A complex nervous system requires precise numbers of various neuronal types produced with exquisite spatiotemporal control. This striking diversity is generated by a limited number of neural stem cells (NSC), where spatial and temporal patterning intersect. Drosophila is a genetically tractable model system that has significant advantages for studying stem cell biology and neuronal fate specification. Here we review the latest findings in the rich literature of temporal patterning of neuronal identity in the Drosophila central nervous system. Rapidly changing consecutive transcription factors expressed in NSCs specify short series of neurons with considerable differences. More slowly progressing changes are orchestrated by NSC intrinsic temporal factor gradients which integrate extrinsic signals to coordinate nervous system and organismal development.

PURPOSE: To develop switchable and tunable labels with high contrast ratio for MRI using magnetocaloric materials that have sharp first-order magnetic phase transitions at physiological temperatures and typical MRI magnetic field strengths.

METHODS: A prototypical magnetocaloric material iron-rhodium (FeRh) was prepared by melt mixing, high-temperature annealing, and ice-water quenching. Temperature- and magnetic field-dependent magnetization measurements of wire-cut FeRh samples were performed on a vibrating sample magnetometer. Temperature-dependent MRI of FeRh samples was performed on a 4.7T MRI.

RESULTS: Temperature-dependent MRI clearly demonstrated image contrast changes due to the sharp magnetic state transition of the FeRh samples in the MRI magnetic field (4.7T) and at a physiologically relevant temperature (~37°C).

CONCLUSION: A magnetocaloric material, FeRh, was demonstrated to act as a high contrast ratio switchable MRI contrast agent due to its sharp first-order magnetic phase transition in the DC magnetic field of MRI and at physiologically relevant temperatures. A wide range of magnetocaloric materials are available that can be tuned by materials science techniques to optimize their response under MRI-appropriate conditions and be controllably switched in situ with temperature, magnetic field, or a combination of both.

Sensory navigation results from coordinated transitions between distinct behavioral programs. During chemotaxis in the larva, the detection of positive odor gradients extends runs while negative gradients promote stops and turns. This algorithm represents a foundation for the control of sensory navigation across phyla. In the present work, we identified an olfactory descending neuron, PDM-DN, which plays a pivotal role in the organization of stops and turns in response to the detection of graded changes in odor concentrations. Artificial activation of this descending neuron induces deterministic stops followed by the initiation of turning maneuvers through head casts. Using electron microscopy, we reconstructed the main pathway that connects the PDM-DN neuron to the peripheral olfactory system and to the pre-motor circuit responsible for the actuation of forward peristalsis. Our results set the stage for a detailed mechanistic analysis of the sensorimotor conversion of graded olfactory inputs into action selection to perform goal-oriented navigation.

Simultaneous recordings of large populations of neurons in behaving animals allow detailed observation of high-dimensional, complex brain activity. However, experimental approaches often focus on singular behavioral paradigms or brain areas. Here, we recorded whole-brain neuronal activity of larval zebrafish presented with a battery of visual stimuli while recording fictive motor output. We identified neurons tuned to each stimulus type and motor output and discovered groups of neurons in the anterior hindbrain that respond to different stimuli eliciting similar behavioral responses. These convergent sensorimotor representations were only weakly correlated to instantaneous motor activity, suggesting that they critically inform, but do not directly generate, behavioral choices. To catalog brain-wide activity beyond explicit sensorimotor processing, we developed an unsupervised clustering technique that organizes neurons into functional groups. These analyses enabled a broad overview of the functional organization of the brain and revealed numerous brain nuclei whose neurons exhibit concerted activity patterns.

In eukaryotic cells, organelles and the cytoskeleton undergo highly dynamic yet organized interactions capable of orchestrating complex cellular functions. Visualizing these interactions requires noninvasive, long-duration imaging of the intracellular environment at high spatiotemporal resolution and low background. To achieve these normally opposing goals, we developed grazing incidence structured illumination microscopy (GI-SIM) that is capable of imaging dynamic events near the basal cell cortex at 97-nm resolution and 266 frames/s over thousands of time points. We employed multi-color GI-SIM to characterize the fast dynamic interactions of diverse organelles and the cytoskeleton, shedding new light on the complex behaviors of these structures. Precise measurements of microtubule growth or shrinkage events helped distinguish among models of microtubule dynamic instability. Analysis of endoplasmic reticulum (ER) interactions with other organelles or microtubules uncovered new ER remodeling mechanisms, such as hitchhiking of the ER on motile organelles. Finally, ER-mitochondria contact sites were found to promote both mitochondrial fission and fusion.

