Coordination of limb movements: three types of intersegmental interneurons in the swimmeret system and their responses to changes in excitation

Investigating the human spinal sensorimotor pathways through functional magnetic resonance imaging

Most of our knowledge about the human spinal ascending (sensory) and descending (motor) pathways comes from non-invasive electrophysiological investigations. However, recent methodological advances in acquisition and analyses of functional magnetic resonance imaging (fMRI) data from the spinal cord, either alone or in combination with the brain, have allowed us to gain further insights into the organization of this structure. In the current review, we conducted a systematic search to produced somatotopic maps of the spinal fMRI activity observed through different somatosensory, motor and resting-state paradigms. By cross-referencing these human neuroimaging findings with knowledge acquired through neurophysiological recordings, our review demonstrates that spinal fMRI is a powerful tool for exploring, in vivo, the human spinal cord pathways. We report strong cross-validation between task-related and resting-state fMRI in accordance with well-known hemicord, postero-anterior and rostro-caudal organization of these pathways. We also highlight the specific advantages of using spinal fMRI in clinical settings to characterize better spinal-related impairments, predict disease progression, and guide the implementation of therapeutic interventions.

Profiling neurotransmitters in a crustacean neural circuit for locomotion

Locomotor systems are widely used to study rhythmically active neural networks. These networks have to be coordinated in order to produce meaningful behavior. The crayfish swimmeret system is well suited to investigate such coordination of distributed neural oscillators because the neurons and their connectivity for generating and especially for coordinating the motor output are identified. The system maintains a fixed phase lag between the segmental oscillators, independent of cycle period. To further the understanding of the system’s plasticity for keeping the phase lag fixed, we profiled the neurotransmitters used by the Coordinating Neurons, which are necessary and sufficient for coordination of the segmental oscillators. We used a combination of electrophysiological, immunohistochemical, and mass spectrometric methods. This arrangement of methods ensured that we could screen for several specific neurotransmitters, since a single method is often not suitable for all neurotransmitters of interest. In a first step, to preselect neurotransmitter candidates, we investigated the effect of substances known to be present in some swimmeret system neurons on the motor output and coordination. Subsequently, we demonstrated electrophysiologically that the identified synapse between the Coordinating Neurons and their target is mainly chemical, but neither glutamate antagonist nor γ-aminobutyric acid antagonist application affected this synapse. With immunohistochemical experiments, we provide strong evidence that the Coordinating Neurons are not serotonergic. Single-cell MALDI-TOF mass spectrometry with subsequent principal component analysis identified acetylcholine as the putative neurotransmitter for both types of Coordinating Neurons.

Nitric oxide-mediated intersegmental modulation of cycle frequency in the crayfish swimmeret system

Crayfish swimmerets are paired appendages located on the ventral side of each abdominal segment that show rhythmic beating during forward swimming produced by central pattern generators in most abdominal segments. For animals with multiple body segments and limbs, intersegmental coordination of central pattern generators in each segment is crucial for the production of effective movements. Here we develop a novel pharmacological approach to analyse intersegmental modulation of swimmeret rhythm by selectively elevating nitric oxide levels and reducing them with pharmacological agents, in specific ganglia. Bath application of L-arginine, the substrate NO synthesis, increased the cyclical spike responses of the power-stroke motor neurons. By contrast the NOS inhibitor, L-NAME decreased them. To determine the role of the different local centres in producing and controlling the swimmeret rhythm, these two drugs were applied locally to two separate ganglia following bath application of carbachol. Results revealed that there was both ascending and descending intersegmental modulation of cycle frequency of the swimmeret rhythm in the abdominal ganglia and that synchrony of cyclical activity between segments of segments was maintained. We also found that there were gradients in the strength effectiveness in modulation, that ascending modulation of the swimmeret rhythm was stronger than descending modulation.

Summary: We develop a novel pharmacological approach using a nitric oxide donor and a nitric oxide synthase inhibitor to analyse modulation and segmental synchrony in the swimmeret rhythm of the crayfish.

