All organisms react to noxious and mechanical stimuli but we still lack a complete understanding of cellular and molecular mechanisms by which somatosensory information is transformed into appropriate motor outputs. The small number of neurons and excellent genetic tools make Drosophila larva an especially tractable model system in which to address this problem. We developed high throughput assays with which we can simultaneously expose more than 1,000 larvae per man-hour to precisely timed noxious heat, vibration, air current, or optogenetic stimuli. Using this hardware in combination with custom software we characterized larval reactions to somatosensory stimuli in far greater detail than possible previously. Each stimulus evoked a distinctive escape strategy that consisted of multiple actions. The escape strategy was context-dependent. Using our system we confirmed that the nociceptive class IV multidendritic neurons were involved in the reactions to noxious heat. Chordotonal (ch) neurons were necessary for normal modulation of head casting, crawling and hunching, in response to mechanical stimuli. Consistent with this we observed increases in calcium transients in response to vibration in ch neurons. Optogenetic activation of ch neurons was sufficient to evoke head casting and crawling. These studies significantly increase our understanding of the functional roles of larval ch neurons. More generally, our system and the detailed description of wild type reactions to somatosensory stimuli provide a basis for systematic identification of neurons and genes underlying these behaviors.

We aim to improve segmentation through the use of machine learning tools during region agglomeration. We propose an active learning approach for performing hierarchical agglomerative segmentation from superpixels. Our method combines multiple features at all scales of the agglomerative process, works for data with an arbitrary number of dimensions, and scales to very large datasets. We advocate the use of variation of information to measure segmentation accuracy, particularly in 3D electron microscopy (EM) images of neural tissue, and using this metric demonstrate an improvement over competing algorithms in EM and natural images.

The Drosophila central brain develops from a fixed number of neuroblasts. Each neuroblast makes a clone of neurons that exhibit common trajectories. Here we identified 15 distinct clones that carry larval-born neurons innervating the Drosophila central complex (CX), which consists of four midline structures including the protocerebral bridge (PB), fan-shaped body (FB), ellipsoid body (EB), and noduli (NO). Clonal analysis revealed that the small-field CX neurons, which establish intricate projections across different CX substructures, exist in four isomorphic groups that respectively derive from four complex posterior asense-negative lineages. In terms of the region-characteristic large-field CX neurons, we found that two lineages make PB neurons, 10 lineages produce FB neurons, three lineages generate EB neurons, and two lineages yield NO neurons. The diverse FB developmental origins reflect the discrete input pathways for different FB subcompartments. Clonal analysis enlightens both development and anatomy of the insect locomotor control center.

The zebrafish Danio rerio has emerged as a powerful vertebrate model system that lends itself particularly well to quantitative investigations with live imaging approaches, owing to its exceptionally high optical clarity in embryonic and larval stages. Recent advances in light microscopy technology enable comprehensive analyses of cellular dynamics during zebrafish embryonic development, systematic mapping of gene expression dynamics, quantitative reconstruction of mutant phenotypes and the system-level biophysical study of morphogenesis. Despite these technical breakthroughs, it remains challenging to design and implement experiments for in vivo long-term imaging at high spatio-temporal resolution. This article discusses the fundamental challenges in zebrafish long-term live imaging, provides experimental protocols and highlights key properties and capabilities of advanced fluorescence microscopes. The article focuses in particular on experimental assays based on light sheet-based fluorescence microscopy, an emerging imaging technology that achieves exceptionally high imaging speeds and excellent signal-to-noise ratios, while minimizing light-induced damage to the specimen. This unique combination of capabilities makes light sheet microscopy an indispensable tool for the in vivo long-term imaging of large developing organisms.

Transcription is reported to be spatially compartmentalized in nuclear transcription factories with clusters of RNA polymerase II (Pol II). However, little is known about when these foci assemble or their relative stability. We developed a quantitative single-cell approach to characterize protein spatiotemporal organization, with single-molecule sensitivity in live eukaryotic cells. We observed that Pol II clusters form transiently, with an average lifetime of 5.1 (± 0.4) seconds, which refutes the notion that they are statically assembled substructures. Stimuli affecting transcription yielded orders-of-magnitude changes in the dynamics of Pol II clusters, which implies that clustering is regulated and plays a role in the cell’s ability to effect rapid response to external signals. Our results suggest that transient crowding of enzymes may aid in rate-limiting steps of gene regulation.

