Sequence database searches require accurate estimation of the statistical significance of scores. Optimal local sequence alignment scores follow Gumbel distributions, but determining an important parameter of the distribution (lambda) requires time-consuming computational simulation. Moreover, optimal alignment scores are less powerful than probabilistic scores that integrate over alignment uncertainty ("Forward" scores), but the expected distribution of Forward scores remains unknown. Here, I conjecture that both expected score distributions have simple, predictable forms when full probabilistic modeling methods are used. For a probabilistic model of local sequence alignment, optimal alignment bit scores ("Viterbi" scores) are Gumbel-distributed with constant lambda = log 2, and the high scoring tail of Forward scores is exponential with the same constant lambda. Simulation studies support these conjectures over a wide range of profile/sequence comparisons, using 9,318 profile-hidden Markov models from the Pfam database. This enables efficient and accurate determination of expectation values (E-values) for both Viterbi and Forward scores for probabilistic local alignments.

We consider the problem of communicating compact descriptors for the purpose of establishing visual correspondences between two cameras operating under rate constraints. Establishing visual correspondences is a critical step before other tasks such as camera calibration or object recognition can be performed in a network of cameras. We verify that descriptors of regions which are in correspondence are highly correlated, and propose the use of distributed source coding to reduce the bandwidth needed for transmitting descriptors required to establish correspondence. Our experiments demonstrate that the proposed scheme is able to provide compression gains of 57% with minimal loss in the number of correctly established correspondences compared to a scheme that communicates the entire image of the scene losslessly in compressed form. Over a wide range of rates, the proposed scheme also provides superior performance when compared to simply transmitting all the feature descriptors.

We present a Bayesian framework for action recognition through ballistic dynamics. Psycho-kinesiological studies indicate that ballistic movements form the natural units for human movement planning. The framework leads to an efficient and robust algorithm for temporally segmenting videos into atomic movements. Individual movements are annotated with person-centric morphological labels called ballistic verbs. This is tested on a dataset of interactive movements, achieving high recognition rates. The approach is also applied on a gesture recognition task, improving a previously reported recognition rate from 84% to 92%. Consideration of ballistic dynamics enhances the performance of the popular Motion History Image feature. We also illustrate the approach’s general utility on real-world videos. Experiments indicate that the method is robust to view, style and appearance variations.

Neurobiological processes occur on spatiotemporal scales spanning many orders of magnitude. Greater understanding of these processes therefore demands improvements in the tools used in their study. Here we review recent efforts to enhance the speed and resolution of one such tool, fluorescence microscopy, with an eye toward its application to neurobiological problems. On the speed front, improvements in beam scanning technology, signal generation rates, and photodamage mediation are bringing us closer to the goal of real-time functional imaging of extended neural networks. With regard to resolution, emerging methods of adaptive optics may lead to diffraction-limited imaging or much deeper imaging in optically inhomogeneous tissues, and super-resolution techniques may prove a powerful adjunct to electron microscopic methods for nanometric neural circuit reconstruction.

Neurobiological processes occur on spatiotemporal scales spanning many orders of magnitude. Greater understanding of these processes therefore demands improvements in the tools used in their study. Here we review recent efforts to enhance the speed and resolution of one such tool, fluorescence microscopy, with an eye toward its application to neurobiological problems. On the speed front, improvements in beam scanning technology, signal generation rates, and photodamage mediation are bringing us closer to the goal of real-time functional imaging of extended neural networks. With regard to resolution, emerging methods of adaptive optics may lead to diffraction-limited imaging or much deeper imaging in optically inhomogeneous tissues, and super-resolution techniques may prove a powerful adjunct to electron microscopic methods for nanometric neural circuit reconstruction.

Commentary: A brief review of recent trends in microscopy. The section “Caveats regarding the application of superresolution microscopy” was written in an effort to inject a dose of reality and caution into the unquestioning enthusiasm in the academic community for all things superresolution, covering the topics of labeling density and specificity, sample preparation artifacts, speed vs. resolution vs. photodamage, and the implications of signal-to-background for Nyquist vs. Rayleigh definitions of resolution.

Back-propagating action potentials (bAPs) travelling from the soma to the dendrites of neurons are involved in various aspects of synaptic plasticity. The distance-dependent increase in Kv4.2-mediated A-type K(+) current along the apical dendrites of CA1 pyramidal cells (CA1 PCs) is responsible for the attenuation of bAP amplitude with distance from the soma. Genetic deletion of Kv4.2 reduced dendritic A-type K(+) current and increased the bAP amplitude in distal dendrites. Our previous studies revealed that the amplitude of unitary Schaffer collateral inputs increases with distance from the soma along the apical dendrites of CA1 PCs. We tested the hypothesis that the weight of distal synapses is dependent on dendritic Kv4.2 channels. We compared the amplitude and kinetics of mEPSCs at different locations on the main apical trunk of CA1 PCs from wild-type (WT) and Kv4.2 knockout (KO) mice. While wild-type mice showed normal distance-dependent scaling, it was missing in the Kv4.2 KO mice. We also tested whether there was an increase in inhibition in the Kv4.2 knockout, induced in an attempt to compensate for a non-specific increase in neuronal excitability (after-polarization duration and burst firing probability were increased in KO). Indeed, we found that the magnitude of the tonic GABA current increased in Kv4.2 KO mice by 53% and the amplitude of mIPSCs increased by 25%, as recorded at the soma. Our results suggest important roles for the dendritic K(+) channels in distance-dependent adjustment of synaptic strength as well as a primary role for tonic inhibition in the regulation of global synaptic strength and membrane excitability.

