Oscillations and oscillatory behavior in small neural circuits

In order to determine the dynamical properties of central pattern generators (CPGs), we have examined the lobster stomatogastric ganglion using the tools of nonlinear dynamics. The lobster pyloric and gastric mill central pattern generators can be analyzed at both the cellular and network levels because they are small, i.e., contain only 25 neurons between them and each neuron and synapse are repeatedly identifiable from animal to animal. We discuss how the biophysical properties of each neuron and synapse in the two circuits act cooperatively to generate two different patterns of sequential activity, how these patterns are altered by neuromodulators and perturbed by noise and sensory inputs. Finally, we show how simplified Hindmarsh–Rose models can be made into analog electronic neurons that mimic the lobster neurons and in addition be incorporated into artificial CPGs with robotic applications.     

Modulation of stomatogastric rhythms

Neuromodulation by peptides and amines is a primary source of plasticity in the nervous system as it adapts the animal to an ever-changing environment. The crustacean stomatogastric nervous system is one of the premier systems to study neuromodulation and its effects on motor pattern generation at the cellular level. It contains the extensively modulated central pattern generators that drive the gastric mill (chewing) and pyloric (food filtering) rhythms. Neuromodulators affect all stages of neuronal processing in this system, from membrane currents and synaptic transmission in network neurons to the properties of the effector muscles. The ease with which distinct neurons are identified and their activity is recorded in this system has provided considerable insight into the mechanisms by which neuromodulators affect their target cells and modulatory neuron function. Recent evidence suggests that neuromodulators are involved in homeostatic processes and that the modulatory system itself is under modulatory control, a fascinating topic whose surface has been barely scratched. Future challenges include exploring the behavioral conditions under which these systems are activated and how their effects are regulated.     

The anatomy and physiology of the stomatogastric nervous system ofSquilla

Summary The stomatogastric nervous system of a mantis shrimp,Squilla oratoria, is described. The motor nerves of the stomatogastric ganglion (STG) and their innervation of muscles of the posterior cardiac plate (pcp) and pyloric systems are detailed.The STG contains more than 25 neurons. It sends out one pair of major output nerves. The pcp-pyloric cycle recorded from the motor axons in this nerve consists of rhythmic bursts of several units which fire with a characteristic phase relationship to each other. The rhythm is intrinsic to the STG itself, but it is modifiable.Recordings from the peripheral nerves reveal that identifiable cardiac plate, pyloric dilator and pyloric neurons control sequential contractions of the pcp and pyloric muscles to constrict or dilate a number of their attached ossicles.Several modulatory input fibres in the stomatogastric nerve, activated via stimulation of the superior or inferior oesophageal nerve (son, ion), prime or trigger the cyclic motor outputs. The son inputs induce distinct effects on the cardiac and pcp-pyloric pattern generators, while the ion inputs, via the oesophageal ganglion, excite only the pcp-pyloric generator.On the basis of anatomical and physiological observations, the possible functions of motor neurons involved in the pcp-pyloric cycle are described with reference to opening of the pcp and pyloric channels.This stomatogastric nervous system inSquilla is compared to that in decapods which has been well analyzed.Abbreviations CG commissural ganglion - ion inferior oesophageal nerve - lvn lateral ventricular nerve - OG oesophageal ganglion - pep posterior cardiac plate - son superior oesophageal nerve - STG stomatogastric ganglion - stn stomatogastric nerve - ivn inferior ventricular nerve     

All-or-none control of the bursting properties of the pacemaker neurons of the labster pyloric pattern generator

In Crustacea the central pattern generator for the pyloric motor rhythm (filtration to the midgut) is known to be located within the stomatogastric ganglion (STG); its cycling activity is known to be organized by three endogenous burster neurons acting as pacemakers and driving 11 follower neurons. In Homarus, recordings from the isolated stomatogastric nervous system (Fig. 1) indicate that (1) the pyloric output can be generated only when the STG is afferented (i.e., connected to the more rostral oesophageal and commissural ganglia) (Fig. 2) and (2) the deafferntation of the STG results in a complete loss of the bursting properties of the pacemaker neurons (Fig. 4). Manipulation of the STG inputs responsible for unmasking the properties of the pacemakers strongly suggests that (1) they are not phasic inputs (Fig. 5) and (2) they are long-term acting inputs (Fig. 6). These results provide evidence for a neural all-or-none control of the bursting properties of the pacemaker neurons of a motor pattern generator.     

