We report learning-related structural plasticity in layer 1 branches of pyramidal neurons in the barrel cortex, a known site of sensorimotor integration. In mice learning an active, whisker-dependent object localization task, layer 2/3 neurons showed enhanced spine growth during initial skill acquisition that both preceded and predicted expert performance. Preexisting spines were stabilized and new persistent spines were formed. These findings suggest rapid changes in connectivity between motor centers and sensory cortex guide subsequent sensorimotor learning.

Axonal branching allows a neuron to connect to several targets, increasing neuronal circuit complexity. While axonal branching is well described, the mechanisms that control it remain largely unknown. We find that in the Drosophila CNS branches develop through a process of excessive growth followed by pruning. In vivo high-resolution live imaging of developing brains as well as loss and gain of function experiments show that activation of Epidermal Growth Factor Receptor (EGFR) is necessary for branch dynamics and the final branching pattern. Live imaging also reveals that intrinsic asymmetry in EGFR localization regulates the balance between dynamic and static filopodia. Elimination of signaling asymmetry by either loss or gain of EGFR function results in reduced dynamics leading to excessive branch formation. In summary, we propose that the dynamic process of axon branch development is mediated by differential local distribution of signaling receptors. DOI: http://dx.doi.org/10.7554/eLife.01699.001.

Light-sheet fluorescence microscopy is able to image large specimens with high resolution by capturing the samples from multiple angles. Multiview deconvolution can substantially improve the resolution and contrast of the images, but its application has been limited owing to the large size of the data sets. Here we present a Bayesian-based derivation of multiview deconvolution that drastically improves the convergence time, and we provide a fast implementation using graphics hardware.

In the evolution of caste-based societies in Hymenoptera, the classical insect hormones, juvenile hormone (JH) and ecdysteroids, were co-opted into new functions. Social wasps, which show all levels of sociality and lifestyles, are an ideal group to study such functional changes. Virtually all studies on the physiological mechanisms underlying reproductive division of labor and caste functions in wasps have been done on independent-founding paper wasps, and the majority of these studies have focused on species specially adapted for overwintering. The relatively little studied tropical swarming-founding wasps of the Epiponini (Vespidae) are a diverse group of permanently social wasps, with some species maintaining caste flexibility well into the adult phase. We investigated the behavior, reproductive status, JH and ecdysteroid titers in hemolymph, ecdysteroid content of the ovary and cuticular hydrocarbon (CHC) profiles in the caste-monomorphic, epiponine wasp Polybia micans Ducke. We found that the JH titer was not elevated in competing queens from established multiple-queen nests, but increased in lone queens that lack direct competition. In queenless colonies, JH titers rose transiently in young potential reproductives upon challenge by nestmates, suggesting that JH may prime the ovaries for further development. Ovarian ecdysteroids were very low in workers but higher and correlated with the number of vitellogenic oocytes in the queens. Hemolymph ecdysteroid levels were low and variable in both. Profiles of P. micans CHCs reflected caste, age and reproductive status, but were not tightly linked to either hormone. These findings show a significant divergence in hormone function in swarm-founding wasps compared to independent-founding ones.

We show that a small subset of two to six subesophageal neurons, expressing the male products of the male courtship master regulator gene products fruitlessMale (fruM), are required in the early stages of the Drosophila melanogaster male courtship behavioral program. Loss of fruM expression or inhibition of synaptic transmission in these fruM(+) neurons results in delayed courtship initiation and a failure to progress to copulation primarily under visually-deficient conditions. We identify a fruM-dependent sexually dimorphic arborization in the tritocerebrum made by two of these neurons. Furthermore, these SOG neurons extend descending projections to the thorax and abdominal ganglia. These anatomical and functional characteristics place these neurons in the position to integrate gustatory and higher-order signals in order to properly initiate and progress through early courtship.