Automatic image segmentation is critical to scale up electron microscope (EM) connectome reconstruction. To this end, segmentation competitions, such as CREMI and SNEMI, exist to help researchers evaluate segmentation algorithms with the goal of improving them. Because generating ground truth is time-consuming, these competitions often fail to capture the challenges in segmenting larger datasets required in connectomics. More generally, the common metrics for EM image segmentation do not emphasize impact on downstream analysis and are often not very useful for isolating problem areas in the segmentation. For example, they do not capture connectivity information and often over-rate the quality of a segmentation as we demonstrate later. To address these issues, we introduce a novel strategy to enable evaluation of segmentation at large scales both in a supervised setting, where ground truth is available, or an unsupervised setting. To achieve this, we first introduce new metrics more closely aligned with the use of segmentation in downstream analysis and reconstruction. In particular, these include synapse connectivity and completeness metrics that provide both meaningful and intuitive interpretations of segmentation quality as it relates to the preservation of neuron connectivity. Also, we propose measures of segmentation correctness and completeness with respect to the percentage of "orphan" fragments and the concentrations of self-loops formed by segmentation failures, which are helpful in analysis and can be computed without ground truth. The introduction of new metrics intended to be used for practical applications involving large datasets necessitates a scalable software ecosystem, which is a critical contribution of this paper. To this end, we introduce a scalable, flexible software framework that enables integration of several different metrics and provides mechanisms to evaluate and debug differences between segmentations. We also introduce visualization software to help users to consume the various metrics collected. We evaluate our framework on two relatively large public groundtruth datasets providing novel insights on example segmentations.

Reconstructing a connectome from an EM dataset often requires a large effort of proofreading automatically generated segmentations. While many tools exist to enable tracing or proofreading, recent advances in EM imaging and segmentation quality suggest new strategies and pose unique challenges for tool design to accelerate proofreading. Namely, we now have access to very large multi-TB EM datasets where (1) many segments are largely correct, (2) segments can be very large (several GigaVoxels), and where (3) several proofreaders and scientists are expected to collaborate simultaneously. In this paper, we introduce NeuTu as a solution to efficiently proofread large, high-quality segmentation in a collaborative setting. NeuTu is a client program of our high-performance, scalable image database called DVID so that it can easily be scaled up. Besides common features of typical proofreading software, NeuTu tames unprecedentedly large data with its distinguishing functions, including: (1) low-latency 3D visualization of large mutable segmentations; (2) interactive splitting of very large false merges with highly optimized semi-automatic segmentation; (3) intuitive user operations for investigating or marking interesting points in 3D visualization; (4) visualizing proofreading history of a segmentation; and (5) real-time collaborative proofreading with lock-based concurrency control. These unique features have allowed us to manage the workflow of proofreading a large dataset smoothly without dividing them into subsets as in other segmentation-based tools. Most importantly, NeuTu has enabled some of the largest connectome reconstructions as well as interesting discoveries in the fly brain.

The transient receptor potential canonical subfamily member 5 (TRPC5) is a non-selective calcium-permeant cation channel. As a depolarizing channel, its function is studied in the central nervous system and kidney. TRPC5 forms heteromultimers with TRPC1, but also forms homomultimers. It can be activated by reducing agents through reduction of the extracellular disulfide bond. Here we present the 2.9 Å resolution electron cryo-microscopy (cryo-EM) structure of TRPC5. The structure of TRPC5 in its apo state is partially open, which may be related to the weak activation of TRPC5 in response to extracellular pH. We also report the conserved negatively charged residues of the cation binding site located in the hydrophilic pocket between S2 and S3. Comparison of the TRPC5 structure to previously determined structures of other TRPC and TRP channels reveals differences in the extracellular pore domain and in the length of the S3 helix. Together, these results shed light on the structural features that contribute to the specific activation mechanism of the receptor-activated TRPC5.

Fruit flies recognize hundreds of ecologically relevant odors and respond appropriately to them. The complexity, redundancy and interconnectedness of the olfactory machinery complicate efforts to pinpoint the functional contributions of any component neuron or receptor to behavior. Some contributions can only be elucidated in flies that carry multiple mutations and transgenes, but the production of such flies is currently labor-intensive and time-consuming. Here, we describe a set of transgenic flies that express the GAL80 in specific olfactory sensory neurons (). The GAL80s effectively and specifically subtract the activities of GAL4-driven transgenes that impart anatomical and physiological phenotypes. can allow researchers to efficiently activate only one or a few types of functional neurons in an otherwise nonfunctional olfactory background. Such experiments will improve our understanding of the mechanistic connections between odorant inputs and behavioral outputs at the resolution of only a few functional neurons.