Neural circuit flexibility in a small sensorimotor system

Neuronal circuits underlying rhythmic behaviors (central pattern generators: CPGs) can generate rhythmic motor output without sensory input. However, sensory input is pivotal for generating behaviorally relevant CPG output. Here we discuss recent work in the decapod crustacean stomatogastric nervous system (STNS) identifying cellular and synaptic mechanisms whereby sensory inputs select particular motor outputs from CPG circuits. This includes several examples in which sensory neurons regulate the impact of descending projection neurons on CPG circuits. This level of analysis is possible in the STNS due to the relatively unique access to identified circuit, projection, and sensory neurons. These studies are also revealing additional degrees of freedom in sensorimotor integration that underlie the extensive flexibility intrinsic to rhythmic motor systems.     

Responses of a bursting pacemaker to excitation reveal spatial segregation between bursting and spiking mechanisms

Central pattern generators (CPGs) frequently include bursting neurons that serve as pacemakers for rhythm generation. Phase resetting curves (PRCs) can provide insight into mechanisms underlying phase locking in such circuits. PRCs were constructed for a pacemaker bursting complex in the pyloric circuit in the stomatogastric ganglion of the lobster and crab. This complex is comprised of the Anterior Burster (AB) neuron and two Pyloric Dilator (PD) neurons that are all electrically coupled. Artificial excitatory synaptic conductance pulses of different strengths and durations were injected into one of the AB or PD somata using the Dynamic Clamp. Previously, we characterized the inhibitory PRCs by assuming a single slow process that enabled synaptic inputs to trigger switches between an up state in which spiking occurs and a down state in which it does not. Excitation produced five different PRC shapes, which could not be explained with such a simple model. A separate dendritic compartment was required to separate the mechanism that generates the up and down phases of the bursting envelope (1) from synaptic inputs applied at the soma, (2) from axonal spike generation and (3) from a slow process with a slower time scale than burst generation. This study reveals that due to the nonlinear properties and compartmentalization of ionic channels, the response to excitation is more complex than inhibition.     

Cellular properties and modulation of the stomatogastric ganglion neurons of a stomatopod,Squilla oratoria

Cellular properties and modulation of the identified neurons of the posterior cardiac plate-pyloric system in the stomatogastric ganglion of a stomatopod, Squilla oratoria, were studied electrophysiologically. Each class of neurons involved in the cyclic bursting activity was able to trigger an endogenous, slow depolarizing potential (termed a driver potential) which sustained bursting. Endogenous oscillatory properties were demonstrated by the phase reset behavior in response to brief stimuli during ongoing rhythm. The driver potential was produced by membrane voltage-dependent activation and terminated by an active repolarization. Striking enhancement of bursting properties of all the cell types was induced by synaptic activation via extrinsic nerves, seen as increases in amplitude or duration of driver potentials, spiking rate during a burst, and bursting rate. The motor pattern produced under the influence of extrinsic modulatory inputs continued for a long time, relative to that in the absence of activation of modulatory inputs. Voltage-dependent conductance mechanisms underlying postinhibitory rebound and driver potential responses were modified by inputs. It is concluded that endogenous cellular properties, as well as synaptic circuitry and extrinsic inputs, contribute to generation of the rhythmic motor pattern, and that a motor system and its component neurons have been highly conserved during evolution between stomatopods and decapods.Abbreviations AB anterior burster neuron - CoG commissural ganglion - CPG central pattern generator - lvn lateral ventricular nerve - OG oesophageal ganglion - pcp posterior cardiac plate - PCP pcp constrictor neuron - PD pyloric dilator neuron - PY pyloric constrictor neuron - son superior oesophageal nerve - STG stomatogastric ganglion - stn stomatogastric nerve     

