Stomatogastric Ganglion Module

STGfigureUnderstanding how neuronal networks enable animals, including humans, to make coordinated movements is a continuing goal of neuroscience research. The stomatogastric nervous system of decapod crustaceans and particularly the networks of the stomatogastric ganglion (STG), which control feeding functions, have significantly contributed to our present understanding of general principles underlying rhythmic motor circuit operation at the cellular level, and has shed light on the mechanisms of network homeostasis and plasticity.

Rhythmic behaviors include all motor acts that, at their core, involve a rhythmic repeating set of movements (e.g., locomotion, breathing, chewing and scratching). The circuits underlying such rhythmic behaviors, central pattern generators (CPGs), operate on the same general principles across all nervous systems. These networks can generate rhythmic output in the completely isolated nervous system, even in the absence of any rhythmic neuronal input, including feedback from sensory systems. Although the details differ in each circuit, all CPGs use the same set of cellular-level mechanisms for circuit construction. More importantly, CPG circuits are usually not dedicated to producing a single neuronal activity pattern. This flexibility results largely from the ability of many different neuromodulators to change the cellular and synaptic properties of individual circuit neurons. When the properties of circuit components are changed, the output of the circuit itself is modified.

The STG contains a set of distinct but interacting motor circuits. The value of this system has resulted from its experimental accessibility, owing to the small number of large and individually identifiable neurons and the use of several innovative techniques. Because of the many similarities between vertebrate and invertebrate systems, especially with regards to basic principles of neuronal function, invertebrate model systems such as the crustacean stomatogastric nervous system continue to provide key insight into how neural circuits operate in the numerically larger and less accessible vertebrate CNS.

The stomatogastric cycle (STG cycle) examines mechanisms of generation, regulation and plasticity of rhythmic neural activity produced by CPG networks. The STG cycle exercises highlight fundamental features of the cellular basis of motor pattern generation and the characterization of dynamical neural systems. Students obtain hands-on experience with the principle that rhythmically active networks can continue to generate rhythmic motor patterns in the isolated CNS, a defining feature of CPGs. We also focus on the fact that anatomically hard-wired circuits remain functionally flexible. All neural networks are malleable through the action of neuromodulatory inputs and intrinsic homeostatic mechanisms, which modify time and voltage-dependent properties of intrinsic membrane properties, and functional synaptic connectivity. Additionally, several key aspects of neuronal communication are studied, including properties of spike-mediated and graded synaptic transmission, short-term synaptic plasticity and the input/output properties of electrical synapses.

We build on skills developed during Cycle I, emphasizing electrophysiological analysis of neural network activity, and its underlying ionic mechanisms, in an isolated nervous system. We emphasize modern experimental tools and paradigms: intracellular recordings of multiple identified neurons; extracellular recordings of identified neurons; single-electrode discontinuous current clamp methods for current injection and recording; synaptic pharmacology defined with pharmacological agonists and antagonists; superfusion of neuromodulators and their release by identified projection neurons; study of graded transmitter release, the dynamic clamp technique for determining the functional impact of intrinsic and synaptic currents in network function, and quantitative analysis of electrophysiological recordings.

Students spend the first week building their understanding of STG networks. For example, students will learn dynamical system techniques to describe activity network parameters, such as phase analysis, resetting, entrainment and phase response curves (PRCs). The two-electrode voltage clamp technique is introduced to quantify time and voltage dependent properties of membrane channels and to clarify how ionic currents (which will be characterized mathematically using the Hodgkin-Huxley framework) contribute to neuronal and network function. These ionic currents will be manipulated using the dynamic clamp technique to understand the functional significance of mathematically defined ionic conductances. The dynamic clamp technique will also be used to examine the role of synapses in the network, by artificially adding or removing synapses in the biological network.

The second week of the STG Cycle is dedicated to independent projects that reflect contemporary research issues asking questions about mechanisms underlying neural network activity, and address specific principles of motor network function common to all animals. These projects are expected, with guidance from faculty mentors, to gather new, previously unpublished data, much as preliminary experiments would accomplish in a research lab. Almost all projects in the STG cycle address unknown conceptual questions and many projects in recent years have led to novel results.

