Mitochondria are difficult targets for microscopy because of their small size and highly compartmentalized, membranous interior. Super-resolution fluorescence microscopy methods have recently been developed that exceed the historical limits of optical imaging. Here we outline considerations and techniques in preparing to image the relative location of mitochondrial proteins using photoactivated localization microscopy (PALM). PALM and similar methods have the capacity to dramatically increase our ability to image proteins within mitochondria, and to expand our knowledge of the location of macromolecules beyond the current limits of immunoEM.

The neuropile of the Drosophila brain is subdivided into anatomically discrete compartments. Compartments are rich in terminal neurite branching and synapses; they are the neuropile domains in which signal processing takes place. Compartment boundaries are defined by more or less dense layers of glial cells as well as long neurite fascicles. These fascicles are formed during the larval period, when the approximately 100 neuronal lineages that constitute the Drosophila central brain differentiate. Each lineage forms an axon tract with a characteristic trajectory in the neuropile; groups of spatially related tracts congregate into the brain fascicles that can be followed from the larva throughout metamorphosis into the adult stage. Here we provide a map of the adult brain compartments and the relevant fascicles defining compartmental boundaries. We have identified the neuronal lineages contributing to each fascicle, which allowed us to compare compartments of the larval and adult brain directly. Most adult compartments can be recognized already in the early larval brain, where they form a "protomap" of the later adult compartments. Our analysis highlights the morphogenetic changes shaping the Drosophila brain; the data will be important for studies that link early-acting genetic mechanisms to the adult neuronal structures and circuits controlled by these mechanisms.

Recording light-microscopy images of large, nontransparent specimens, such as developing multicellular organisms, is complicated by decreased contrast resulting from light scattering. Early zebrafish development can be captured by standard light-sheet microscopy, but new imaging strategies are required to obtain high-quality data of late development or of less transparent organisms. We combined digital scanned laser light-sheet fluorescence microscopy with incoherent structured-illumination microscopy (DSLM-SI) and created structured-illumination patterns with continuously adjustable frequencies. Our method discriminates the specimen-related scattered background from signal fluorescence, thereby removing out-of-focus light and optimizing the contrast of in-focus structures. DSLM-SI provides rapid control of the illumination pattern, exceptional imaging quality, and high imaging speeds. We performed long-term imaging of zebrafish development for 58 h and fast multiple-view imaging of early Drosophila melanogaster development. We reconstructed cell positions over time from the Drosophila DSLM-SI data and created a fly digital embryo.

Although hippocampal theta oscillations represent a prime example of temporal coding in the mammalian brain, little is known about the specific biophysical mechanisms. Intracellular recordings support a particular abstract oscillatory interference model of hippocampal theta activity, the soma-dendrite interference model. To gain insight into the cellular and circuit level mechanisms of theta activity, we implemented a similar form of interference using the actual hippocampal network in mice in vitro. We found that pairing increasing levels of phasic dendritic excitation with phasic stimulation of perisomatic projecting inhibitory interneurons induced a somatic polarization and action potential timing profile that reproduced most common features. Alterations in the temporal profile of inhibition were required to fully capture all features. These data suggest that theta-related place cell activity is generated through an interaction between a phasic dendritic excitation and a phasic perisomatic shunting inhibition delivered by interneurons, a subset of which undergo activity-dependent presynaptic modulation.

Within dendritic spines, actin is presumed to anchor receptors in the postsynaptic density and play numerous roles regulating synaptic transmission. However, the submicron dimensions of spines have hindered examination of actin dynamics within them and prevented live-cell discrimination of perisynaptic actin filaments. Using photoactivated localization microscopy, we measured movement of individual actin molecules within living spines. Velocity of single actin molecules along filaments, an index of filament polymerization rate, was highly heterogeneous within individual spines. Most strikingly, molecular velocity was elevated in discrete, well-separated foci occurring not principally at the spine tip, but in subdomains throughout the spine, including the neck. Whereas actin velocity on filaments at the synapse was substantially elevated, at the endocytic zone there was no enhanced polymerization activity. We conclude that actin subserves spatially diverse, independently regulated processes throughout spines. Perisynaptic actin forms a uniquely dynamic structure well suited for direct, active regulation of the synapse.

