In neurons, individual dendritic spines isolate N-methyl-d-aspartate (NMDA) receptor-mediated calcium ion (Ca2+) accumulations from the dendrite and other spines. However, the extent to which spines compartmentalize signaling events downstream of Ca2+ influx is not known. We combined two-photon fluorescence lifetime imaging with two-photon glutamate uncaging to image the activity of the small guanosine triphosphatase Ras after NMDA receptor activation at individual spines. Induction of long-term potentiation (LTP) triggered robust Ca2+-dependent Ras activation in single spines that decayed in approximately 5 minutes. Ras activity spread over approximately 10 micrometers of dendrite and invaded neighboring spines by diffusion. The spread of Ras-dependent signaling was necessary for the local regulation of the threshold for LTP induction. Thus, Ca2+-dependent synaptic signals can spread to couple multiple synapses on short stretches of dendrite.

Fluorescent proteins and their engineered variants have played an important role in the study of biology. The genetically encoded calcium-indicator protein GCaMP2 comprises a circularly permuted fluorescent protein coupled to the calcium-binding protein calmodulin and a calmodulin target peptide, M13, derived from the intracellular calmodulin target myosin light-chain kinase and has been used to image calcium transients in vivo. To aid rational efforts to engineer improved variants of GCaMP2, this protein was crystallized in the calcium-saturated form. X-ray diffraction data were collected to 2.0 A resolution. The crystals belong to space group C2, with unit-cell parameters a = 126.1.

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.

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.

Over hundreds of millions of years, evolution has optimized brain design to maximize its functionality while minimizing costs associated with building and maintenance. This observation suggests that one can use optimization theory to rationalize various features of brain design. Here, we attempt to explain the dimensions and branching structure of dendritic arbors by minimizing dendritic cost for given potential synaptic connectivity. Assuming only that dendritic cost increases with total dendritic length and path length from synapses to soma, we find that branching, planar, and compact dendritic arbors, such as those belonging to Purkinje cells in the cerebellum, are optimal. The theory predicts that adjacent Purkinje dendritic arbors should spatially segregate. In addition, we propose two explicit cost function expressions, falsifiable by measuring dendritic caliber near bifurcations.

We demonstrate live-cell super-resolution imaging using photoactivated localization microscopy (PALM). The use of photon-tolerant cell lines in combination with the high resolution and molecular sensitivity of PALM permitted us to investigate the nanoscale dynamics within individual adhesion complexes (ACs) in living cells under physiological conditions for as long as 25 min, with half of the time spent collecting the PALM images at spatial resolutions down to approximately 60 nm and frame rates as short as 25 s. We visualized the formation of ACs and measured the fractional gain and loss of individual paxillin molecules as each AC evolved. By allowing observation of a wide variety of nanoscale dynamics, live-cell PALM provides insights into molecular assembly during the initiation, maturation and dissolution of cellular processes.

Commentary: The first example of true live cell and time lapse imaging by localization microscopy (as opposed to particle tracking), this paper uses the Nyquist criterion to establish a necessary condition for true spatial resolution based on the density of localized molecules – a condition often unmet in claims elsewhere in the superresolution literature.
By any method, higher spatiotemporal resolution requires increasing light exposure at the specimen, making noninvasive imaging increasingly difficult. Here, simultaneous differential interference contrast imaging is used to establish that cells behave physiologically before, during, and after PALM imaging. Similar controls are lacking from many supposed “live cell” superresolution demonstrations.

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%.

Although information storage in the central nervous system is thought to be primarily mediated by various forms of synaptic plasticity, other mechanisms, such as modifications in membrane excitability, are available. Local dendritic spikes are nonlinear voltage events that are initiated within dendritic branches by spatially clustered and temporally synchronous synaptic input. That local spikes selectively respond only to appropriately correlated input allows them to function as input feature detectors and potentially as powerful information storage mechanisms. However, it is currently unknown whether any effective form of local dendritic spike plasticity exists. Here we show that the coupling between local dendritic spikes and the soma of rat hippocampal CA1 pyramidal neurons can be modified in a branch-specific manner through an N-methyl-d-aspartate receptor (NMDAR)-dependent regulation of dendritic Kv4.2 potassium channels. These data suggest that compartmentalized changes in branch excitability could store multiple complex features of synaptic input, such as their spatio-temporal correlation. We propose that this ’branch strength potentiation’ represents a previously unknown form of information storage that is distinct from that produced by changes in synaptic efficacy both at the mechanistic level and in the type of information stored.

Genetically-encoded calcium indicators (GECIs) hold the promise of monitoring [Ca(2+)] in selected populations of neurons and in specific cellular compartments. Relating GECI fluorescence to neuronal activity requires quantitative characterization. We have characterized a promising new genetically-encoded calcium indicator-GCaMP2-in mammalian pyramidal neurons. Fluorescence changes in response to single action potentials (17+/-10% DeltaF/F [mean+/-SD]) could be detected in some, but not all, neurons. Trains of high-frequency action potentials yielded robust responses (302+/-50% for trains of 40 action potentials at 83 Hz). Responses were similar in acute brain slices from in utero electroporated mice, indicating that long-term expression did not interfere with GCaMP2 function. Membrane-targeted versions of GCaMP2 did not yield larger signals than their non-targeted counterparts. We further targeted GCaMP2 to dendritic spines to monitor Ca(2+) accumulations evoked by activation of synaptic NMDA receptors. We observed robust DeltaF/F responses (range: 37%-264%) to single spine uncaging stimuli that were correlated with NMDA receptor currents measured through a somatic patch pipette. One major drawback of GCaMP2 was its low baseline fluorescence. Our results show that GCaMP2 is improved from the previous versions of GCaMP and may be suited to detect bursts of high-frequency action potentials and synaptic currents in vivo.