Publications by authors named "Eviatar Yemini"

We develop a data harmonization approach for volumetric microscopy data, still or video, consisting of a standardized format, data pre-processing techniques, and a set of human-in-the-loop machine learning based analysis software tools. We unify a diverse collection of 118 whole-brain neural activity imaging datasets from 5 labs, storing these and accompanying tools in an online repository called WormID (wormid.org).

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The static synaptic connectivity of neuronal circuits stands in direct contrast to the dynamics of their function. As in changing community interactions, different neurons can participate actively in various combinations to effect behaviors at different times. We introduce an unsupervised approach to learn the dynamic affinities between neurons in live, behaving animals, and to reveal which communities form among neurons at different times.

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Optical aberrations hinder fluorescence microscopy of thick samples, reducing image signal, contrast, and resolution. Here we introduce a deep learning-based strategy for aberration compensation, improving image quality without slowing image acquisition, applying additional dose, or introducing more optics into the imaging path. Our method (i) introduces synthetic aberrations to images acquired on the shallow side of image stacks, making them resemble those acquired deeper into the volume and (ii) trains neural networks to reverse the effect of these aberrations.

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Serotonin signaling is conserved in regulating animal behaviors. A new paper decodes the nonlinear effects of all serotonin receptor combinations on foraging behaviors. The authors introduce a brain-wide multiscale method to dissect receptor dynamics, receptor effects on neural activity, and resulting behavioral changes.

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Atlases are crucial to imaging statistics as they enable the standardization of inter-subject and inter-population analyses. While existing atlas estimation methods based on fluid/elastic/diffusion registration yield high-quality results for the human brain, these deformation models do not extend to a variety of other challenging areas of neuroscience such as the anatomy of worms and fruit flies. To this end, this work presents a general probabilistic deep network-based framework for atlas estimation and registration which can flexibly incorporate various deformation models and levels of keypoint supervision that can be applied to a wide class of model organisms.

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Are there common mechanisms of neurogenesis used throughout an entire nervous system? We explored to what extent canonical proneural class I/II bHLH complexes are responsible for neurogenesis throughout the entire Caenorhabditis elegans nervous system. Distinct, lineage-specific proneural class II bHLH factors are generally thought to operate via interaction with a common, class I bHLH subunit, encoded by Daughterless in flies, the E proteins in vertebrates and HLH-2 in C. elegans.

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Sexual dimorphism occurs where different sexes of the same species display differences in characteristics not limited to reproduction. For the nematode , in which the complete neuroanatomy has been solved for both hermaphrodites and males, sexually dimorphic features have been observed both in terms of the number of neurons and in synaptic connectivity. In addition, male behaviours, such as food-leaving to prioritise searching for mates, have been attributed to neuropeptides released from sex-shared or sex-specific neurons.

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Background: Determining cell identity in volumetric images of tagged neuronal nuclei is an ongoing challenge in contemporary neuroscience. Frequently, cell identity is determined by aligning and matching tags to an "atlas" of labeled neuronal positions and other identifying characteristics. Previous analyses of such C.

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Sex differences in the brain are prevalent throughout the animal kingdom and particularly well appreciated in the nematode Caenorhabditis elegans, where male animals contain a little-studied set of 93 male-specific neurons. To make these neurons amenable for future study, we describe here how a multicolor reporter transgene, NeuroPAL, is capable of visualizing the distinct identities of all male-specific neurons. We used NeuroPAL to visualize and characterize a number of features of the male-specific nervous system.

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We have produced gene expression profiles of all 302 neurons of the C. elegans nervous system that match the single-cell resolution of its anatomy and wiring diagram. Our results suggest that individual neuron classes can be solely identified by combinatorial expression of specific gene families.

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The generation of the enormous diversity of neuronal cell types in a differentiating nervous system entails the activation of neuron type-specific gene batteries. To examine the regulatory logic that controls the expression of neuron type-specific gene batteries, we interrogate single cell expression profiles of all 118 neuron classes of the nervous system for the presence of DNA binding motifs of 136 neuronally expressed transcription factors. Using a phylogenetic footprinting pipeline, we identify regulatory motif enrichments among neuron class-specific gene batteries and we identify cognate transcription factors for 117 of the 118 neuron classes.

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The model research animal Caenorhabditis elegans has unique properties making it particularly advantageous for studies of the nervous system. The nervous system is composed of a stereotyped complement of neurons connected in a consistent manner. Here, we describe methods for studying nervous system structure and function.

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Cells of the same type can be generated by distinct cellular lineages that originate in different parts of the developing embryo ('lineage convergence'). Several Caenorhabditis elegans neuron classes composed of left/right or radially symmetric class members display such lineage convergence. We show here that the C.