Flexibility of the axial central pattern generator network for locomotion in the salamander

In tetrapods, limb and axial movements are coordinated during locomotion. It is well established that inter- and intralimb coordination show considerable variations during ongoing locomotion. Much less is known about the flexibility of the axial musculoskeletal system during locomotion and the neural mechanisms involved. Here we examined this issue in the salamander Pleurodeles waltlii, which is capable of locomotion in both aquatic and terrestrial environments. Kinematics of the trunk and electromyograms from the mid-trunk epaxial myotomes were recorded during four locomotor behaviors in freely moving animals. A similar approach was used during rhythmic struggling movements since this would give some insight into the flexibility of the axial motor system. Our results show that each of the forms of locomotion and the struggling behavior is characterized by a distinct combination of mid-trunk motor patterns and cycle durations. Using in vitro electrophysiological recordings in isolated spinal cords, we observed that the spinal networks activated with bath-applied N-methyl-d-aspartate could generate these axial motor patterns. In these isolated spinal cord preparations, the limb motor nerve activities were coordinated with each mid-trunk motor pattern. Furthermore, isolated mid-trunk spinal cords and hemicords could generate the mid-trunk motor patterns. This indicates that each side of the cord comprises a network able to generate coordinated axial motor activity. The roles of descending and sensory inputs in the behavior-related changes in axial motor coordination are discussed.

Mechanisms of coordination in distributed neural circuits: encoding coordinating information

We describe synaptic connections through which information essential for encoding efference copies reaches two coordinating neurons in each of the microcircuits that controls limbs on abdominal segments of the crayfish, Pacifastacus leniusculus. In each microcircuit, these coordinating neurons fire bursts of spikes simultaneously with motor neurons. These bursts encode timing, duration, and strength of each motor burst. Using paired microelectrode recordings, we demonstrate that one class of nonspiking neurons in each microcircuit's pattern-generating kernel--IPS--directly inhibits the ASCE coordinating neuron that copies each burst in power-stroke (PS) motor neurons. This inhibitory synapse parallels IPS's inhibition of the same PS motor neurons. Using a disynaptic pathway to control its membrane potential, we demonstrate that a second type of nonspiking interneuron in the pattern-generating kernel--IRSh--inhibits the DSC coordinating neuron that copies each burst in return-stroke (RS) motor neurons. This inhibitory synapse parallels IRS's inhibition of the microcircuit's RS motor neurons. Experimental changes in the membrane potential of one IPS or one IRSh neuron simultaneously changed the strengths of motor bursts, durations, numbers of spikes, and spike frequency in the simultaneous ASCE and DSC bursts. ASCE and DSC coordinating neurons link the segmentally distributed microcircuits into a coordinated system that oscillates with the same period and with stable phase differences. The inhibitory synapses from different pattern-generating neurons that parallel their inhibition of different sets of motor neurons enable ASCE and DSC to encode details of each oscillation that are necessary for stable, adaptive synchronization of the system.

Mechanisms of coordination in distributed neural circuits: decoding and integration of coordinating information

We describe the synaptic connections through which information required to coordinate limb movements reaches the modular microcircuits that control individual limbs on different abdominal segments of the crayfish, Pacifastacus leniusculus. In each segmental ganglion, a local commissural interneuron, ComInt 1, integrates information about other limbs and transmits it to one microcircuit. Five types of nonspiking local interneurons are components of each microcircuit's pattern-generating kernel (Smarandache-Wellmann et al., 2013). We demonstrate here, using paired microelectrode recordings, that the pathway through which information reaches this kernel is an electrical synapse between ComInt 1 and one of these five types, an IRSh interneuron. Using single-electrode voltage clamp, we show that brief changes of ComInt 1's membrane potential affect the timing of its microcircuit's motor output. Changing ComInt 1's membrane potential also changes the phase, duration, and strengths of bursts of spikes in its microcircuit's motor neurons and corresponding changes in its efferent coordinating neurons that project to other ganglia. These effects on coordinating neurons cause changes in the phases of motor output from other microcircuits in those distant ganglia. ComInt 1s function as hub neurons in the intersegmental circuit that synchronizes distributed microcircuits. The synapse between each ComInt 1 and its microcircuit's IRSh neuron completes a five synapse pathway in which analog information is encoded as a digital signal by efference-copy neurons and decoded from digital to analog form by ComInt 1. The synaptic organization of this pathway provides a cellular explanation of this nervous system's key dynamic properties.

