand the role of the apoptosome in programmed cell death and disease.

In Drosophila, the Apaf-1-related killer (Dark) forms an apoptosome that activates procaspases. To investigate function, we have determined a near-atomic structure of Dark double rings using cryo-electron microscopy. We then built a nearly complete model of the apoptosome that includes 7- and 8-blade β-propellers. We find that the preference for dATP during Dark assembly may be governed by Ser325, which is in close proximity to the 2' carbon of the deoxyribose ring. Interestingly, β-propellers in V-shaped domains of the Dark apoptosome are more widely separated, relative to these features in the Apaf-1 apoptosome. This wider spacing may be responsible for the lack of cytochrome c binding to β-propellers in the Dark apoptosome. Our structure also highlights the roles of two loss-of-function mutations that may block Dark assembly. Finally, the improved model provides a framework to understand apical procaspase activation in the intrinsic cell death pathway.

Computing sparse redundant representations is an important problem in both applied mathematics and neuroscience. In many applications, this problem must be solved in an energy-efficient way. Here, we propose a hybrid distributed algorithm (HDA), which solves this problem on a network of simple nodes communicating by low-bandwidth channels. HDA nodes perform both gradient-descent-like steps on analog internal variables and coordinate-descent-like steps via quantized external variables communicated to each other. Interestingly, the operation is equivalent to a network of integrate-and-fire neurons, suggesting that HDA may serve as a model of neural computation. We show that the numerical performance of HDA is on par with existing algorithms. In the asymptotic regime, the representation error of HDA decays with time, t, as 1/t. HDA is stable against time-varying noise; specifically, the representation error decays as 1/√t for gaussian white noise.

Incentives tend to drive improvements in performance. But when incentives get too high, we can "choke under pressure" and underperform right when it matters most. What neural processes might lead to choking under pressure? We studied rhesus monkeys performing a challenging reaching task in which they underperformed when an unusually large "jackpot" reward was at stake, and we sought a neural mechanism that might result in that underperformance. We found that increases in reward drive neural activity during movement preparation into, and then past, a zone of optimal performance. We conclude that neural signals of reward and motor preparation interact in the motor cortex (MC) in a manner that can explain why we choke under pressure.

In pursuit of food, hungry animals mobilize significant energy resources and overcome exhaustion and fear. How need and motivation control the decision to continue or change behavior is not understood. Using a single fly treadmill, we show that hungry flies persistently track a food odor and increase their effort over repeated trials in the absence of reward suggesting that need dominates negative experience. We further show that odor tracking is regulated by two mushroom body output neurons (MBONs) connecting the MB to the lateral horn. These MBONs, together with dopaminergic neurons and Dop1R2 signaling, control behavioral persistence. Conversely, an octopaminergic neuron, VPM4, which directly innervates one of the MBONs, acts as a brake on odor tracking by connecting feeding and olfaction. Together, our data suggest a function for the MB in internal state-dependent expression of behavior that can be suppressed by external inputs conveying a competing behavioral drive.

In pursuit of food, hungry animals mobilize significant energy resources and overcome exhaustion and fear. How need and motivation control the decision to continue or change behavior is not understood. Using a single fly treadmill, we show that hungry flies persistently track a food odor and increase their effort over repeated trials in the absence of reward suggesting that need dominates negative experience. We further show that odor tracking is regulated by two mushroom body output neurons (MBONs) connecting the MB to the lateral horn. These MBONs, together with dopaminergic neurons and Dop1R2 signaling, control behavioral persistence. Conversely, an octopaminergic neuron, VPM4, which directly innervates one of the MBONs, acts as a brake on odor tracking by connecting feeding and olfaction. Together, our data suggest a function for the MB in internal state-dependent expression of behavior that can be suppressed by external inputs conveying a competing behavioral drive.

Anchoring goals to spatial representations enables flexible navigation but is challenging in novel environments when both representations must be acquired simultaneously. We propose a framework for how Drosophila uses internal representations of head direction (HD) to build goal representations upon selective thermal reinforcement. We show that flies use stochastically generated fixations and directed saccades to express heading preferences in an operant visual learning paradigm and that HD neurons are required to modify these preferences based on reinforcement. We used a symmetric visual setting to expose how flies' HD and goal representations co-evolve and how the reliability of these interacting representations impacts behavior. Finally, we describe how rapid learning of new goal headings may rest on a behavioral policy whose parameters are flexible but whose form is genetically encoded in circuit architecture. Such evolutionarily structured architectures, which enable rapidly adaptive behavior driven by internal representations, may be relevant across species.

Female behavior changes profoundly after mating. In Drosophila, the mechanisms underlying the long-term changes led by seminal products have been extensively studied. However, the effect of the sensory component of copulation on the female's internal state and behavior remains elusive. We pursued this question by dissociating the effect of coital sensory inputs from those of male ejaculate. We found that the sensory inputs of copulation cause a reduction of post-coital receptivity in females, referred to as the "copulation effect." We identified three layers of a neural circuit underlying this phenomenon. Abdominal neurons expressing the mechanosensory channel Piezo convey the signal of copulation to female-specific ascending neurons, LSANs, in the ventral nerve cord. LSANs relay this information to neurons expressing myoinhibitory peptides in the brain. We hereby provide a neural mechanism by which the experience of copulation facilitates females encoding their mating status, thus adjusting behavior to optimize reproduction.

Hunger and pain are two competing signals that individuals must resolve to ensure survival. However, the neural processes that prioritize conflicting survival needs are poorly understood. We discovered that hunger attenuates behavioral responses and affective properties of inflammatory pain without altering acute nociceptive responses. This effect is centrally controlled, as activity in hunger-sensitive agouti-related protein (AgRP)-expressing neurons abrogates inflammatory pain. Systematic analysis of AgRP projection subpopulations revealed that the neural processing of hunger and inflammatory pain converge in the hindbrain parabrachial nucleus (PBN). Strikingly, activity in AgRP → PBN neurons blocked the behavioral response to inflammatory pain as effectively as hunger or analgesics. The anti-nociceptive effect of hunger is mediated by neuropeptide Y (NPY) signaling in the PBN. By investigating the intersection between hunger and pain, we have identified a neural circuit that mediates competing survival needs and uncovered NPY Y1 receptor signaling in the PBN as a target for pain suppression.

Animals retain some but not all experiences in long-term memory (LTM). Sleep supports LTM retention across animal species. It is well established that learning experiences enhance post-learning sleep. However, the underlying mechanisms of how learning mediates sleep for memory retention are not clear. Drosophila males display increased amounts of sleep after courtship learning. Courtship learning depends on Mushroom Body (MB) neurons, and post-learning sleep is mediated by the sleep-promoting ventral Fan-Shaped Body neurons (vFBs). We show that post-learning sleep is regulated by two opposing output neurons (MBONs) from the MB, which encode a measure of learning. Excitatory MBONs-γ2α'1 becomes increasingly active upon increasing time of learning, whereas inhibitory MBONs-β'2mp is activated only by a short learning experience. These MB outputs are integrated by SFS neurons, which excite vFBs to promote sleep after prolonged but not short training. This circuit may ensure that only longer or more intense learning experiences induce sleep and are thereby consolidated into LTM.