Eviatar Yemini.

Interview with Eviatar Yemini, who studies how neurobehavioral circuits grow and evolve to meet the needs at different stages of development at UMass Chan Medical School.

Learning dynamic representations of the functional connectome in neurobiological networks.

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. The inference occurs in two major steps. First, pairwise non-linear affinities between neuronal traces from brain-wide calcium activity are organized by non-negative tensor factorization (NTF). Each factor specifies which groups of neurons are most likely interacting for an inferred interval in time, and for which animals. Finally, a generative model that allows for weighted community detection is applied to the functional motifs produced by NTF to reveal a dynamic functional connectome. Since time codes the different experimental variables (e.g., application of chemical stimuli), this provides an atlas of neural motifs active during separate stages of an experiment (e.g., stimulus application or spontaneous behaviors). Results from our analysis are experimentally validated, confirming that our method is able to robustly predict causal interactions between neurons to generate behavior.

Deep learning-based aberration compensation improves contrast and resolution in fluorescence microscopy.

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. We use simulations to show that applying the trained 'de-aberration' networks outperforms alternative methods, and subsequently apply the networks to diverse datasets captured with confocal, light-sheet, multi-photon, and super-resolution microscopy. In all cases, the improved quality of the restored data facilitates qualitative image inspection and improves downstream image quantitation, including orientational analysis of blood vessels in mouse tissue and improved membrane and nuclear segmentation in C. elegans embryos.

Systems neuroscience: Foraging through serotonin's tangled web.

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.

Learning Probabilistic Piecewise Rigid Atlases of Model Organisms via Generative Deep Networks.

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 C. elegans 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. Of particular relevance, it also develops a deformable piecewise rigid atlas model which is regularized to preserve inter-observation distances between neighbors. These modeling considerations are shown to improve atlas construction and key-point alignment across a diversity of datasets with small sample sizes including neuron positions in C. elegans hermaphrodites, fluorescence microscopy of male C. elegans, and images of fruit fly wings. Code is accessible at https://github.com/amin-nejat/Deformable-Atlas.

Cell-specific effects of the sole C. elegans Daughterless/E protein homolog, HLH-2, on nervous system development.

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. To eliminate function of all proneuronal class I/II bHLH complexes, we therefore genetically removed maternal and zygotic hlh-2 gene activity. We observed broad effects on neurogenesis, but still detected normal neurogenesis in many distinct neuron-producing lineages of the central and peripheral nervous system. Moreover, we found that hlh-2 selectively affects some aspects of neuron differentiation while leaving others unaffected. Although our studies confirm the function of proneuronal class I/II bHLH complexes in many different lineages throughout a nervous system, we conclude that their function is not universal, but rather restricted by lineage, cell type and components of differentiation programs affected.

Neuropeptide signalling shapes feeding and reproductive behaviours in male Caenorhabditis elegans.

Sexual dimorphism occurs where different sexes of the same species display differences in characteristics not limited to reproduction. For the nematode Caenorhabditis elegans, 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. In this study, we show that the lury-1 neuropeptide gene shows a sexually dimorphic expression pattern; being expressed in pharyngeal neurons in both sexes but displaying additional expression in tail neurons only in the male. We also show that lury-1 mutant animals show sex differences in feeding behaviours, with pharyngeal pumping elevated in hermaphrodites but reduced in males. LURY-1 also modulates male mating efficiency, influencing motor events during contact with a hermaphrodite. Our findings indicate sex-specific roles of this peptide in feeding and reproduction in C. elegans, providing further insight into neuromodulatory control of sexually dimorphic behaviours.

Toward a more accurate 3D atlas of C. elegans neurons.

