Smart camera networks have recently emerged as a new class of sensor network infrastructure that is capable of supporting high-power in-network signal processing and enabling a wide range of applications. In this article, we provide an exposition of our efforts to build a low-bandwidth wireless camera network platform, called CITRIC, and its applications in smart camera networks. The platform integrates a camera, a microphone, a frequency-scalable (up to 624 MHz) CPU, 16 MB FLASH, and 64 MB RAM onto a single device. The device then connects with a standard sensor network mote to form a wireless camera mote. With reasonably low power consumption and extensive algorithmic libraries running on a decent operating system that is easy to program, CITRIC is ideal for research and applications in distributed image and video processing. Its capabilities of in-network image processing also reduce communication requirements, which has been high in other existing camera networks with centralized processing. Furthermore, the mote easily integrates with other low-bandwidth sensor networks via the IEEE 802.15.4 protocol. To justify the utility of CITRIC, we present several representative applications. In particular, concrete research results will be demonstrated in two areas, namely, distributed coverage hole identification and distributed object recognition.

Rapid evolution of genitalia shape, a widespread phenomenon in animals with internal fertilization, offers the opportunity to dissect the genetic architecture of morphological evolution linked to sexual selection and speciation. Most quantitative trait loci (QTL) mapping studies of genitalia divergence have focused on Drosophila melanogaster and its three most closely related species, D. simulans, D. mauritiana, and D. sechellia, and have suggested that the genetic basis of genitalia evolution involves many loci. We report the first genetic study of male genitalia evolution between D. yakuba and D. santomea, two species of the D. melanogaster species subgroup. We focus on male ventral branches, which harm females during interspecific copulation. Using landmark-based geometric morphometrics, we characterized shape variation in parental species, F1 hybrids, and backcross progeny and show that the main axis of shape variation within the backcross population matches the interspecific variation between parental species. For genotyping, we developed a new molecular method to perform multiplexed shotgun genotyping (MSG), which allowed us to prepare genomic DNA libraries from 365 backcross individuals in a few days using little DNA. We detected only three QTL, one of which spans 2.7 Mb and exhibits a highly significant effect on shape variation that can be linked to the harmfulness of the ventral branches. We conclude that the genetic architecture of genitalia morphology divergence may not always be as complex as suggested by previous studies.

Developmental genetic analysis has shown that embryos of the parasitoid wasp Nasonia vitripennis depend more on zygotic gene products to direct axial patterning than do Drosophila embryos. In Drosophila, anterior axial patterning is largely established by bicoid, a rapidly evolving maternal-effect gene, working with hunchback, which is expressed both maternally and zygotically. Here, we focus on a comparative analysis of Nasonia hunchback function and expression. We find that a lesion in Nasonia hunchback is responsible for the severe zygotic headless mutant phenotype, in which most head structures and the thorax are deleted, as are the three most posterior abdominal segments. This defines a major role for zygotic Nasonia hunchback in anterior patterning, more extensive than the functions described for hunchback in Drosophila or Tribolium. Despite the major zygotic role of Nasonia hunchback, we find that it is strongly expressed maternally, as well as zygotically. Nasonia Hunchback embryonic expression appears to be generally conserved; however, the mRNA expression differs from that of Drosophila hunchback in the early blastoderm. We also find that the maternal hunchback message decays at an earlier developmental stage in Nasonia than in Drosophila, which could reduce the relative influence of maternal products in Nasonia embryos. Finally, we extend the comparisons of Nasonia and Drosophila hunchback mutant phenotypes, and propose that the more severe Nasonia hunchback mutant phenotype may be a consequence of differences in functionally overlapping regulatory circuitry.

There is a continuing need for driver strains to enable cell type-specific manipulation in the nervous system. Each cell type expresses a unique set of genes, and recapitulating expression of marker genes by BAC transgenesis or knock-in has generated useful transgenic mouse lines. However since genes are often expressed in many cell types, many of these lines have relatively broad expression patterns. We report an alternative transgenic approach capturing distal enhancers for more focused expression. We identified an enhancer trap probe often producing restricted reporter expression and developed efficient enhancer trap screening with the PiggyBac transposon. We established more than 200 lines and found many lines that label small subsets of neurons in brain substructures, including known and novel cell types. Images and other information about each line are available online (enhancertrap.bio.brandeis.edu).

Ribonuclease mitochondrial RNA processing, a site-specific endoribonuclease involved in primer RNA metabolism in mammalian mitochondria, requires an RNA component for its activity. On the basis of copurification and selective inactivation with complementary oligonucleotides, a 135-nucleotide RNA species, not encoded in the mitochondrial genome, is identified as the RNA moiety of the endoribonuclease. This finding implies transport of a nucleus-encoded RNA, essential for organelle DNA replication, to the mitochondrial matrix.

