Inference-based decision-making, which underlies a broad range of behavioral tasks, is typically studied using a small number of handcrafted models. We instead enumerate a complete ensemble of strategies that could be used to effectively, but not necessarily optimally, solve a dynamic foraging task. Each strategy is expressed as a behavioral "program" that uses a limited number of internal states to specify actions conditioned on past observations. We show that the ensemble of strategies is enormous-comprising a quarter million programs with up to five internal states-but can nevertheless be understood in terms of algorithmic "mutations" that alter the structure of individual programs. We devise embedding algorithms that reveal how mutations away from a Bayesian-like strategy can diversify behavior while preserving performance, and we construct a compositional description to link low-dimensional changes in algorithmic structure with high-dimensional changes in behavior. Together, this work provides an alternative approach for understanding individual variability in behavior across animals and tasks.

Until recent advancements in genome editing via CRISPR/Cas9 technology, understanding protein function typically involved artificially overexpressing proteins of interest. Despite that CRISPR/Cas9 has ushered in a new era of possibilities for modifying endogenous genes with labeling tags (knock-in) to more accurately study proteins under physiological conditions, the technique is largely underutilized due to its tedious, multi-step process. Here we outline a homologous recombination system (FAST-HDR) to be used in combination with CRISPR/Cas9 that significantly simplifies and accelerates this process while introducing multiplexing to allow live-cell studies of 3 endogenous proteins within the same cell line. Furthermore, the recombination vectors are assembled in a single reaction that is enhanced for eliminating false positives and reduces the overall creation time for the knockin cell line from ~8 weeks to <15 days. Finally, the system utilizes a modular construction to allow for seamlessly swapping labeling tags to ensure flexibility according to the area under study. We validated this new methodology by developing advanced cell lines with 3 fluorescent-labeled endogenous proteins that support high-content phenotypic drug screening without using antibodies or exogenous staining. Therefore, Fast-HDR cell lines provide a robust alternative for studying multiple proteins of interest in live cells without artificially overexpressing labeled proteins.

Animal behaviour arises from computations in neuronal circuits, but our understanding of these computations has been frustrated by the lack of detailed synaptic connection maps, or connectomes. For example, despite intensive investigations over half a century, the neuronal implementation of local motion detection in the insect visual system remains elusive. Here we develop a semi-automated pipeline using electron microscopy to reconstruct a connectome, containing 379 neurons and 8,637 chemical synaptic contacts, within the Drosophila optic medulla. By matching reconstructed neurons to examples from light microscopy, we assigned neurons to cell types and assembled a connectome of the repeating module of the medulla. Within this module, we identified cell types constituting a motion detection circuit, and showed that the connections onto individual motion-sensitive neurons in this circuit were consistent with their direction selectivity. Our results identify cellular targets for future functional investigations, and demonstrate that connectomes can provide key insights into neuronal computations.

We have developed a miniature telemetry system that captures neural, EMG, and acceleration signals from a freely moving insect and transmits the data wirelessly to a remote digital receiver. The system is based on a custom low-power integrated circuit that amplifies and digitizes four biopotential signals as well as three acceleration signals from an off-chip MEMS accelerometer, and transmits this information over a wireless 920-MHz telemetry link. The unit weighs 0.79 g and runs for two hours on two small batteries. We have used this system to monitor neural and EMG signals in jumping and flying locusts.

Electrons, because of their strong interaction with matter, produce high-resolution diffraction patterns from tiny 3D crystals only a few hundred nanometers thick in a frozen-hydrated state. This discovery offers the prospect of facile structure determination of complex biological macromolecules, which cannot be coaxed to form crystals large enough for conventional crystallography or cannot easily be produced in sufficient quantities. Two potential obstacles stand in the way. The first is a phenomenon known as dynamical scattering, in which multiple scattering events scramble the recorded electron diffraction intensities so that they are no longer informative of the crystallized molecule. The second obstacle is the lack of a proven means of de novo phase determination, as is required if the molecule crystallized is insufficiently similar to one that has been previously determined. We show with four structures of the amyloid core of the Sup35 prion protein that, if the diffraction resolution is high enough, sufficiently accurate phases can be obtained by direct methods with the cryo-EM method microelectron diffraction (MicroED), just as in X-ray diffraction. The success of these four experiments dispels the concern that dynamical scattering is an obstacle to ab initio phasing by MicroED and suggests that structures of novel macromolecules can also be determined by direct methods.

BACKGROUND: Female sexual receptivity offers an excellent model for complex behavioral decisions. The female must parse her own reproductive state, the external environment, and male sensory cues to decide whether to copulate. In the fly Drosophila melanogaster, virgin female receptivity has received relatively little attention, and its neural circuitry and individual behavioral components remain unmapped. Using a genome-wide neuronal RNAi screen, we identify a subpopulation of neurons responsible for pausing, a novel behavioral aspect of virgin female receptivity characterized in this study.