Pattern generation in the lobster (Panulirus) stomatogastric ganglion

1. Results from the companion paper were incorporated into a physiologically realistic computer model of the three principal cell types (PD/AB, LP, PY) of the pyloric network in the stomatogastric ganglion. Parameters for the model were mostly calculated (sometimes estimated) from experimental data rather than fitting the model to observed output patterns. 2. The initial run was successful in predicting several features of the pyloric pattern: the observed gap between PD and LP bursts, the appropriate sequence of the activity periods (PD, LP, PY), and a substantial PY burst not properly simulated by an earlier model. 3. The major discrepancy between model and observed patterns was the too-early occurrence of the PY burst, which resulted in a much shortened LP burst. Motivated by this discrepancy, additional investigations were made of PY properties. A hyperpolarization-enabled depolorization-activated hyperpolarizing conductance change was discovered which may make an important contribution to the late phase of PY activity in the normal burst cycle. Addition of this effect to the model brought its predictions more in line with observed patterns. 4. Other discrepancies between model and observation were instructive and are discussed. The findings force a substantial revision in previously held ideas on pattern production in the pyloric system. More weight must be given to functional properties of individual neurons and less to properties arising purely from network interactions. This shift in emphasis may be necessary in more complicated systems as well. 5. An example has been provided of the value quantitative modeling can be to network physiology. Only through rigorous quantitative testing can qualitative theories of how the nervous system operates be substantiated.     

The stomatogastric nervous system of the house cricket Acheta domesticus L. II. Iontophoretic study of neuron anatomy

The anatomy of neurons of the stomatogastric nervous system of Ascheta domesticus was studied using heavy metal iontophoresis through cut nerve ends followed by silver intensification. Nineteen categories of neuron are described and compared with neurons known from the stomatogastric nervous system of other insects. Possible functions for the neurons are suggested. Motor neuron candidates are suggested for all parts of the gut served by the stomatogastric nervous system, and axons of sensory neurons of the anterior pharynx are located. There are four neuron types that cannot readily be assigned motor, sensory, or interneuron functions: large dorsal cells of the frontal ganglion; the two neurons of the nervus connectivus, and two categories of neurons in the median neurosecretory cell group of the pars intercerebralis, the axons of which are contained in the stomatogastric nerves.     

Increasing sensor flexibility through neuromodulation

Both biological and man-made motor control networks require input from sensors to allow for modification of the motor program. Real sensory neurons are more flexible than typical robotic sensors because they are dynamic rather than static. The membrane properties of neurons and hence their excitability can be modified by the presence of neuromodulatory substances. In the case of a sensory neuron, this can change, in a functionally significant way, the code used to describe a stimulus. For instance, extension of the neuron's dynamic range or modification of its filtering characteristics can result. This flexibility has an apparent cost. The code used may be situation-dependent and hence difficult to interpret. To address this issue and to understand how neuromodulation is used effectively in a motor control network, I am studying the GPR2 stretch receptor in the crustacean stomatogastric nervous system. Several different neuromodulatory substances can modify its encoding properties. Comparisons of physiological and anatomical evidence suggest that neuromodulation can be effected both by GPR2 itself and by other neurons in the network. These results suggest that the analog of neuromodulation might be useful for improving sensor performance in an artificial motor control system.     

Motor pattern generation of the posterior cardiac plate-pyloric system in the stomatogastric ganglion of the mantis shrimp Squilla oratoria