Neurobiology of the crustacean swimmeret system

The crustacean swimmeret system includes a distributed set of local circuits that individually control movements of one jointed limb. These modular local circuits occur in pairs in each segmental ganglion, and normally operate synchronously to produce smoothly coordinated cycles of limb movements on different body segments. The system presents exceptional opportunities for computational and experimental investigation of neural mechanisms of coordination because: (a) The system will express in vitro the periodic motor pattern that normally drives cycles of swimmeret movements during forward swimming. (b) The intersegmental neurons which encode information that is necessary and sufficient for normal coordination have been identified, and their activity can be recorded. (c) The local commissural neurons that integrate this coordinating information and tune the phase of each swimmeret are known. (d) The complete set of synaptic connections between coordinating neurons and these commissural neurons have been described. (e). The synaptic connections onto each local pattern-generating circuit through which coordinating information tunes the circuit's phase have been discovered. These factors make possible for the first time a detailed, comprehensive cellular and synaptic explanation of how this neural circuit produces an effective, behaviorally significant output. This paper is the first comprehensive review of the system's neuroanatomy and neurophysiology, its local and intersegmental circuitry, its transmitter pharmacology, its neuromodulatory control mechanisms, and its interactions with other motor systems. Each of these topics is covered in detail in an attempt to provide a complete review of the literature as a foundation for new research. The series of hypotheses that have been proposed to account for the system's properties are reviewed critically in the context of experimental tests of their validity.

Fifty Years of CPGs: Two Neuroethological Papers that Shaped the Course of Neuroscience

Half a century ago, two independent papers that described unexpected results of experiments on locomotion in insects and crayfish appeared almost simultaneously. Together these papers demonstrated that an animal's central nervous system (CNS) was organized to produce behaviorally important motor output without the need for constant sensory feedback. These results contradicted the established line of thought that was based on interpretations of reflexes and ablation experiments, and established that in these animals the CNS contained neural circuits that could produce complex, periodic, multisegmental patterns of activity. These papers stimulated a flowering of research on central pattern-generating mechanisms that displaced reflex-based thinking everywhere except in medical physiology texts. Here we review these papers and their influence on thinking in the 1960s, 1970s, and today. We follow the development of ideas about central organization and control of expression of motor patterns, the roles of sensory input to central pattern-generating circuits, and integration of continuous sensory signals into a periodic motor system. We also review recent work on limb coordination that provides detailed cellular explanations of observations and speculations contained in those original papers.

Coordination of rhythmic motor activity by gradients of synaptic strength in a neural circuit that couples modular neural oscillators

Synchronization of distributed neural circuits is required for many behavioral tasks, but the mechanisms that coordinate these circuits are largely unknown. The modular local circuits that control crayfish swimmerets are distributed in four segments of the CNS, but when the swimmeret system is active their outputs are synchronized with a stable intersegmental phase difference of 0.25, an example of metachronal synchronization (Izhikevich, 2007). In each module, coordinating neurons encode detailed information about each cycle of the module's motor output as bursts of spikes, and their axons conduct this information to targets in other segments. This information is both necessary and sufficient for normal intersegmental coordination. In a comprehensive set of recordings, we mapped the synaptic connections of two types of coordinating neurons onto their common target neurons in other segments. Both types of coordinating axons caused large, brief EPSPs in their targets. The shape indices of these EPSPs are tuned to transmit the information from each axon precisely. In each target neuron's own module, these bursts of EPSPs modified the phase of the module's motor output. Each axon made its strongest synapse onto the target neuron in the nearest neighboring segment. Its synapses onto homologous targets in more remote segments were progressively weaker. Each target neuron decodes information from several coordinating axons, and the strengths of their synapses differ systematically. These differences in synaptic strength weight information from each segment differently, which might account for features of the system's characteristic metachronal synchronization.