RESULTS: We show that Abdominal-B (Abd-B), a homeobox transcription factor, is required in developing neurons for high levels of virgin female receptivity. Silencing adult Abd-B neurons significantly decreased receptivity. We characterize two components of receptivity that are elicited in sexually mature females by male courtship: pausing and vaginal plate opening. Silencing Abd-B neurons decreased pausing but did not affect vaginal plate opening, demonstrating that these two components of female sexual behavior are functionally separable. Synthetic activation of Abd-B neurons increased pausing, but male courtship song alone was not sufficient to elicit this behavior.

CONCLUSIONS: Our results provide an entry point to the neural circuit controlling virgin female receptivity. The female integrates multiple sensory cues from the male to execute discrete motor programs prior to copulation. Abd-B neurons control pausing, a key aspect of female sexual receptivity, in response to male courtship.

Down syndrome (DS) is a genetic disorder that causes cognitive impairment. The staggering effects associated with an extra copy of human chromosome 21 (HSA21) complicates mechanistic understanding of DS pathophysiology. We examined the neuron-astrocyte interplay in a fully recapitulated HSA21 trisomy cellular model differentiated from DS-patient-derived induced pluripotent stem cells (iPSCs). By combining calcium imaging with genetic approaches, we discovered the functional defects of DS astroglia and their effects on neuronal excitability. Compared with control isogenic astroglia, DS astroglia exhibited more-frequent spontaneous calcium fluctuations, which reduced the excitability of co-cultured neurons. Furthermore, suppressed neuronal activity could be rescued by abolishing astrocytic spontaneous calcium activity either chemically by blocking adenosine-mediated signaling or genetically by knockdown of inositol triphosphate (IP3) receptors or S100B, a calcium binding protein coded on HSA21. Our results suggest a mechanism by which DS alters the function of astrocytes, which subsequently disturbs neuronal excitability.

Medial frontal cortical areas are thought to play a critical role in the brain's ability to flexibly deploy strategies that are effective in complex settings. Still, the specific circuit computations that underpin this foundational aspect of intelligence remain unclear. Here, by examining neural ensemble activity in rats that sample different strategies in a self-guided search for latent task structure, we demonstrate a robust tracking of individual strategy prevalence in the anterior cingulate cortex (ACC), especially in an area homologous to primate area 32D. Prevalence encoding in the ACC is wide-scale, independent of reward delivery, and persists through a substantial ensemble reorganization that tags ACC representations with contextual content. Our findings argue that ACC ensemble dynamics is structured by a summary statistic of recent behavioral choices, raising the possibility that ACC plays a role in estimating - through statistical learning - which actions promote the occurrence of events in the environment.

Recent advances in automatic image segmentation and synapse prediction in electron microscopy (EM) datasets of the brain enable more efficient reconstruction of neural connectivity. In these datasets, a single neuron can span thousands of images containing complex tree-like arbors with thousands of synapses. While image segmentation algorithms excel within narrow fields of views, the algorithms sometimes struggle to correctly segment large neurons, which require large context given their size and complexity. Conversely, humans are comparatively good at reasoning with large objects. In this paper, we introduce several semi-automated strategies that combine 3D visualization and machine guidance to accelerate connectome reconstruction. In particular, we introduce a strategy to quickly correct a segmentation through merging and cleaving, or splitting a segment along supervoxel boundaries, with both operations driven by affinity scores in the underlying segmentation. We deploy these algorithms as streamlined workflows in a tool called Neu3 and demonstrate superior performance compared to prior work, thus enabling efficient reconstruction of much larger datasets. The insights into proofreading from our work clarify the trade-offs to consider when tuning the parameters of image segmentation algorithms.

Profile hidden Markov models (profile HMMs) and probabilistic inference methods have made important contributions to the theory of sequence database homology search. However, practical use of profile HMM methods has been hindered by the computational expense of existing software implementations. Here I describe an acceleration heuristic for profile HMMs, the "multiple segment Viterbi" (MSV) algorithm. The MSV algorithm computes an optimal sum of multiple ungapped local alignment segments using a striped vector-parallel approach previously described for fast Smith/Waterman alignment. MSV scores follow the same statistical distribution as gapped optimal local alignment scores, allowing rapid evaluation of significance of an MSV score and thus facilitating its use as a heuristic filter. I also describe a 20-fold acceleration of the standard profile HMM Forward/Backward algorithms using a method I call "sparse rescaling". These methods are assembled in a pipeline in which high-scoring MSV hits are passed on for reanalysis with the full HMM Forward/Backward algorithm. This accelerated pipeline is implemented in the freely available HMMER3 software package. Performance benchmarks show that the use of the heuristic MSV filter sacrifices negligible sensitivity compared to unaccelerated profile HMM searches. HMMER3 is substantially more sensitive and 100- to 1000-fold faster than HMMER2. HMMER3 is now about as fast as BLAST for protein searches.