Activity patterns of the constituent neurons of the posterior cardiac plate-pyloric system in the stomatogastric ganglion of the mantis shrimp Squilla oratoria were studied by recording spontaneous burst discharges intracellularly from neuronal somata. These neurons were identified electrophysiologically, and synaptic connections among them were qualitatively analysed. The posterior cardiac plate constrictor, pyloric constrictor, pyloric dilator and ventricular dilator motoneurons, and the pyloric interneuron were involved in the posterior cardiac plate-pyloric system. All the cell types could produce slow burst-forming potentials which led to repetitive spike discharges. These neurons generated sequentially patterned outputs. Most commonly, the posterior cardiac plate neuron activity was followed by the activity of pyloric constrictor neurons, and then by the activity of pyloric dilator/pyloric interneuron, and ventricular dilator neurons. The motoneurons and interneuron in the posterior cardiac plate-pyloric system were connected to each other either by electrical or by inhibitory chemical synapses, and thus constructed the neural circuit characterized by a wiring diagram which was structurally similar to the pyloric circuit of decapods. The circuitry in the stomatogastric ganglion was strongly conserved during evolution between stomatopods and decapods, despite significant changes in the peripheral structure of the foregut. There were more electrical synapses in stomatopods, and more reciprocal inhibitory synapses in decapods.Abbreviations EJP excitatory junctional potential - IPSP inhibitory postsynaptic potential - CoG commissural ganglion - CPG central pattern generator - ion inferior oesophageal nerve - OG oesophageal ganglion - pcp posterior cardiac plate - son superior oesophageal nerve - STG stomatogastric ganglion - stn stomatogastric nerve - PY pyloric constrictor - PD pyloric dilator - VD ventricular dilator - AB pyloric interneuron - lvn lateral ventricular nerves - tcpm transverse cardiac plate muscle     

Neuromorphic hardware databases for exploring structure-function relationships in the brain.

Neuromorphic hardware is the term used to describe full custom-designed integrated circuits, or silicon ''chips'', that are the product of neuromorphic engineering--a methodology for the synthesis of biologically inspired elements and systems, such as individual neurons, retinae, cochleas, oculomotor systems and central pattern generators. We focus on the implementation of neurons and networks of neurons, designed to illuminate structure-function relationships. Neuromorphic hardware can be constructed with either digital or analogue circuitry or with mixed-signal circuitry--a hybrid of the two. Currently, most examples of this type of hardware are constructed using analogue circuits, in complementary metal-oxide-semiconductor technology. The correspondence between these circuits and neurons, or networks of neurons, can exist at a number of levels. At the lowest level, this correspondence is between membrane ion channels and field-effect transistors. At higher levels, the correspondence is between whole conductances and firing behaviour, and filters and amplifiers, devices found in conventional integrated circuit design. Similarly, neuromorphic engineers can choose to design Hodgkin-Huxley model neurons, or reduced models, such as integrate-and-fire neurons. In addition to the choice of level, there is also choice within the design technique itself; for example, resistive and capacitive properties of the neuronal membrane can be constructed with extrinsic devices, or using the intrinsic properties of the materials from which the transistors themselves are composed. So, silicon neurons can be built, with dendritic, somatic and axonal structures, and endowed with ionic, synaptic and morphological properties. Examples of the structure-function relationships already explored using neuromorphic hardware include correlation detection and direction selectivity. Establishing a database for this hardware is valuable for two reasons: first, independently of neuroscientific motivations, the field of neuromorphic engineering would benefit greatly from a resource in which circuit designs could be stored in a form appropriate for reuse and re-fabrication. Analogue designers would benefit particularly from such a database, as there are no equivalents to the algorithmic design methods available to designers of digital circuits. Second, and more importantly for the purpose of this theme issue, is the possibility of a database of silicon neuron designs replicating specific neuronal types and morphologies. In the future, it may be possible to use an automated process to translate morphometric data directly into circuit design compatible formats. The question that needs to be addressed is: what could a neuromorphic hardware database contribute to the wider neuroscientific community that a conventional database could not? One answer is that neuromorphic hardware is expected to provide analogue sensory-motor systems for interfacing the computational power of symbolic, digital systems with the external, analogue environment. It is also expected to contribute to ongoing work in neural-silicon interfaces and prosthetics. Finally, there is a possibility that the use of evolving circuits, using reconfigurable hardware and genetic algorithms, will create an explosion in the number of designs available to the neuroscience community. All this creates the need for a database to be established, and it would be advantageous to set about this while the field is relatively young. This paper outlines a framework for the construction of a neuromorphic hardware database, for use in the biological exploration of structure-function relationships.     

A Neural Infrastructure for Rhythmic Motor Patterns

It is possible to work out the neural circuity of many invertebrate central pattern generators (CPGs) thereby providing a basis for linking cellular processes to actual behaviors. This review summarizes the infrastructure of the two CPGs in the lobster stomatogastric ganglion in terms of circuitry, ionic conductances and chemical modulation by amines and peptides. Analysis of the circuit using modeling techniques including the use of electronic neurons closes the chapter.     