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. elegans datasets have been hampered by the limited accuracy of such atlases, especially for neurons present in the ventral nerve cord, and also by time-consuming manual elements of the alignment process. RESULTS: We present a novel automated alignment method for sparse and incomplete point clouds of the sort resulting from typical C. elegans fluorescence microscopy datasets. This method involves a tunable learning parameter and a kernel that enforces biologically realistic deformation. We also present a pipeline for creating alignment atlases from datasets of the recently developed NeuroPAL transgene. In combination, these advances allow us to label neurons in volumetric images with confidence much higher than previous methods. CONCLUSIONS: We release, to the best of our knowledge, the most complete full-body C. elegans 3D positional neuron atlas, incorporating positional variability derived from at least 7 animals per neuron, for the purposes of cell-type identity prediction for myriad applications (e.g., imaging neuronal activity, gene expression, and cell-fate).

Visualizing the organization and differentiation of the male-specific nervous system of C. elegans.

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. We provide several proofs of concept for using NeuroPAL to identify the sites of expression of gfp-tagged reporter genes and for cellular fate analysis by analyzing the effect of removal of several developmental patterning genes on neuronal identity acquisition. We use NeuroPAL and its intrinsic cohort of more than 40 distinct differentiation markers to show that, even though male-specific neurons are generated throughout all four larval stages, they execute their terminal differentiation program in a coordinated manner in the fourth larval stage. This coordinated wave of differentiation, which we call 'just-in-time' differentiation, couples neuronal maturation programs with the appearance of sexual organs.

Molecular topography of an entire nervous system.

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. For example, each neuron class expresses distinct codes of ∼23 neuropeptide genes and ∼36 neuropeptide receptors, delineating a complex and expansive "wireless" signaling network. To demonstrate the utility of this comprehensive gene expression catalog, we used computational approaches to (1) identify cis-regulatory elements for neuron-specific gene expression and (2) reveal adhesion proteins with potential roles in process placement and synaptic specificity. Our expression data are available at https://cengen.org and can be interrogated at the web application CengenApp. We expect that this neuron-specific directory of gene expression will spur investigations of underlying mechanisms that define anatomy, connectivity, and function throughout the C. elegans nervous system.

In silico analysis of the transcriptional regulatory logic of neuronal identity specification throughout the C. elegans nervous system.

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 Caenorhabditis elegans nervous system for the presence of DNA binding motifs of 136 neuronally expressed C. elegans transcription factors. Using a phylogenetic footprinting pipeline, we identify cis-regulatory motif enrichments among neuron class-specific gene batteries and we identify cognate transcription factors for 117 of the 118 neuron classes. In addition to predicting novel regulators of neuronal identities, our nervous system-wide analysis at single cell resolution supports the hypothesis that many transcription factors directly co-regulate the cohort of effector genes that define a neuron type, thereby corroborating the concept of so-called terminal selectors of neuronal identity. Our analysis provides a blueprint for how individual components of an entire nervous system are genetically specified.

Methods for analyzing neuronal structure and activity in Caenorhabditis elegans.

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. The transparency of the animal makes it possible to visualize and identify neurons in living animals with fluorescent probes. These methods have been recently enhanced for the efficient use of neuron-specific reporter genes. Because of its simple structure, for a number of years, C. elegans has been at the forefront of connectomic studies defining synaptic connectivity by electron microscopy. This field is burgeoning with new, more powerful techniques, and recommended up-to-date methods are here described that encourage the possibility of new work in C. elegans. Fluorescent probes for single synapses and synaptic connections have allowed verification of the EM reconstructions and for experimental approaches to synapse formation. Advances in microscopy and in fluorescent reporters sensitive to Ca2+ levels have opened the way to observing activity within single neurons across the entire nervous system.

Piecemeal regulation of convergent neuronal lineages by bHLH transcription factors in Caenorhabditis elegans.

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. elegans Atonal homolog lin-32 is differentially expressed in neuronal lineages that give rise to left/right or radially symmetric class members. Loss of lin-32 results in the selective loss of the expression of pan-neuronal markers and terminal selector-type transcription factors that confer neuron class-specific features. Another basic helix-loop-helix (bHLH) gene, the Achaete-Scute homolog hlh-14, is expressed in a mirror image pattern relative to lin-32 and is required to induce neuronal identity and terminal selector expression on the contralateral side of the animal. These findings demonstrate that distinct lineage histories converge via different bHLH factors at the level of induction of terminal selector identity determinants, which thus serve as integrators of distinct lineage histories. We also describe neuron-to-neuron identity transformations in lin-32 mutants, which we propose to also be the result of misregulation of terminal selector gene expression.