Local and Intersegmental Interactions of Coordinating Neurons and Local Circuits in the Swimmeret System

During forward swimming, periodic movements of swimmerets on different segments of the crayfish abdomen progress from back to front with the same period. Information encoded as bursts of spikes by coordinating neurons in each segmental ganglion is necessary for this coherent organization. This information is conducted to targets in other ganglia. When an individual coordinating neuron is stimulated at different phases in the system's cycle of activity, the timing of motor output from other ganglia may be altered. In models of this coordinating circuit, we assumed that each coordinating neuron encodes information about the state of the local pattern-generating circuit in its home ganglion but is not part of that local circuit. We tested this assumption by stimulating individual coordinating neurons of two kinds—ASCE and DSC—at different phases under two conditions: with the target ganglion functional, and with the target ganglion silenced. Blocking a DSC neuron's target ganglion did not alter its negligible influence on the output from its home ganglion; the phase-response curves (PRC) remained flat. Blocking an ASCE neuron's target ganglion significantly affected its influence on the output from its home ganglion. We had predicted that ASCE's modest phase-dependent influence would disappear with the target silenced, but instead the amplitude of the PRCs increased significantly. Thus we have two different results: DSC neurons conformed to prediction based on the models’ assumptions, but ASCE neurons showed an unexpected property, one that is partially masked when the bidirectional flow of information between neighboring ganglia is operating normally.

Biomimetic approaches to the control of underwater walking machines

We have developed a biomimetic robot based on the American lobster. The robot is designed to achieve the performance advantages of the animal model by adopting biomechanical features and neurobiological control principles. Three types of controllers are described. The first is a state machine based on the connectivity and dynamics of the lobster central pattern generator (CPG). The state machine controls myomorphic actuators based on shape memory alloys (SMAs) and responds to environmental perturbation through sensors that employ a labelled-line code. The controller supports a library of action patterns and exteroceptive reflexes to mediate tactile navigation, obstacle negotiation and adaptation to surge. We are extending this controller to neuronal network-based models. A second type of leg CPG is based on synaptic networks of electronic neurons and has been adapted to control the SMA actuated leg. A brain is being developed using layered reflexes based on discrete time map-based neurons.

Not by spikes alone: responses of coordinating neurons and the swimmeret system to local differences in excitation

Swimmeret coordinating neurons in the crayfish CNS collectively encode a detailed cycle-by-cycle report on features of the motor output to each swimmeret. This information coordinates the motor output that drives swimmeret movements. To see how coordinating neurons responded to forced changes in intersegmental phase, we used a split-bath, repeated-measures experimental design to expose different regions of isolated abdominal nerve cords to different levels of excitation. We present a quantitative description of the firing of power-stroke (PS) motor units and two kinds of coordinating interneurons, ASC(E) and DSC, recorded simultaneously from each swimmeret ganglion under uniform and nonuniform excitation. When anterior and posterior ganglia were excited differently, several parameters of the swimmeret motor pattern were affected. Strengths of PS bursts in each ganglion were determined by local excitation. The phase of PS bursts in neighboring ganglia changed at the excitation boundary. Coordinating neurons from the two ganglia closest to the excitation boundary were most affected by nonuniform excitation. ASC(E) neurons tracked the timing and duration of each PS burst in their home ganglion, but did not follow changes in PS burst strength. DSC neurons changed the duration, phase, and number of spikes per burst. We propose two models to explain these results. First, the period expressed under nonuniform conditions is the sum of local intersegmental latencies and these latencies are determined by local excitation. Second, the phase change at the excitation boundary is determined by local modulation of the targets of the intersegmental coordinating neurons, not by modulation of the coordinating neurons themselves.

