Neurotransmitter maps are important complements to anatomical maps and represent an invaluable resource to understand nervous system function and development. We report here a comprehensive map of neurons in the C. elegans nervous system that contain the neurotransmitter GABA, revealing twice as many GABA-positive neuron classes as previously reported. We define previously unknown glia-like cells that take up GABA, as well as 'GABA uptake neurons' which do not synthesize GABA but take it up from the extracellular environment, and we map the expression of previously uncharacterized ionotropic GABA receptors. We use the map of GABA-positive neurons for a comprehensive analysis of transcriptional regulators that define the GABA phenotype. We synthesize our findings of specification of GABAergic neurons with previous reports on the specification of glutamatergic and cholinergic neurons into a nervous system-wide regulatory map which defines neurotransmitter specification mechanisms for more than half of all neuron classes in C. elegans.

/pdf/a-cellular-and-regulatory-map-of-the-cholinergic-nervous-o3n1qk940u.pdf

A cellular and regulatory map of the cholinergic nervous system of C. elegans

Nested Neuronal Dynamics Orchestrate a Behavioral Hierarchy across Timescales.

Localizing the sources of stimuli is essential. Most organisms cannot eat, mate, or escape without knowing where the relevant stimuli originate. For many, if not most, animals, olfaction plays an essential role in search. While microorganismal chemotaxis is relatively well understood, in larger animals the algorithms and mechanisms of olfactory search remain mysterious. In this symposium, we will present recent advances in our understanding of olfactory search in flies and rodents. Despite their different sizes and behaviors, both species must solve similar problems, including meeting the challenges of turbulent airflow, sampling the environment to optimize olfactory information, and incorporating odor information into broader navigational systems.

https://www.jneurosci.org/content/jneuro/38/44/9383.full.pdf

Algorithms for Olfactory Search across Species.

Micro-connectomics involves determining the principles of how neuronal networks are organized at the cellular level. In this Review, Schroter, Paulsen and Bullmore examine studies that have provided insight into the network organization of relatively small, as well as more complex, nervous systems.

Micro-connectomics: probing the organization of neuronal networks at the cellular scale

Cell- or network-driven oscillators underlie motor rhythmicity. The identity of C. elegans oscillators remains unknown. Through cell ablation, electrophysiology, and calcium imaging, we show: (1) forward and backward locomotion is driven by different oscillators; (2) the cholinergic and excitatory A-class motor neurons exhibit intrinsic and oscillatory activity that is sufficient to drive backward locomotion in the absence of premotor interneurons; (3) the UNC-2 P/Q/N high-voltage-activated calcium current underlies A motor neuron's oscillation; (4) descending premotor interneurons AVA, via an evolutionarily conserved, mixed gap junction and chemical synapse configuration, exert state-dependent inhibition and potentiation of A motor neuron's intrinsic activity to regulate backward locomotion. Thus, motor neurons themselves derive rhythms, which are dually regulated by the descending interneurons to control the reversal motor state. These and previous findings exemplify compression: essential circuit properties are conserved but executed by fewer numbers and layers of neurons in a small locomotor network.

/pdf/excitatory-motor-neurons-are-local-oscillators-for-backward-2s0ga1h25e.pdf

Excitatory motor neurons are local oscillators for backward locomotion.

Random search is a behavioral strategy used by organisms from bacteria to humans to locate food that is randomly distributed and undetectable at a distance. We investigated this behavior in the nematode Caenorhabditis elegans, an organism with a small, well-described nervous system. Here we formulate a mathematical model of random search abstracted from the C. elegans connectome and fit to a large-scale kinematic analysis of C. elegans behavior at submicron resolution. The model predicts behavioral effects of neuronal ablations and genetic perturbations, as well as unexpected aspects of wild type behavior. The predictive success of the model indicates that random search in C. elegans can be understood in terms of a neuronal flip-flop circuit involving reciprocal inhibition between two populations of stochastic neurons. Our findings establish a unified theoretical framework for understanding C. elegans locomotion and a testable neuronal model of random search that can be applied to other organisms.

/pdf/a-stochastic-neuronal-model-predicts-random-search-behaviors-vsimbha0fv.pdf

Steven B Augustine

Papers

A stochastic neuronal model predicts random search behaviors at multiple spatial scales in C. elegans .