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Comprehensively resolving neuronal identities in whole-brain images is a major challenge. We achieve this in C. elegans by engineering a multicolor transgene called NeuroPAL (a neuronal polychromatic atlas of landmarks).

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It is not known at present whether neuronal cell-type diversity-defined by cell-type-specific anatomical, biophysical, functional and molecular signatures-can be reduced to relatively simple molecular descriptors of neuronal identity. Here we show, through examination of the expression of all of the conserved homeodomain proteins encoded by the Caenorhabditis elegans genome, that the complete set of 118 neuron classes of C. elegans can be described individually by unique combinations of the expression of homeodomain proteins, thereby providing-to our knowledge-the simplest currently known descriptor of neuronal diversity.

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Detailed anatomical maps of individual organs and entire animals have served as invaluable entry points for ensuing dissection of their evolution, development, and function. The pharynx of the nematode Caenorhabditis elegans is a simple neuromuscular organ with a self-contained, autonomously acting nervous system, composed of 20 neurons that fall into 14 anatomically distinct types. Using serial electron micrograph (EM) reconstruction, we re-evaluate here the connectome of the pharyngeal nervous system, providing a novel and more detailed view of its structure and predicted function.

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Connectomics has focused primarily on the mapping of synaptic links in the brain; yet it is well established that extrasynaptic volume transmission, especially via monoamines and neuropeptides, is also critical to brain function and occurs primarily outside the synaptic connectome. We have mapped the putative monoamine connections, as well as a subset of neuropeptide connections, in C. elegans based on new and published gene expression data.

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While isolated motor actions can be correlated with activities of neuronal networks, an unresolved problem is how the brain assembles these activities into organized behaviors like action sequences. Using brain-wide calcium imaging in Caenorhabditis elegans, we show that a large proportion of neurons across the brain share information by engaging in coordinated, dynamical network activity. This brain state evolves on a cycle, each segment of which recruits the activities of different neuronal sub-populations and can be explicitly mapped, on a single trial basis, to the animals' major motor commands.

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Locomotion and gross morphology have been important phenotypes for C. elegans genetics since the inception of the field and remain relevant. In parallel with developments in genome sequencing and editing, phenotyping methods have become more automated and quantitative, making it possible to detect subtle differences between mutants and wild-type animals.

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Although undulatory swimming is observed in many organisms, the neuromuscular basis for undulatory movement patterns is not well understood. To better understand the basis for the generation of these movement patterns, we studied muscle activity in the nematode Caenorhabditis elegans. Caenorhabditis elegans exhibits a range of locomotion patterns: in low viscosity fluids the undulation has a wavelength longer than the body and propagates rapidly, while in high viscosity fluids or on agar media the undulatory waves are shorter and slower.

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Using low-cost automated tracking microscopes, we have generated a behavioral database for 305 Caenorhabditis elegans strains, including 76 mutants with no previously described phenotype. The growing database currently consists of 9,203 short videos segmented to extract behavior and morphology features, and these videos and feature data are available online for further analysis. The database also includes summary statistics for 702 measures with statistical comparisons to wild-type controls so that phenotypes can be identified and understood by users.

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Visible phenotypes based on locomotion and posture have played a critical role in understanding the molecular basis of behavior and development in Caenorhabditis elegans and other model organisms. However, it is not known whether these human-defined features capture the most important aspects of behavior for phenotypic comparison or whether they are sufficient to discover new behaviors. Here we show that four basic shapes, or eigenworms, previously described for wild-type worms, also capture mutant shapes, and that this representation can be used to build a dictionary of repetitive behavioral motifs in an unbiased way.

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The simple and well-characterized nervous system of C. elegans facilitates the analysis of mechanisms controlling behavior. Locomotion is a major behavioral output governed by multiple external and internal signals.

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Neurobiological research in genetically tractable organisms relies heavily on robust assays for behavioral phenotypes. The simple body plan of the nematode Caenorhabditis elegans makes it particularly amenable to the use of automated microscopy and image analysis to describe behavioral patterns quantitatively. Forward genetic screens and screens of drug libraries require high-throughput phenotyping, a task traditionally incompatible with manual scoring of quantitatively varying behaviors.

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Synopsis of recent research by authors named "Eviatar Yemini"

  • Eviatar Yemini's research focuses on innovative methodologies in neuroscience, particularly in enhancing imaging techniques, understanding neuron dynamics, and analyzing neurobiological networks.
  • His work includes the development of data harmonization approaches for comprehensive neuron identification and analysis through the integration of diverse imaging datasets, as demonstrated in the WormID repository project.
  • He also explores dynamic representations of neuronal interactions and the impact of signaling on animal behavior, contributing significant insights into neurogenesis and sexually dimorphic traits in model organisms like C. elegans.