Invertebrate central pattern generation moves along

Central pattern generators (CPGs) are circuits that generate organized and repetitive motor patterns, such as those underlying feeding, locomotion and respiration. We summarize recent work on invertebrate CPGs which has provided new insights into how rhythmic motor patterns are produced and how they are controlled by higher-order command and modulatory interneurons.

Bursts of Information: Coordinating Interneurons Encode Multiple Parameters of a Periodic Motor Pattern

The limbs on different segments of the crayfish abdomen that drive forward swimming are directly controlled by modular pattern-generating circuits. These circuits are linked together by axons of identified coordinating interneurons. We described the distributions of these neurons in each abdominal ganglion and monitored their firing during expression of the swimming motor pattern. We analyzed the timing, the numbers of spikes, and the duration of each burst of spikes in these coordinating neurons. To see what information these neurons encoded, we correlated these parameters with the timing, durations, and strengths of bursts of spikes in motor axons from the same modules. During the power-stroke phase of each output cycle, the anterior-projecting neurons fired bursts of spikes that encoded information about the start-time, duration, and strength of each burst of spikes in power-stroke motor neurons from the same module. When the period and intensity of the motor output fluctuated, the bursts of spikes in these neurons tracked these fluctuations accurately. Each additional spike in these neurons signified an increase in the strength of the power-stroke burst. The posterior-projecting neurons that fired during the return-stroke phase encoded similar information about the return-stroke motor neurons. Although homologous neurons from different ganglia were qualitatively similar, neurons from posterior ganglia fired significantly more spikes per burst than those from more anterior ganglia, a segmental gradient that correlates with the normal posterior-to-anterior phase progression of limb movements. We propose that this gradient and a similar gradient in the durations of bursts in power-stroke motor neurons might reflect a hitherto-undetected difference in the excitation or intrinsic excitability of swimmeret modules in different segments.

A method to measure the strength of multi-unit bursts of action potentials

Both the numbers of neurons that are active during multi-unit bursts of spikes and the frequencies with which individual neurons fire in these bursts can vary in response to changes in excitation. Here is a digital-filtering method that measures the strength of a burst of spikes by calculating the area of a polygon derived from the squared voltages that record the burst, and dividing this area by the burst's duration. The method was developed in the SigmaPlot environment, and makes use of the Fast-Fourier Transform functions provided in the SigmaPlot transform language. To test the method's performance, I constructed multi-unit bursts of spikes with known structure and calculated the strengths of these known bursts. To demonstrate the method's usefulness, I applied it to a train of 23 bursts of spikes in motor axons recorded during a spontaneous bout of patterned motor output. The measured strengths of these bursts varied 30-fold, and were well-correlated with the differences in the original recording. The results demonstrate that the method effectively measures burst strength independent of burst duration.

Local commissural interneurons integrate information from intersegmental coordinating interneurons

The information that coordinates movements of swimmerets on different segments of the crayfish abdomen is conducted by interneurons that originate in each abdominal ganglion. These interneurons project axons to neighboring ganglia and beyond. To discover the anatomy of these axons in their target ganglia, we used Neurobiotin and dextran-Texas Red microelectrodes to fill them near their targets. Coordinating axons coursed through these target ganglia close to the midline and extended only a few short branches that did not approach the lateral neuropils. Two of the three types of coordinating axons made direct synaptic connections with a class of local commissural interneurons that relayed the information to targets in the swimmeret pattern-generating circuits. These commissural interneurons, named here ComInt 1 neurons, followed a particular route to cross the midline and reach their targets. ComInt 1 neurons were nonspiking; they received EPSPs from the coordinating axons near the midline and transmitted this information to their targets in the lateral neuropils using graded transmission. The output of each ComInt 1 was restricted to a single local circuit and had opposite effects on the power-stroke and return-stroke motor neurons driven by that circuit. ComInt 1 neurons were direct postsynaptic targets of both descending and ascending coordinating axons that originated in other anterior and posterior ganglia. Because of phase differences in the impulses in these different coordinating axons, their signals arrived simultaneously at each ComInt 1. We discuss these findings in the context of alternative models of the intersegmental coordinating circuit.

