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.

Amyloid fibrils characterize a diverse group of human diseases that includes Alzheimer’s disease, Creutzfeldt-Jakob and type II diabetes. Alzheimer’s amyloid fibrils consist of amyloid-beta (Abeta) peptide and occur in a range of structurally different fibril morphologies. The structural characteristics of 12 single Abeta(1-40) amyloid fibrils, all formed under the same solution conditions, were determined by electron cryo-microscopy and three-dimensional reconstruction. The majority of analyzed fibrils form a range of morphologies that show almost continuously altering structural properties. The observed fibril polymorphism implies that amyloid formation can lead, for the same polypeptide sequence, to many different patterns of inter- or intra-residue interactions. This property differs significantly from native, monomeric protein folding reactions that produce, for one protein sequence, only one ordered conformation and only one set of inter-residue interactions.

Disrupted-in-Schizophrenia-1 (DISC1) is a genetic susceptibility locus for major mental illness, including schizophrenia and depression. The Disc1 protein was recently shown to interact with the Wnt signaling protein, DIX domain containing 1 (Dixdc1). Both proteins participate in neural progenitor proliferation dependent on Wnt signaling, and in neural migration independently of Wnt signaling. Interestingly, their effect on neural progenitor proliferation is additive. By analogy to Disc1, mutations in Dixdc1 may lead to abnormal behavior in mice, and to schizophrenia or depression in humans. To explore this hypothesis further, we generated mice mutant at the Dixdc1 locus and analyzed their behavior. Dixdc1(-/-) mice had normal prepulse inhibition, but displayed decreased spontaneous locomotor activity, abnormal behavior in the elevated plus maze and deficits in startle reactivity. Our results suggest that Dixdc1(-/-) mice will be a useful tool to elucidate molecular pathophysiology involving Disc1 in major mental illnesses.

In tandem ring-closing metathesis of alkynyl silaketals containing two different tethered olefins, the gem-dimethyl group showed the expected Thorpe-Ingold effect, thereby giving good level of group selectivity. Unexpectedly, however, the corresponding gem-diphenyl group did not show any Thorpe-Ingold effect for the ring closure reaction.

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.

We introduce an efficient search strategy to substantially accelerate feature based registration. Previous feature based registration algorithms often use truncated search strategies in order to achieve small computation times. Our new accelerated search strategy is based on the realization that the search for corresponding features can be dramatically accelerated by utilizing Johnson-Lindenstrauss dimension reduction. Order of magnitude calculations for the search strategy we propose here indicate that the algorithm proposed is more than a million times faster than previously utilized naive search strategies, and this advantage in speed is directly translated into an advantage in accuracy as the fast speed enables more comparisons to be made in the same amount of time. We describe the accelerated scheme together with a full complexity analysis. The registration algorithm was applied to large transmission electron microscopy (TEM) images of neural ultrastructure. Our experiments demonstrate that our algorithm enables alignment of TEM images with increased accuracy and efficiency compared to previous algorithms.