The spatiotemporal activities of astrocyte Ca(2+) signaling in mature neuronal circuits remain unclear. We used genetically encoded Ca(2+) and glutamate indicators as well as pharmacogenetic and electrical control of neurotransmitter release to explore astrocyte activity in the hippocampal mossy fiber pathway. Our data revealed numerous localized, spontaneous Ca(2+) signals in astrocyte branches and territories, but these were not driven by neuronal activity or glutamate. Moreover, evoked astrocyte Ca(2+) signaling changed linearly with the number of mossy fiber action potentials. Under these settings, astrocyte responses were global, suppressed by neurotransmitter clearance, and mediated by glutamate and GABA. Thus, astrocyte engagement in the fully developed mossy fiber pathway was slow and territorial, contrary to that frequently proposed for astrocytes within microcircuits. We show that astrocyte Ca(2+) signaling functionally segregates large volumes of neuropil and that these transients are not suited for responding to, or regulating, single synapses in the mossy fiber pathway.

How adherent and contractile systems coordinate to promote cell shape changes is unclear. Here, we define a counterbalanced adhesion/contraction model for cell shape control. Live-cell microscopy data showed a crucial role for a contractile meshwork at the top of the cell, which is composed of actin arcs and myosin IIA filaments. The contractile actin meshwork is organized like muscle sarcomeres, with repeating myosin II filaments separated by the actin bundling protein α-actinin, and is mechanically coupled to noncontractile dorsal actin fibers that run from top to bottom in the cell. When the meshwork contracts, it pulls the dorsal fibers away from the substrate. This pulling force is counterbalanced by the dorsal fibers' attachment to focal adhesions, causing the fibers to bend downward and flattening the cell. This model is likely to be relevant for understanding how cells configure themselves to complex surfaces, protrude into tight spaces, and generate three-dimensional forces on the growth substrate under both healthy and diseased conditions.

The generation of four-dimensional (4D) confocal datasets; consisting of 3D image sequences over time; provides an excellent methodology to capture cellular behaviors involved in developmental processes.  The ability to track and follow cell movements is limited by sample movements that occur due to drift of the sample or, in some cases, growth during image acquisition. Tracking cells in datasets affected by drift and/or growth will incorporate these movements into any analysis of cell position. This may result in the apparent movement of static structures within the sample. Therefore prior to cell tracking, any sample drift should be corrected. Using the open source Fiji distribution (1)  of ImageJ (2,3) and the incorporated LOCI tools (4), we developed the Correct 3D drift plug-in to remove erroneous sample movement in confocal datasets. This protocol effectively compensates for sample translation or alterations in focal position by utilizing phase correlation to register each time-point of a four-dimensional confocal datasets while maintaining the ability to visualize and measure cell movements over extended time-lapse experiments.

Spatial patterns of gene expression in the vertebrate brain are not independent, as pairs of genes can exhibit complex patterns of coexpression. Two genes may be similarly expressed in one region, but differentially expressed in other regions. These correlations have been studied quantitatively, particularly for the Allen Atlas of the adult mouse brain, but their biological meaning remains obscure. We propose a simple model of the coexpression patterns in terms of spatial distributions of underlying cell types and establish its plausibility using independently measured cell-type-specific transcriptomes. The model allows us to predict the spatial distribution of cell types in the mouse brain.

The aim in high-resolution connectomics is to reconstruct complete neuronal connectivity in a tissue. Currently, the only technology capable of resolving the smallest neuronal processes is electron microscopy (EM). Thus, a common approach to network reconstruction is to perform (error-prone) automatic segmentation of EM images, followed by manual proofreading by experts to fix errors. We have developed an algorithm and software library to not only improve the accuracy of the initial automatic segmentation, but also point out the image coordinates where it is likely to have made errors. Our software, called gala (graph-based active learning of agglomeration), improves the state of the art in agglomerative image segmentation. It is implemented in Python and makes extensive use of the scientific Python stack (numpy, scipy, networkx, scikit-learn, scikit-image, and others). We present here the software architecture of the gala library, and discuss several designs that we consider would be generally useful for other segmentation packages. We also discuss the current limitations of the gala library and how we intend to address them.