 

STG Faculty and Teaching Assistants


blitzdDawn Blitz
Miami University

In my lab, we use the well-defined model system, the stomatogastric nervous system of the Jonah crab, Cancer borealis to determine cellular, synaptic and systems-level mechanisms used by the nervous system to select particular outputs from neural networks capable of generating many different output patterns. We use electrophysiological approaches such as current clamp, voltage clamp and dynamic clamp recording techniques along with immunocytochemistry, single cell dye-fills, photoablation, and confocal microscopy. We are particularly interested in how the activity of projection neurons, inputs to neural circuits, is controlled. This includes determining the roles of circuit feedback and extrinsic inputs (relaying information about the internal and external environment) in regulating the activity of projection neurons and the consequences for the rest of the motor pathway. Dawn was a NS&B student in 1995, TA from 1996-2001, and a faculty member from 2006-2008 and since 2012.

 

People_NellyNelly Daur
NJIT/Rutgers University

I want to understand how the nervous system encodes information at the single neuron and synapse level. Axons are still often viewed as faithful transmission lines of temporal activity patterns. The Bucher Lab’s recent work however has shown the large degree to which the temporal activity patterns can be altered during axonal signal propagation, as a function of both the history of activity and the presence of neuromodulatory substances. I am interested in the role potassium currents play for axonal fidelity and the consequences that neuromodulator- and activity-dependent changes in the temporal fidelity of axonal propagation of electrical signals have on muscle responses. Nelly has served as a TA for the STG team in 2012, 2013, and 2016.

 

anna_nsb-photoAnna Schneider
NJIT/Rutgers University

I want to understand how neuropeptides and their interactions provide stability and flexibility to neural networks. In the Nadim / Bucher Lab, we use the stomatogastric nervous system to tackle these questions. Its identified pyloric network produces a stereotypic triphasic pattern with low variability across animals. However, the underlying ion channel currents and mRNA levels vary largely. One key component to reduce variability from the component to the network level could be the convergence of neuropeptides on the same target. To test this hypothesis, I compare variation of several rhythm and component parameters in the presence or absence of neuropeptides. With these results, we want to discover general rules of neuropeptide interaction.

 

picture1Carmen Wellmann
University of Cologne

I am interested in understanding how distributed neural oscillators are coordinated. We can gain important information about functioning of neuronal networks while using simple systems. Such systems that coordinate rhythmic activity and locomotion are well suited to discover the insights of phase constancy and synchronization between coupled oscillators. For locomotion to be effective, these limbs have to be always activated at the same phase in the rhythm, independent of its frequency.

In my lab we use the swimmeret system of crayfish. Swimmerets are the limbs on the abdomen of crustaceans and are used for forward swimming. Each individual swimmeret is driven by its own neuronal oscillator located in the segmental abdominal ganglia. During movement they are very well coordinated, namely in a metachronal wave from posterior to anterior. We investigate the synaptic connections between identified neurons in the system with electrophysiological and morphological methods. Carmen joined the STG team in 2017.

 

picture2Elizabeth Cronin
NJIT/Rutgers University

I want to understand how neuromodulators, specifically neuropeptides, shape network outputs.  Using the stomatogastric nervous system in the American lobster, Homarus americanus, we have access to the four neuron types that make up the core pyloric network.  When a modulator is applied, a distinct rhythm is generated but, as of now, we don’t have a quantitative understanding of how this is happening.  Our approach to solve this problem in the Bucher lab is to measure the modulatory inward current, IMI, at the single neuron and synaptic level for each of the core pyloric neurons.  By mapping the response of these neurons to different modulators, we will have a data set that will allow us to build back the network from its components.  In doing so we will be able to make predictions as to how the network would respond given a set of parameters including type and concentration of that modulator. Elizabeth joined the STG team in 2017.