During fictive locomotion, graded synaptic currents drive bursts of impulses in swimmeret motor neurons

During forward swimming, motor neurons that innervate each crayfish swimmeret fire periodic coordinated bursts of impulses. These bursts occur simultaneously in neurons that are functional synergists but alternate with bursts in their antagonists. These impulses ride on periodic oscillations of membrane potential that occur simultaneously in neurons of each type. A model of the local circuit that generates this motor pattern has been proposed. In this model, each motor neuron is driven alternately by excitatory and inhibitory synaptic currents from nonspiking local interneurons. I tested this model by perturbing individual interneurons and recording synaptic currents and changes in input resistance from each class of motor neuron. I also simulated the synaptic currents that would be observed in a cell subject to different patterns of presynaptic input. When the CNS was actively expressing the swimming motor pattern, changes in the membrane potential of individual local interneurons controlled firing of whole sets of motor neurons. Membrane currents in these motor neurons oscillated in phase with the motor output from their own local circuit. The phases of these oscillations differed in different functional classes of motor neurons. In neurons that could be clamped at the reversal potential of their outward currents, the model predicted that large periodic inward currents would be recorded. I observed no signs of periodic inward currents, even when the outward currents clearly had reversed. These results permit a simplification of the cellular model. They are discussed in the context of neural control of locomotion in crustacea and insects.

Coordination of cellular pattern-generating circuits that control limb movements: the sources of stable differences in intersegmental phases

Neuronal mechanisms in nervous systems that keep intersegmental phase lags the same at different frequencies are not well understood. We investigated biophysical mechanisms that permit local pattern-generating circuits in neighboring segments to maintain stable phase differences. We use a modified version of an existing model of the crayfish swimmeret system that is based on three known coordinating neurons and hypothesized intersegmental synaptic connections. Weakly coupled oscillator theory was used to derive coupling functions that predict phase differences between neurons in neighboring segments. We show how features controlling the size of the lag under simplified network configurations combine to create realistic lags in the full network. Using insights from the coupled oscillator theory analysis, we identify an alternative intersegmental connection pattern producing realistic stable phase differences. We show that the persistence of a stable phase lag to changes in frequency can arise from complementary effects on the network with ascending-only or descending-only intersegmental connections. To corroborate the numerical results, we experimentally constructed phase-response curves (PRCs) for two different coordinating interneurons in the swimmeret system by perturbing the firing of individual interneurons at different points in the cycle of swimmeret movement. These curves provide information about the contribution of individual intersegmental connections to the stable phase lag. We also numerically constructed PRCs for individual connections in the model. Similarities between the experimental and numerical PRCs confirm the plausibility of the network configuration that has been proposed and suggest that the same stabilizing balance present in the model underlies the normal phase-constant behavior of the swimmeret system.

Follower neurons in lobster (Panulirus interruptus) pyloric network regulate pacemaker period in complementary ways

Distributed neural networks (ones characterized by high levels of interconnectivity among network neurons) are not well understood. Increased insight into these systems can be obtained by perturbing network activity so as to study the functions of specific neurons not only in the network's "baseline" activity but across a range of network activities. We applied this technique to study cycle period control in the rhythmic pyloric network of the lobster, Panulirus interruptus. Pyloric rhythmicity is driven by an endogenous oscillator, the Anterior Burster (AB) neuron. Two network neurons feed back onto the pacemaker, the Lateral Pyloric (LP) neuron by inhibition and the Ventricular Dilator (VD) neuron by electrical coupling. LP and VD neuron effects on pyloric cycle period can be studied across a range of periods by altering period by injecting current into the AB neuron and functionally removing (by hyperpolarization) the LP and VD neurons from the network at each period. Within a range of pacemaker periods, the LP and VD neurons regulate period in complementary ways. LP neuron removal speeds the network and VD neuron removal slows it. Outside this range, network activity is disrupted because the LP neuron cannot follow slow periods, and the VD neuron cannot follow fast periods. These neurons thus also limit, in complementary ways, normal pyloric activity to a certain period range. These data show that follower neurons in pacemaker networks can play central roles in controlling pacemaker period and suggest that in some cases specific functions can be assigned to individual network neurons.

