Roles for Multifunctional and Specialized Spinal Interneurons During Motor Pattern Generation in Tadpoles, Zebrafish Larvae, and Turtles

The hindbrain and spinal cord can produce multiple forms of locomotion, escape, and withdrawal behaviors and (in limbed vertebrates) site-specific scratching. Until recently, the prevailing view was that the same classes of central nervous system neurons generate multiple kinds of movements, either through reconfiguration of a single, shared network or through an increase in the number of neurons recruited within each class. The mechanisms involved in selecting and generating different motor patterns have recently been explored in detail in some non-mammalian, vertebrate model systems. Work on the hatchling Xenopus tadpole, the larval zebrafish, and the adult turtle has now revealed that distinct kinds of motor patterns are actually selected and generated by combinations of multifunctional and specialized spinal interneurons. Multifunctional interneurons may form a core, multipurpose circuit that generates elements of coordinated motor output utilized in multiple behaviors, such as left-right alternation. But, in addition, specialized spinal interneurons including separate glutamatergic and glycinergic classes are selectively activated during specific patterns: escape-withdrawal, swimming and struggling in tadpoles and zebrafish, and limb withdrawal and scratching in turtles. These specialized neurons can contribute by changing the way central pattern generator (CPG) activity is initiated and by altering CPG composition and operation. The combined use of multifunctional and specialized neurons is now established as a principle of organization across a range of vertebrates. Future research may reveal common patterns of multifunctionality and specialization among interneurons controlling diverse movements and whether similar mechanisms exist in higher-order brain circuits that select among a wider array of complex movements

Studying the role of axon fasciculation during development in a computational model of the Xenopus tadpole spinal cord

Abstract During nervous system development growing axons can interact with each other, for example by adhering together in order to produce bundles (fasciculation). How does such axon-axon interaction affect the resulting axonal trajectories, and what are the possible benefits of this process in terms of network function? In this paper we study these questions by adapting an existing computational model of the development of neurons in the Xenopus tadpole spinal cord to include interactions between axons. We demonstrate that even relatively weak attraction causes bundles to appear, while if axons weakly repulse each other their trajectories diverge such that they fill the available space. We show how fasciculation can help to ensure axons grow in the correct location for proper network formation when normal growth barriers contain gaps, and use a functional spiking model to show that fasciculation allows the network to generate reliable swimming behaviour even when overall synapse counts are artificially lowered. Although we study fasciculation in one particular organism, our approach to modelling axon growth is general and can be widely applied to study other nervous systems

Modeling the connectome of a simple spinal cord.

In this paper we develop a computational model of the anatomy of a spinal cord. We address a long-standing ambition of neuroscience to understand the structure-function problem by modeling the complete spinal cord connectome map in the 2-day old hatchling Xenopus tadpole. Our approach to modeling neuronal connectivity is based on developmental processes of axon growth. A simple mathematical model of axon growth allows us to reconstruct a biologically realistic connectome of the tadpole spinal cord based on neurobiological data. In our model we distribute neuron cell bodies and dendrites on both sides of the body based on experimental measurements. If growing axons cross the dendrite of another neuron, they make a synaptic contact with a defined probability. The total neuronal network contains ∼1,500 neurons of six cell-types with a total of ∼120,000 connections. The anatomical model contains random components so each repetition of the connectome reconstruction procedure generates a different neuronal network, though all share consistent features such as distributions of cell bodies, dendrites, and axon lengths. Our study reveals a complex structure for the connectome with many interesting specific features including contrasting distributions of connection length distributions. The connectome also shows some similarities to connectivity graphs for other animals such as the global neuronal network of C. elegans. In addition to the interesting intrinsic properties of the connectome, we expect the ability to grow and analyze a biologically realistic spinal cord connectome will provide valuable insights into the properties of the real neuronal networks underlying simple behavior

Axon and dendrite geography predict the specificity of synaptic connections in a functioning spinal cord network

<p>Abstract</p> <p>Background</p> <p>How specific are the synaptic connections formed as neuronal networks develop and can simple rules account for the formation of functioning circuits? These questions are assessed in the spinal circuits controlling swimming in hatchling frog tadpoles. This is possible because detailed information is now available on the identity and synaptic connections of the main types of neuron.</p> <p>Results</p> <p>The probabilities of synapses between 7 types of identified spinal neuron were measured directly by making electrical recordings from 500 pairs of neurons. For the same neuron types, the dorso-ventral distributions of axons and dendrites were measured and then used to calculate the probabilities that axons would encounter particular dendrites and so potentially form synaptic connections. Surprisingly, synapses were found between all types of neuron but contact probabilities could be predicted simply by the anatomical overlap of their axons and dendrites. These results suggested that synapse formation may not require axons to recognise specific, correct dendrites. To test the plausibility of simpler hypotheses, we first made computational models that were able to generate longitudinal axon growth paths and reproduce the axon distribution patterns and synaptic contact probabilities found in the spinal cord. To test if probabilistic rules could produce functioning spinal networks, we then made realistic computational models of spinal cord neurons, giving them established cell-specific properties and connecting them into networks using the contact probabilities we had determined. A majority of these networks produced robust swimming activity.</p> <p>Conclusion</p> <p>Simple factors such as morphogen gradients controlling dorso-ventral soma, dendrite and axon positions may sufficiently constrain the synaptic connections made between different types of neuron as the spinal cord first develops and allow functional networks to form. Our analysis implies that detailed cellular recognition between spinal neuron types may not be necessary for the reliable formation of functional networks to generate early behaviour like swimming.</p

Can simple rules control development of a pioneer vertebrate neuronal network generating behavior?