Flexible goal-driven orientation requires that the position of a target be stored, especially in case the target moves out of sight. The capability to retain, recall and integrate such positional information into guiding behaviour has been summarized under the term spatial working memory. This kind of memory contains specific details of the presence that are not necessarily part of a long-term memory. Neurophysiological studies in primates indicate that sustained activity of neurons encodes the sensory information even though the object is no longer present. Furthermore they suggest that dopamine transmits the respective input to the prefrontal cortex, and simultaneous suppression by GABA spatially restricts this neuronal activity. Here we show that Drosophila melanogaster possesses a similar spatial memory during locomotion. Using a new detour setup, we show that flies can remember the position of an object for several seconds after it has been removed from their environment. In this setup, flies are temporarily lured away from the direction towards their hidden target, yet they are thereafter able to aim for their former target. Furthermore, we find that the GABAergic (stainable with antibodies against GABA) ring neurons of the ellipsoid body in the central brain are necessary and their plasticity is sufficient for a functional spatial orientation memory in flies. We also find that the protein kinase S6KII (ignorant) is required in a distinct subset of ring neurons to display this memory. Conditional expression of S6KII in these neurons only in adults can restore the loss of the orientation memory of the ignorant mutant. The S6KII signalling pathway therefore seems to be acutely required in the ring neurons for spatial orientation memory in flies.

Mammalian herbivores profoundly influence plant-dwelling insects [1]. Most studies have focused on the indirect effect of herbivory on insect populations via damage to the host plant [2,3]. Many insects, however, are in danger of being inadvertently ingested during herbivore feeding. Here, we report that pea aphids (Acyrthosiphon pisum) are able to sense the elevated heat and humidity of the breath of an approaching herbivore and thus salvage most of the colony by simultaneously dropping off the plant in large numbers immediately before the plant is eaten. Dropping entails the risk of losing the host plant and becoming desiccated or preyed upon on the ground [4,5], yet pea aphids may sporadically drop when threatened by insect enemies [6]. The immediate mass dropping, however, is an adaptation to the potential destructive impact of mammalian herbivory on the entire aphid colony. The combination of heat and humidity serves as a reliable cue to impending mammalian herbivory, enabling the aphids to avoid unnecessary dropping. No defensive behavior against incidental predation by herbivores has ever been demonstrated. The pea aphids' highly adaptive escape behavior uniquely demonstrates the strength of the selective pressure large mammalian herbivores impose on insect herbivores.

Landmark correspondences can be used for various tasks in image processing such as image alignment, reconstruction of panoramic photographs, object recognition and simultaneous localization and mapping for mobile robots. The computer vision community knows several techniques for extracting and pairwise associating such landmarks using distinctive invariant local image features. Two very successful methods are the Scale Invariant Feature Transform (SIFT)1 and Multi-Scale Oriented Patches (MOPS).2
We implemented these methods in the Java programming language3 for seamless use in ImageJ.4 We use it for fully automatic registration of gigantic serial section Transmission Electron Microscopy (TEM) mosaics. Using automatically detected landmark correspondences, the registration of large image mosaics simplifies to globally minimizing the displacement of corresponding points.
We present here an introduction to automatic landmark correspondence detection and demonstrate our implementation for ImageJ. We demonstrate the application of the plug-in on diverse image data.

The development of high-resolution microscopy makes possible the high-throughput screening of cellular information, such as gene expression at single cell resolution. One of the critical enabling techniques yet to be developed is the automatic recognition or annotation of specific cells in a 3D image stack. In this paper, we present a novel graph-based algorithm, ARC, that determines cell identities in a 3D confocal image of C. elegans based on their highly stereotyped arrangement. This is an essential step in our work on gene expression analysis of C. elegans at the resolution of single cells. Our ARC method integrates both the absolute and relative spatial locations of cells in a C. elegans body. It uses a marker-guided, spatially-constrained, two-stage bipartite matching to find the optimal match between cells in a subject image and cells in 15 template images that have been manually annotated and vetted. We applied ARC to the recognition of cells in 3D confocal images of the first larval stage (L1) of C. elegans hermaphrodites, and achieved an average accuracy of 94.91%.