NeuroPAL: A Multicolor Atlas for Whole-Brain Neuronal Identification in C. elegans.

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). NeuroPAL worms share a stereotypical multicolor fluorescence map for the entire hermaphrodite nervous system that resolves all neuronal identities. Neurons labeled with NeuroPAL do not exhibit fluorescence in the green, cyan, or yellow emission channels, allowing the transgene to be used with numerous reporters of gene expression or neuronal dynamics. We showcase three applications that leverage NeuroPAL for nervous-system-wide neuronal identification. First, we determine the brainwide expression patterns of all metabotropic receptors for acetylcholine, GABA, and glutamate, completing a map of this communication network. Second, we uncover changes in cell fate caused by transcription factor mutations. Third, we record brainwide activity in response to attractive and repulsive chemosensory cues, characterizing multimodal coding for these stimuli.

Unique homeobox codes delineate all the neuron classes of C. elegans.

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 identity1. Here we show, through examination of the expression of all of the conserved homeodomain proteins encoded by the Caenorhabditis elegans genome2, 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. Computational and genetic loss-of-function analyses corroborate the notion that homeodomain proteins not only provide unique descriptors of neuron type, but also have a critical role in specifying neuronal identity. We speculate that the pervasive use of homeobox genes in defining unique neuronal identities reflects the evolutionary history of neuronal cell-type specification.

The connectome of the Caenorhabditis elegans pharynx.

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. Contrasting the previous classification of pharyngeal neurons into distinct inter- and motor neuron classes, we provide evidence that most pharyngeal neurons are also likely sensory neurons and most, if not all, pharyngeal neurons also classify as motor neurons. Together with the extensive cross-connectivity among pharyngeal neurons, which is more widespread than previously realized, the sensory-motor characteristics of most neurons define a shallow network architecture of the pharyngeal connectome. Network analysis reveals that the patterns of neuronal connections are organized into putative computational modules that reflect the known functional domains of the pharynx. Compared with the somatic nervous system, pharyngeal neurons both physically associate with a larger fraction of their neighbors and create synapses with a greater proportion of their neighbors. We speculate that the overall architecture of the pharyngeal nervous system may be reminiscent of the architecture of ancestral, primitive nervous systems.

The Multilayer Connectome of Caenorhabditis elegans.

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. The monoamine and neuropeptide networks exhibit distinct topological properties, with the monoamine network displaying a highly disassortative star-like structure with a rich-club of interconnected broadcasting hubs, and the neuropeptide network showing a more recurrent, highly clustered topology. Despite the low degree of overlap between the extrasynaptic (or wireless) and synaptic (or wired) connectomes, we find highly significant multilink motifs of interaction, pinpointing locations in the network where aminergic and neuropeptide signalling modulate synaptic activity. Thus, the C. elegans connectome can be mapped as a multiplex network with synaptic, gap junction, and neuromodulator layers representing alternative modes of interaction between neurons. This provides a new topological plan for understanding how aminergic and peptidergic modulation of behaviour is achieved by specific motifs and loci of integration between hard-wired synaptic or junctional circuits and extrasynaptic signals wirelessly broadcast from a small number of modulatory neurons.

Global brain dynamics embed the motor command sequence of Caenorhabditis elegans.

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. This organization defines the assembly of motor commands into a string of run-and-turn action sequence cycles, including decisions between alternative behaviors. These dynamics serve as a robust scaffold for action selection in response to sensory input. This study shows that the coordination of neuronal activity patterns into global brain dynamics underlies the high-level organization of behavior.

Tracking Single C. elegans Using a USB Microscope on a Motorized Stage.

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. In this chapter, we describe how to calibrate a single-worm tracker consisting of a USB microscope mounted on a motorized stage and how to record and analyze movies of worms crawling on food. The resulting quantitative phenotypic fingerprint can sensitively identify differences between mutant and wild-type worms.