Architectonics of crayfish ganglia

The central nervous system of crayfish consists of a chain of segmental ganglia that are linked by cables of intersegmental axons. Each ganglion contains a highly-ordered core of longitudinal tracts, vertical tracts, commissures, and synaptic neuropils. We review from a technical perspective the history of the description of these ganglia, and recognize four episodes of progress. Each major innovation in anatomical methods has led to new insight into the structure and function of this nervous system, and new awareness of the structural patterns that are common to the CNS of all arthropods. Ganglia in different segments of the body differ in size, and appear to differ in anatomy. From a comparison of the structures of the cores of abdominal, thoracic, and subesophageal ganglia, we argue that this apparent difference is illusory. Rather, each of these ganglia is organized on the same plan, a plan also found in insect segmental ganglia. The apparent differences follow from longitudinal compression during development and from allometric growth of particular neuropils associated with innervation of the walking legs. Different authors have described the internal organization of ganglia in different segments, so we provide a cross-reference to the nomenclatures they have introduced. We compare the locations of cell bodies of motor neurons and accessory neurons that innervate different peripheral structures, and demonstrate double-labeling of certain GABAergic peripheral inhibitory neurons. Finally, we describe the construction of digital movies of serial sections of these ganglia, and discuss their utility.

Model for intersegmental coordination of leech swimming: central and sensory mechanisms

Sensory feedback as well as the coupling signals within the CNS are essential for leeches to produce intersegmental phase relationships in body movements appropriate for swimming behavior. To study the interactions between the central pattern generator (CPG) and peripheral feedback in controlling intersegmental coordination, we have constructed a computational model for the leech swimming system with physiologically realistic parameters. First, the leech swimming CPG is simulated by a chain of phase oscillators coupled by three channels of coordinating signals. The activity phase, the projection direction, and the phase response curve (PRC) of each channel are based on the identified intersegmental interneuron network. Output of this largely constrained model produces stable coordination in the simulated CPG with average phase lags of 8-10 degrees/segment in the period range from 0.5 to 1.5 s, similar to those observed in isolated nerve cords. The model also replicates the experimental finding that shorter chains of leech nerve cords have larger phase lags per segment. Sensory inputs, represented by stretch receptors, were subsequently incorporated into the CPG model. Each stretch receptor with its associated PRC, which was defined to mimic the experimental results of phase-dependent phase shifts of the central oscillator by the ventral stretch receptor, can alter the phase of the local central oscillator. Finally, mechanical interactions between the muscles from neighboring segments were simulated by PRCs linking adjacent stretch receptors. This model shows that interactions between neighboring muscles could globally increase the phase lags to the larger value required for the one-wavelength body form observed in freely swimming leeches. The full model also replicates the experimental observation that leeches with severed nerve cords have larger intersegmental phase lags than intact animals. The similarities between physiological and simulation results demonstrate that we have established a realistic model for the central and peripheral control of intersegmental coordination of leech swimming.

Sensory and central mechanisms control intersegmental coordination

Recent experiments on the sensory and central mechanisms that coordinate animal locomotory movements have advanced our understanding of the relative importance of these two components and overturned some previously held notions. In different experimental preparations, sensory inputs and central pattern generators have now been shown to play different roles in setting intersegmental phase lags.