Modulation of circuits underlying rhythmic behaviors

Summary What have we learned about behavior from neuromodulatory studies of the crustacean stomatogastric system? The emphasis of this paper has been on the analysis of one single class of behaviors (rhythmic) in terms of microcircuitry (synaptic connections between identified neurons). But in the general case, all behaviors result from the generation of spatio-temporal patterns by the central nervous system. How individual nerve cells interact with each other to produce such patterns is of fundamental interest. We know from work on simple networks that it is possible to link the circuitry of the nervous system with behavior in a precise way, and that instead of a large number of dedicated circuits, behaviors can be altered by chemically adjusting the functional properties of the neuronal elements. One circuit can be configured to perform a variety of different behaviors by activating neurons which contain neuromodulatory substances or in response to neurohormones circulating in the hemolymph. At present we know only a few of the ways neuromodulatory neurons are triggered to release their contents onto the neurons making up CPGs.The findings described here raise many questions. What are the parameters which control the distribution of neuromodulatory substances throughout the nervous system? What happens when more than one neuromodulator is present? At the cellular level, what mechanisms are involved in transforming each neuron from one functional state to another, and then how does the entire constellation of changes give rise to a new output? It is important to answer such questions in reduced networks, because there are presently no techniques available to answer them in the more complex networks of the brain. While there is no question that modulatory activity occurs in the brain, whether or not the principles which have been discovered by using simple invertebrate circuits scale up to vertebrate circuits remains an intriguing question.     

Pattern generation in the lobster (Panulirus) stomatogastric ganglion

There are a number of perspectives gained from a quantitative analysis of the pyloric system which may be applicable to other simple pattern generators: 1. The system is organized around a dominant, endogenously-bursting neuron group, and its properties are tailored to that dominance. In particular, synaptic strengths and firing frequencies of that group appear just sufficient to suppress postsynaptic "follower" cells if the latter are not too highly excited. 2. Repetitive firing properties of follower neurons are such as to facilitate their switch-like mode of activity. This includes pacemaker response nonlinearities, rebound properties, and "burstiness" properties. 3. Proper sequencing of follower cells may be controlled by particular synaptic strengths and time-courses, feedback on the oscillator cells, and functional cellular properties of follower neurons (e.g., rebound; see also next paper). All such properties interact and must be tuned to each other for proper patterns to result.     

Co-variation of ionic conductances supports phase maintenance in stomatogastric neurons

Neuronal networks produce reliable functional output throughout the lifespan of an animal despite ceaseless molecular turnover and a constantly changing environment. Central pattern generators, such as those of the crustacean stomatogastric ganglion (STG), are able to robustly maintain their functionality over a wide range of burst periods. Previous experimental work involving extracellular recordings of the pyloric pattern of the STG has demonstrated that as the burst period varies, the inter-neuronal delays are altered proportionally, resulting in burst phases that are roughly invariant. The question whether spike delays within bursts are also proportional to pyloric period has not been explored in detail. The mechanism by which the pyloric neurons accomplish phase maintenance is currently not obvious. Previous studies suggest that the co-regulation of certain ion channel properties may play a role in governing neuronal activity. Here, we observed in long-term recordings of the pyloric rhythm that spike delays can vary proportionally with burst period, so that spike phase is maintained. We then used a conductance-based model neuron to determine whether co-varying ionic membrane conductances results in neural output that emulates the experimentally observed phenomenon of spike phase maintenance. Next, we utilized a model neuron database to determine whether conductance correlations exist in model neuron populations with highly maintained spike phases. We found that co-varying certain conductances, including the sodium and transient calcium conductance pair, causes the model neuron to maintain a specific spike phase pattern. Results indicate a possible relationship between conductance co-regulation and phase maintenance in STG neurons.     