Activity in the mouse anterior lateral motor cortex (ALM) instructs directional movements, often seconds before movement initiation. It is unknown whether this preparatory activity is localized to ALM or widely distributed within motor cortex. Here we imaged activity across motor cortex while mice performed a whisker-based object localization task with a delayed, directional licking response. During tactile sensation and the delay epoch, object location was represented in motor cortex areas that are medial and posterior relative to ALM, including vibrissal motor cortex. Preparatory activity appeared first in deep layers of ALM, seconds before the behavioral response, and remained localized to ALM until the behavioral response. Later, widely distributed neurons represented the outcome of the trial. Cortical area was more predictive of neuronal selectivity than laminar location or axonal projection target. Motor cortex therefore represents sensory, motor, and outcome information in a spatially organized manner.

Complex phenotypes, such as an animal’s behavior, generally depend on an overwhelming number of processes that span a vast range of scales. While there is no reason that behavioral dynamics permit simple models, by subsuming inherent nonlinearities and memory into maximally predictive microstates, we find one for Caenorhabditis elegans foraging. The resulting “Markov worm” is effectively indistinguishable from real worm motion across a range of timescales, and we can decompose our model dynamics both to recover and reveal behavioral states. Finally, we connect postures to trajectories, illuminating how worms explore the environment in different behavioral states. How do we capture the breadth of behavior in animal movement, from rapid body twitches to aging? Using high-resolution videos of the nematode worm Caenorhabditis elegans, we show that a single dynamics connects posture-scale fluctuations with trajectory diffusion and longer-lived behavioral states. We take short posture sequences as an instantaneous behavioral measure, fixing the sequence length for maximal prediction. Within the space of posture sequences, we construct a fine-scale, maximum entropy partition so that transitions among microstates define a high-fidelity Markov model, which we also use as a means of principled coarse-graining. We translate these dynamics into movement using resistive force theory, capturing the statistical properties of foraging trajectories. Predictive across scales, we leverage the longest-lived eigenvectors of the inferred Markov chain to perform a top–down subdivision of the worm’s foraging behavior, revealing both “runs-and-pirouettes” as well as previously uncharacterized finer-scale behaviors. We use our model to investigate the relevance of these fine-scale behaviors for foraging success, recovering a trade-off between local and global search strategies.

Early stages of sensory systems face the challenge of compressing information from numerous receptors onto a much smaller number of projection neurons, a so called communication bottleneck. To make more efficient use of limited bandwidth, compression may be achieved using predictive coding, whereby predictable, or redundant, components of the stimulus are removed. In the case of the retina, Srinivasan et al. (1982) suggested that feedforward inhibitory connections subtracting a linear prediction generated from nearby receptors implement such compression, resulting in biphasic center-surround receptive fields. However, feedback inhibitory circuits are common in early sensory circuits and furthermore their dynamics may be nonlinear. Can such circuits implement predictive coding as well? Here, solving the transient dynamics of nonlinear reciprocal feedback circuits through analogy to a signal-processing algorithm called linearized Bregman iteration we show that nonlinear predictive coding can be implemented in an inhibitory feedback circuit. In response to a step stimulus, interneuron activity in time constructs progressively less sparse but more accurate representations of the stimulus, a temporally evolving prediction. This analysis provides a powerful theoretical framework to interpret and understand the dynamics of early sensory processing in a variety of physiological experiments and yields novel predictions regarding the relation between activity and stimulus statistics.

Johnston’s organ is the largest mechanosensory organ in Drosophila; it analyzes movements of the antenna due to sound, wind, gravity, and touch. Different Johnston’s organ neurons (JONs) encode distinct stimulus features. Certain JONs respond in a sustained manner to steady displacements, and these JONs subdivide into opponent populations that prefer push or pull displacements. Here, we describe neurons in the brain (aPN3 neurons) that combine excitation and inhibition from push/pull JONs in different ratios. Consequently, different aPN3 neurons are sensitive to movement in different parts of the antenna’s range, at different frequencies, or at different amplitude modulation rates. We use a model to show how the tuning of aPN3 neurons can arise from rectification and temporal filtering in JONs, followed by mixing of JON signals in different proportions. These results illustrate how several canonical neural circuit components—rectification, opponency, and filtering—can combine to produce selectivity for complex stimulus features.

Low dose imaging procedures are key for a successful cryoEM experiment (whether by electron cryotomography, single particle analysis, electron crystallography, or MicroED). We present a method to minimize magnetic hysteresis of the condenser lens system in the JEOL JEM-3200FSC transmission electron microscope (TEM) in order to maintain a stable optical axis for the beam path of low-dose imaging. The simple procedure involves independent voltage ramping of the CL1 and CL2 lenses immediately before switching to the focusing and exposure beam settings for data collection.