A single nervous system can generate many distinct motor patterns. Identifying which neurons and circuits control which behaviors has been a laborious piecemeal process, usually for one observer-defined behavior at a time. We present a fundamentally different approach to neuron-behavior mapping. We optogenetically activated 1,054 identified neuron lines in Drosophila larva and tracked the behavioral responses from 37,780 animals. Applying multiscale unsupervised structure learning methods to the behavioral data identified 29 discrete statistically distinguishable and observer-unbiased behavioral phenotypes. Mapping the neural lines to the behavior(s) they evoke provides a behavioral reference atlas for neuron subsets covering a large fraction of larval neurons. This atlas is a starting point for connectivity- and activity-mapping studies to further investigate the mechanisms by which neurons mediate diverse behaviors.

Certain marine invertebrates harbor chemosynthetic bacterial symbionts, giving them the remarkable ability to consume inorganic chemicals such as hydrogen sulfide (H2S) rather than organic matter as food. These chemosynthetic animals are found near geochemical (e.g., hydrothermal vents) or biological (e.g., decaying wood or large animal carcasses) sources of H2S on the seafloor. Although many such symbioses have been discovered, little is known about how or where they originated. Here, we demonstrate a new chemosynthetic symbiosis in the giant teredinid bivalve (shipworm) Kuphus polythalamia and show that this symbiosis arose in a wood-eating ancestor via the displacement of ancestral cellulolytic symbionts by sulfur-oxidizing invaders. Here, wood served as an evolutionary stepping stone for a dramatic transition from heterotrophy to chemoautotrophy.The “wooden-steps” hypothesis [Distel DL, et al. (2000) Nature 403:725–726] proposed that large chemosynthetic mussels found at deep-sea hydrothermal vents descend from much smaller species associated with sunken wood and other organic deposits, and that the endosymbionts of these progenitors made use of hydrogen sulfide from biogenic sources (e.g., decaying wood) rather than from vent fluids. Here, we show that wood has served not only as a stepping stone between habitats but also as a bridge between heterotrophic and chemoautotrophic symbiosis for the giant mud-boring bivalve Kuphus polythalamia. This rare and enigmatic species, which achieves the greatest length of any extant bivalve, is the only described member of the wood-boring bivalve family Teredinidae (shipworms) that burrows in marine sediments rather than wood. We show that K. polythalamia harbors sulfur-oxidizing chemoautotrophic (thioautotrophic) bacteria instead of the cellulolytic symbionts that allow other shipworm species to consume wood as food. The characteristics of its symbionts, its phylogenetic position within Teredinidae, the reduction of its digestive system by comparison with other family members, and the loss of morphological features associated with wood digestion indicate that K. polythalamia is a chemoautotrophic bivalve descended from wood-feeding (xylotrophic) ancestors. This is an example in which a chemoautotrophic endosymbiosis arose by displacement of an ancestral heterotrophic symbiosis and a report of pure culture of a thioautotrophic endosymbiont.

Short-term memories link events separated in time, such as past sensation and future actions. Short-term memories are correlated with slow neural dynamics, including selective persistent activity, which can be maintained over seconds. In a delayed response task that requires short-term memory, neurons in the mouse anterior lateral motor cortex (ALM) show persistent activity that instructs future actions. To determine the principles that underlie this persistent activity, here we combined intracellular and extracellular electrophysiology with optogenetic perturbations and network modelling. We show that during the delay epoch, the activity of ALM neurons moved towards discrete end points that correspond to specific movement directions. These end points were robust to transient shifts in ALM activity caused by optogenetic perturbations. Perturbations occasionally switched the population dynamics to the other end point, followed by incorrect actions. Our results show that discrete attractor dynamics underlie short-term memory related to motor planning.

Each training step for a variational autoencoder (VAE) requires us to sample from the approximate posterior, so we usually choose simple (e.g. factorised) approximate posteriors in which sampling is an efficient computation that fully exploits GPU parallelism. However, such simple approximate posteriors are often insufficient, as they eliminate statistical dependencies in the posterior. While it is possible to use normalizing flow approximate posteriors for continuous latents, some problems have discrete latents and strong statistical dependencies. The most natural approach to model these dependencies is an autoregressive distribution, but sampling from such distributions is inherently sequential and thus slow. We develop a fast, parallel sampling procedure for autoregressive distributions based on fixed-point iterations which enables efficient and accurate variational inference in discrete state-space latent variable dynamical systems. To optimize the variational bound, we considered two ways to evaluate probabilities: inserting the relaxed samples directly into the pmf for the discrete distribution, or converting to continuous logistic latent variables and interpreting the K-step fixed-point iterations as a normalizing flow. We found that converting to continuous latent variables gave considerable additional scope for mismatch between the true and approximate posteriors, which resulted in biased inferences, we thus used the former approach. Using our fast sampling procedure, we were able to realize the benefits of correlated posteriors, including accurate uncertainty estimates for one cell, and accurate connectivity estimates for multiple cells, in an order of magnitude less time.