Multiple motor patterns in the stomatogastric ganglion of the shrimp Penaeus japonicus

 Motor patterns of the cardiac sac, the gastric and the pyloric network in the stomatogastric nervous system of the shrimp Penaeus japonicus, the most primitive decapod species, were studied. Single neurons can switch from the gastric or the pyloric pattern to the cardiac sac pattern. Some of the pyloric neurons fire with the gastric pattern. All of the gastric neurons fire with the pyloric pattern, unlike those in reptantians. Proctolin activates and modulates the cardiac sac and the pyloric rhythm, and promotes reconfiguration of the networks. Neurons of the three networks have so many interconnections that they construct a multifunctional neural network like those in Cancer. This network may function in different configurations under the appropriate conditions. Several modes of interactions between the networks found in different reptantian species can apply to the penaeidean shrimp. Such interactions are general features of the stomatogastric nervous system in decapods. Phylogenetic differences among the decapod infraorders are seen in the number and orientation of muscles and the innervation pattern of muscles. The multifunctional networks have existed in the most primitive decapod species, and types of configurations of the networks would have evolved to produce a wide range of motor patterns as the foregut structure has become complex. Accepted: 26 October 1999     

Comparison of Two Voltage-Sensitive Dyes and Their Suitability for Long-Term Imaging of Neuronal Activity

One of the key approaches for studying neural network function is the simultaneous measurement of the activity of many neurons. Voltage-sensitive dyes (VSDs) simultaneously report the membrane potential of multiple neurons, but often have pharmacological and phototoxic effects on neuronal cells. Yet, to study the homeostatic processes that regulate neural network function long-term recordings of neuronal activities are required. This study aims to test the suitability of the VSDs RH795 and Di-4-ANEPPS for optically recording pattern generating neurons in the stomatogastric nervous system of crustaceans with an emphasis on long-term recordings of the pyloric central pattern generator. We demonstrate that both dyes stain pyloric neurons and determined an optimal concentration and light intensity for optical imaging. Although both dyes provided sufficient signal-to-noise ratio for measuring membrane potentials, Di-4-ANEPPS displayed a higher signal quality indicating an advantage of this dye over RH795 when small neuronal signals need to be recorded. For Di-4-ANEPPS, higher dye concentrations resulted in faster and brighter staining. Signal quality, however, only depended on excitation light strength, but not on dye concentration. RH795 showed weak and slowly developing phototoxic effects on the pyloric motor pattern as well as slow bleaching of the staining and is thus the better choice for long-term experiments. Low concentrations and low excitation intensities can be used as, in contrast to Di-4-ANEPPS, the signal-to-noise ratio was independent of excitation light strength. In summary, RH795 and Di-4-ANEPPS are suitable for optical imaging in the stomatogastric nervous system of crustaceans. They allow simultaneous recording of the membrane potential of multiple neurons with high signal quality. While Di-4-ANEPPS is better suited for short-term experiments that require high signal quality, RH795 is a better candidate for long-term experiments since it has only minor effects on the motor pattern.     

Comparative study of the stomatogastric system of the decapod crustacea. II. Musculature

The stomach musculature of several species of decapod Crustacea is described in detail. All species are sufficiently similar so that muscle homologies can be established. The Natantia have a simplified muscle system while the Reptantia are characterized by a more complex muscle system. Species can be arranged in a graded series of muscle system complexity which closely follows the evolution of the decapod Crustacea. The information presented here should provide the basis for consistent identification of the stomatogastric motor neurons throughout the decapod Crustacea.     

Reliable circuits from irregular neurons: A dynamical approach to understanding central pattern generators

Central pattern generating neurons from the lobster stomatogastric ganglion were analyzed using new nonlinear methods. The LP neuron was found to have only four or five degrees of freedom in the isolated condition and displayed chaotic behavior. We show that this chaotic behavior could be regularized by periodic pulses of negative current injected into the neuron or by coupling it to another neuron via inhibitory connections. We used both a modified Hindmarsh-Rose model to simulate the neurons behavior phenomenologically and a more realistic conductance-based model so that the modeling could be linked to the experimental observations. Both models were able to capture the dynamics of the neuron behavior better than previous models. We used the Hindmarsh-Rose model as the basis for building electronic neurons which could then be integrated into the biological circuitry. Such neurons were able to rescue patterns which had been disabled by removing key biological neurons from the circuit.