Commentary: A nice application of single particle tracking PALM (sptPALM), showing the flow of actin in the spines of live cultured neurons. Since 2008, the PALM in our lab has largely become a user facility, available to outside users as well as Janelians. Grad student Nick Frost in Tom Blanpied’s group at the U. of Maryland Med School visited on a number of occasions to use the PALM, with training and assistance from Hari.

Drosophila melanogaster is a model organism rich in genetic tools to manipulate and identify neural circuits involved in specific behaviors. Here we present a technique for two-photon calcium imaging in the central brain of head-fixed Drosophila walking on an air-supported ball. The ball’s motion is tracked at high resolution and can be treated as a proxy for the fly’s own movements. We used the genetically encoded calcium sensor, GCaMP3.0, to record from important elements of the motion-processing pathway, the horizontal-system lobula plate tangential cells (LPTCs) in the fly optic lobe. We presented motion stimuli to the tethered fly and found that calcium transients in horizontal-system neurons correlated with robust optomotor behavior during walking. Our technique allows both behavior and physiology in identified neurons to be monitored in a genetic model organism with an extensive repertoire of walking behaviors.

Recent advances in optogenetic techniques have generated new tools for controlling neuronal activity, with a wide range of neuroscience applications. The most commonly used approach has been the optical activation of the light-gated ion channel channelrhodopsin-2 (ChR2). However, targeted single-cell-level optogenetic activation with temporal precessions comparable to the spike timing remained challenging. Here we report fast (< or = 1 ms), selective, and targeted control of neuronal activity with single-cell resolution in hippocampal slices. Using temporally focused laser pulses (TEFO) for which the axial beam profile can be controlled independently of its lateral distribution, large numbers of channels on individual neurons can be excited simultaneously, leading to strong (up to 15 mV) and fast (< or = 1 ms) depolarizations. Furthermore, we demonstrated selective activation of cellular compartments, such as dendrites and large presynaptic terminals, at depths up to 150 microm. The demonstrated spatiotemporal resolution and the selectivity provided by TEFO allow manipulation of neuronal activity, with a large number of applications in studies of neuronal microcircuit function in vitro and in vivo.

The centrosome is a dynamic structure in animal cells that serves as a microtubule organizing center during mitosis and also regulates cell-cycle progression and sets polarity cues. Automated and reliable tracking of centrosomes is essential for genetic screens that study the process of centrosome assembly and maturation in the nematode Caenorhabditis elegans.

Digital reconstruction of 3D neuron structures is an important step toward reverse engineering the wiring and functions of a brain. However, despite a number of existing studies, this task is still challenging, especially when a 3D microscopic image has low single-to-noise ratio and discontinued segments of neurite patterns.

The Drosophila brain is formed by an invariant set of lineages, each of which is derived from a unique neural stem cell (neuroblast) and forms a genetic and structural unit of the brain. The task of reconstructing brain circuitry at the level of individual neurons can be made significantly easier by assigning neurons to their respective lineages. In this article we address the automation of neuron and lineage identification. We focused on the Drosophila brain lineages at the larval stage when they form easily recognizable secondary axon tracts (SATs) that were previously partially characterized. We now generated an annotated digital database containing all lineage tracts reconstructed from five registered wild-type brains, at higher resolution and including some that were previously not characterized. We developed a method for SAT structural comparisons based on a dynamic programming approach akin to nucleotide sequence alignment and a machine learning classifier trained on the annotated database of reference SATs. We quantified the stereotypy of SATs by measuring the residual variability of aligned wild-type SATs. Next, we used our method for the identification of SATs within wild-type larval brains, and found it highly accurate (93-99%). The method proved highly robust for the identification of lineages in mutant brains and in brains that differed in developmental time or labeling. We describe for the first time an algorithm that quantifies neuronal projection stereotypy in the Drosophila brain and use the algorithm for automatic neuron and lineage recognition.