The extraction of directional motion information from changing retinal images is one of the earliest and most important processing steps in any visual system. In the fly optic lobe, two parallel processing streams have been anatomically described, leading from two first-order interneurons, L1 and L2, via T4 and T5 cells onto large, wide-field motion-sensitive interneurons of the lobula plate. Therefore, T4 and T5 cells are thought to have a pivotal role in motion processing; however, owing to their small size, it is difficult to obtain electrical recordings of T4 and T5 cells, leaving their visual response properties largely unknown. We circumvent this problem by means of optical recording from these cells in Drosophila, using the genetically encoded calcium indicator GCaMP5 (ref. 2). Here we find that specific subpopulations of T4 and T5 cells are directionally tuned to one of the four cardinal directions; that is, front-to-back, back-to-front, upwards and downwards. Depending on their preferred direction, T4 and T5 cells terminate in specific sublayers of the lobula plate. T4 and T5 functionally segregate with respect to contrast polarity: whereas T4 cells selectively respond to moving brightness increments (ON edges), T5 cells only respond to moving brightness decrements (OFF edges). When the output from T4 or T5 cells is blocked, the responses of postsynaptic lobula plate neurons to moving ON (T4 block) or OFF edges (T5 block) are selectively compromised. The same effects are seen in turning responses of tethered walking flies. Thus, starting with L1 and L2, the visual input is split into separate ON and OFF pathways, and motion along all four cardinal directions is computed separately within each pathway. The output of these eight different motion detectors is then sorted such that ON (T4) and OFF (T5) motion detectors with the same directional tuning converge in the same layer of the lobula plate, jointly providing the input to downstream circuits and motion-driven behaviours.

Animal behaviour arises from computations in neuronal circuits, but our understanding of these computations has been frustrated by the lack of detailed synaptic connection maps, or connectomes. For example, despite intensive investigations over half a century, the neuronal implementation of local motion detection in the insect visual system remains elusive. Here we develop a semi-automated pipeline using electron microscopy to reconstruct a connectome, containing 379 neurons and 8,637 chemical synaptic contacts, within the Drosophila optic medulla. By matching reconstructed neurons to examples from light microscopy, we assigned neurons to cell types and assembled a connectome of the repeating module of the medulla. Within this module, we identified cell types constituting a motion detection circuit, and showed that the connections onto individual motion-sensitive neurons in this circuit were consistent with their direction selectivity. Our results identify cellular targets for future functional investigations, and demonstrate that connectomes can provide key insights into neuronal computations.

Active dendritic synaptic integration enhances the computational power of neurons. Such nonlinear processing generates an object-localization signal in the apical dendritic tuft of layer 5B cortical pyramidal neurons during sensory-motor behavior. Here, we employ electrophysiological and optical approaches in brain slices and behaving animals to investigate how excitatory synaptic input to this distal dendritic compartment influences neuronal output. We find that active dendritic integration throughout the apical dendritic tuft is highly compartmentalized by voltage-gated potassium (KV) channels. A high density of both transient and sustained KV channels was observed in all apical dendritic compartments. These channels potently regulated the interaction between apical dendritic tuft, trunk, and axosomatic integration zones to control neuronal output in vitro as well as the engagement of dendritic nonlinear processing in vivo during sensory-motor behavior. Thus, KV channels dynamically tune the interaction between active dendritic integration compartments in layer 5B pyramidal neurons to shape behaviorally relevant neuronal computations.

A central problem in neuroscience is reconstructing neuronal circuits on the synapse level. Due to a wide range of scales in brain architecture such reconstruction requires imaging that is both high-resolution and high-throughput. Existing electron microscopy (EM) techniques possess required resolution in the lateral plane and either high-throughput or high depth resolution but not both. Here, we exploit recent advances in unsupervised learning and signal processing to obtain high depth-resolution EM images computationally without sacrificing throughput. First, we show that the brain tissue can be represented as a sparse linear combination of localized basis functions that are learned using high-resolution datasets. We then develop compressive sensing-inspired techniques that can reconstruct the brain tissue from very few (typically 5) tomographic views of each section. This enables tracing of neuronal processes and, hence, high throughput reconstruction of neural circuits on the level of individual synapses.

Drug addiction and obesity share the core feature that those afflicted by the disorders express a desire to limit drug or food consumption yet persist despite negative consequences. Emerging evidence suggests that the compulsivity that defines these disorders may arise, to some degree at least, from common underlying neurobiological mechanisms. In particular, both disorders are associated with diminished striatal dopamine D2 receptor (D2R) availability, likely reflecting their decreased maturation and surface expression. In striatum, D2Rs are expressed by approximately half of the principal medium spiny projection neurons (MSNs), the striatopallidal neurons of the so-called 'indirect' pathway. D2Rs are also expressed presynaptically on dopamine terminals and on cholinergic interneurons. This heterogeneity of D2R expression has hindered attempts, largely using traditional pharmacological approaches, to understand their contribution to compulsive drug or food intake. The emergence of genetic technologies to target discrete populations of neurons, coupled to optogenetic and chemicogenetic tools to manipulate their activity, have provided a means to dissect striatopallidal and cholinergic contributions to compulsivity. Here, we review recent evidence supporting an important role for striatal D2R signaling in compulsive drug use and food intake. We pay particular attention to striatopallidal projection neurons and their role in compulsive responding for food and drugs. Finally, we identify opportunities for future obesity research using known mechanisms of addiction as a heuristic, and leveraging new tools to manipulate activity of specific populations of striatal neurons to understand their contributions to addiction and obesity.