How do the pioneer networks in the axial core of the vertebrate nervous system first develop? Fundamental to understanding any full-scale neuronal network is knowledge of the constituent neurons, their properties, synaptic interconnections, and normal activity. Our novel strategy uses basic developmental rules to generate model networks that retain individual neuron and synapse resolution and are capable of reproducing correct, whole animal responses. We apply our developmental strategy to young Xenopus tadpoles, whose brainstem and spinal cord share a core vertebrate plan, but at a tractable complexity. Following detailed anatomical and physiological measurements to complete a descriptive library of each type of spinal neuron, we build models of their axon growth controlled by simple chemical gradients and physical barriers. By adding dendrites and allowing probabilistic formation of synaptic connections, we reconstruct network connectivity among up to 2000 neurons. When the resulting "network" is populated by model neurons and synapses, with properties based on physiology, it can respond to sensory stimulation by mimicking tadpole swimming behavior. This functioning model represents the most complete reconstruction of a vertebrate neuronal network that can reproduce the complex, rhythmic behavior of a whole animal. The findings validate our novel developmental strategy for generating realistic networks with individual neuron- and synapse-level resolution. We use it to demonstrate how early functional neuronal connectivity and behavior may in life result from simple developmental "rules," which lay out a scaffold for the vertebrate CNS without specific neuron-to-neuron recognition

Exogenous double-stranded RNA inhibits the infection physiology of rust fungi to reduce symptoms in planta

Rust fungi (Pucciniales) are a diverse group of plant pathogens in natural and agricultural systems. They pose ongoing threats to the diversity of native flora and cause annual crop yield losses. Agricultural rusts are predominantly managed with fungicides and breeding for resistance, but new control strategies are needed on non-agricultural plants and in fragile ecosystems. RNA interference (RNAi) induced by exogenous double-stranded RNA (dsRNA) has promise as a sustainable approach for managing plant-pathogenic fungi, including rust fungi. We investigated the mechanisms and impact of exogenous dsRNA on rust fungi through in vitro and whole-plant assays using two species as models, Austropuccinia psidii (the cause of myrtle rust) and Coleosporium plumeriae (the cause of frangipani rust). In vitro, dsRNA either associates externally or is internalized by urediniospores during the early stages of germination. The impact of dsRNA on rust infection architecture was examined on artificial leaf surfaces. dsRNA targeting predicted essential genes significantly reduced germination and inhibited development of infection structures, namely appressoria and penetration pegs. Exogenous dsRNA sprayed onto 1-year-old trees significantly reduced myrtle rust symptoms. Furthermore, we used comparative genomics to assess the wide-scale amenability of dsRNA to control rust fungi. We sequenced genomes of six species of rust fungi, including three new families (Araucariomyceaceae, Phragmidiaceae, and Skierkaceae) and identified key genes of the RNAi pathway across 15 species in eight families of Pucciniales. Together, these findings indicate that dsRNA targeting essential genes has potential for broad-use management of rust fungi across natural and agricultural systems

Approximate Quantum Cloning with Nuclear Magnetic Resonance

Here we describe a Nuclear Magnetic Resonance (NMR) experiment that uses a three qubit NMR device to implement the one to two approximate quantum cloning network of Buzek et al.Comment: 4 pages RevTeX4 including 5 postscript figures. Submitted to PR

The decision to move : response times, neuronal circuits and sensory memory in a simple vertebrate

All animals use sensory systems to monitor external events and have to decide whether to move. Response times are long and variable compared to reflexes, and fast escape movements. The complexity of adult vertebrate brains makes it difficult to trace the neuronal circuits underlying basic decisions to move. To simplify the problem, we investigate the nervous system and responses of hatchling frog tadpoles which swim when their skin is stimulated. Studying the neuron-by-neuron pathway from sensory to hindbrain neurons, where the decision to swim is made, has revealed two simple pathways generating excitation which sums to threshold in these neurons to initiate swimming. The direct pathway leads to short, and reliable delays like an escape response. The other includes a population of sensory processing neurons which extend firing to introduce noise and delay into responses. These neurons provide a brief, sensory memory of the stimulus, that allows tadpoles to integrate stimuli occurring within a second or so of each other. We relate these findings to other studies and conclude that sensory memory makes a fundamental contribution to simple decisions and is present in the brainstem of a basic vertebrate at a surprisingly early stage in development.PostprintPeer reviewe

A simple decision to move in response to touch reveals basic sensory memory and mechanisms for variable response times

Many motor responses to sensory input, like locomotion or eye movements, are much slower than reflexes. Can simpler animals provide fundamental answers about the cellular mechanisms for motor decisions? Can we observe the ‘accumulation’ of excitation to threshold proposed to underlie decision making elsewhere? We explore how somatosensory touch stimulation leads to the decision to swim in hatchling Xenopus tadpoles. Delays measured to swimming in behaving and immobilized tadpoles are long and variable. Activity in their extensively studied sensory and sensory pathway neurons is too short-lived to explain these response delays. Instead, whole-cell recordings from the hindbrain reticulospinal neurons that drive swimming show these receive prolonged, variable synaptic excitation lasting for nearly a second following a brief stimulus. They fire and initiate swimming when this excitation reaches threshold. Analysis of the summation of excitation requires us to propose extended firing in currently undefined presynaptic hindbrain neurons. Simple models show that a small excitatory recurrent-network inserted in the sensory pathway can mimic this process. We suggest that such a network may generate slow, variable summation of excitation to threshold. This excitation provides a simple memory of the sensory stimulus. It allows temporal and spatial integration of sensory inputs and explains the long, variable delays to swimming. The process resembles the ‘accumulation’ of excitation proposed for cortical circuits in mammals. We conclude that fundamental elements of sensory memory and decision making are present in the brainstem at a surprisingly early stage in development