Animals smelling in the real world use a small number of receptors to sense a vast number of natural molecular mixtures, and proceed to learn arbitrary associations between odors and valences. Here, we propose how the architecture of olfactory circuits leverages disorder, diffuse sensing and redundancy in representation to meet these immense complementary challenges. First, the diffuse and disordered binding of receptors to many molecules compresses a vast but sparsely-structured odor space into a small receptor space, yielding an odor code that preserves similarity in a precise sense. Introducing any order/structure in the sensing degrades similarity preservation. Next, lateral interactions further reduce the correlation present in the low-dimensional receptor code. Finally, expansive disordered projections from the periphery to the central brain reconfigure the densely packed information into a high-dimensional representation, which contains multiple redundant subsets from which downstream neurons can learn flexible associations and valences. Moreover, introducing any order in the expansive projections degrades the ability to recall the learned associations in the presence of noise. We test our theory empirically using data from . Our theory suggests that the neural processing of sparse but high-dimensional olfactory information differs from the other senses in its fundamental use of disorder.

To control reaching, the nervous system must generate large changes in muscle activation to drive the limb toward the target, and must also make smaller adjustments for precise and accurate behavior. Motor cortex controls the arm through projections to diverse targets across the central nervous system, but it has been challenging to identify the roles of cortical projections to specific targets. Here, we selectively disrupt cortico-cerebellar communication in the mouse by optogenetically stimulating the pontine nuclei in a cued reaching task. This perturbation did not typically block movement initiation, but degraded the precision, accuracy, duration, or success rate of the movement. Correspondingly, cerebellar and cortical activity during movement were largely preserved, but differences in hand velocity between control and stimulation conditions predicted from neural activity were correlated with observed velocity differences. These results suggest that while the total output of motor cortex drives reaching, the cortico-cerebellar loop makes small adjustments that contribute to the successful execution of this dexterous movement.

The neuropeptide eclosion hormone (EH) is a key regulator of insect ecdysis. We tested the role of the two EH-producing neurons in Drosophila by using an EH cell-specific enhancer to activate cell death genes reaper and head involution defective to ablate the EH cells. In the EH cell knockout flies, larval and adult ecdyses were disrupted, yet a third of the knockouts emerged as adults, demonstrating that EH has a significant but nonessential role in ecdysis. The EH cell knockouts had discrete behavioral deficits, including slow, uncoordinated eclosion and an insensitivity to ecdysis-triggering hormone. The knockouts lacked the lights-on eclosion response despite having a normal circadian eclosion rhythm. This study represents a novel approach to the dissection of neuropeptide regulation of a complex behavioral program.

Circadian (daily) rhythms are present in almost all plants and animals. In mammals, a brain clock located in the hypothalamic suprachiasmatic nucleus maintains synchrony between environmental light/dark cycles and physiology and behavior. Over the past 100 y, especially with the advent of electric lighting, modern society has resulted in a round-the-clock lifestyle, in which natural connections between rest/activity cycles and environmental light/dark cycles have been degraded or even broken. Instances in which rapid changes to sleep patterns are necessary, such as transmeridian air travel, demonstrate negative effects of acute circadian disruption on physiology and behavior. However, the ramifications of chronic disruption of the circadian clock for mental and physical health are not yet fully understood. By housing mice in 20-h light/dark cycles, incongruous with their endogenous ∼24-h circadian period, we were able to model the effects of chronic circadian disruption noninvasively. Housing in these conditions results in accelerated weight gain and obesity, as well as changes in metabolic hormones. In the brain, circadian-disrupted mice exhibit a loss of dendritic length and decreased complexity of neurons in the prelimbic prefrontal cortex, a brain region important in executive function and emotional control. Disrupted animals show decreases in cognitive flexibility and changes in emotionality consistent with the changes seen in neural architecture. How our findings translate to humans living and working in chronic circadian disruption is unknown, but we believe that this model can provide a foundation to understand how environmental disruption of circadian rhythms impacts the brain, behavior, and physiology.

Small molecules that alter protein function provide a means to modulate biological networks with temporal resolution. Here we demonstrate a potentially general and scalable method of identifying such molecules by application to a particular protein, Ure2p, which represses the transcription factors Gln3p and Nil1p. By probing a high-density microarray of small molecules generated by diversity-oriented synthesis with fluorescently labelled Ure2p, we performed 3,780 protein-binding assays in parallel and identified several compounds that bind Ure2p. One compound, which we call uretupamine, specifically activates a glucose-sensitive transcriptional pathway downstream of Ure2p. Whole-genome transcription profiling and chemical epistasis demonstrate the remarkable Ure2p specificity of uretupamine and its ability to modulate the glucose-sensitive subset of genes downstream of Ure2p. These results demonstrate that diversity-oriented synthesis and small-molecule microarrays can be used to identify small molecules that bind to a protein of interest, and that these small molecules can regulate specific functions of the protein.