Limb movements during locomotion: Tests of a model of an intersegmental coordinating circuit

During normal forward swimming, the swimmerets on neighboring segments of the crayfish abdomen make periodic power-stroke movements that have a characteristic intersegmental difference in phase. Three types of intersegmental interneurons that originate in each abdominal ganglion are necessary and sufficient to maintain this phase relationship. A cellular model of the intersegmental coordinating circuit that also produces the same intersegmental phase has been proposed. In this model, coordinating axons synapse with local interneurons in their target ganglion and form a concatenated circuit that links neighboring segmental ganglia. This model assumed that coordinating axons projected to their nearest-neighboring ganglion but not farther. We tested this assumption in two sets of experiments. If the assumption is correct, then blocking synaptic transmission in an intermediate ganglion should uncouple swimmeret activity on opposite sides of the block. We bathed individual ganglia in a low Ca(2+)-high Mg(2+) saline that effectively silenced both motor output from the ganglion and the coordinating interneurons that originated in it. With this block in place, other ganglia on opposite sides of the block could nonetheless maintain their normal phase difference. Simultaneous recordings of spikes in coordinating axons on opposite sides of the blocked ganglion showed that these axons projected beyond the neighboring ganglion. Selective bilateral ablation of the tracts in which these axons ran showed that they were necessary and usually sufficient to maintain coordination across a blocked ganglion. We discuss revisions of the cellular model of the coordinating circuit that would incorporate these new results.

A model of a segmental oscillator in the leech heartbeat neuronal network

We modeled a segmental oscillator of the timing network that paces the heartbeat of the leech. This model represents a network of six heart interneurons that comprise the basic rhythm-generating network within a single ganglion. This model builds on a previous two cell model (Nadim et al., 1995) by incorporating modifications of intrinsic and synaptic currents based on the results of a realistic waveform voltage-clamp study (Olsen and Calabrese, 1996). Due to these modifications, the new model behaves more similarly to the biological system than the previous model. For example, the slow-wave oscillation of membrane potential that underlies bursting is similar in form and amplitude to that of the biological system. Furthermore, the new model with its expanded architecture demonstrates how coordinating interneurons contribute to the oscillations within a single ganglion, in addition to their role of intersegmental coordination.

Functional organization of crayfish abdominal ganglia. III. Swimmeret motor neurons

Swimmerets are limbs on several segments of the crayfish abdomen that are used for forward swimming and other behaviors. We present evidence that the functional modules demonstrated previously in physiological experiments are reflected in the morphological disposition of swimmeret motor neurons. The single nerve that innervates each swimmeret divides into two branches that separately contain the axons of power-stroke and return-stroke motor neurons. We used Co(++) or biocytin to backfill the entire pool of neurons that innervated a swimmeret, or functional subsets whose axons occurred in particular branches. Each filled cell body extended a single neurite that projected first to the Lateral Neuropil (LN), and there branched to form dendritic structures and its axon. All the motor neurons that innervated one swimmeret had cell bodies located in the ganglion from which their axons emerged, and the cell bodies of all but two of these neurons were located ipsilateral to their swimmeret. Counts of cell bodies filled from selected peripheral branches revealed about 35 power-stroke motor neurons and 35 return-stroke motor neurons. The cell bodies of these two types were segregated into different clusters within the ganglion, but both types sent their neurites into the ipsilateral LN and had their principle branches in this neuropil. We saw no significant differences in the numbers or distributions of these motor neurons in ganglia A2 through A5. These anatomical features are consistent with the physiological evidence that each swimmeret is controlled by its own neural module, which drives the alternating bursts of impulses in power-stroke and return-stroke motor neurons. We propose that the LN is the site of the synaptic circuit that generates this pattern.

Intersegmental coordination of swimmeret movements: mathematical models and neural circuits

Swimmerets move periodically through a cycle of power-strokes and return-strokes. Swimmerets on neighboring segments differ in phase by approximately 25%, and maintain this difference even when the period of the cycle changes from < 1 to > 4 Hz. We constructed a minimal cellular model of the segmental pattern-generating circuit which incorporated its essential components, and whose dynamics were like those of the local circuit. Three different intersegmental coordinating units were known to link neighboring ganglia, but their targets are unknown. We constructed different intersegmental circuits which these units might form between neighboring cellular models, and compared their dynamics with the real system. One intersegmental circuit could maintain an approximately 25% phase difference through a range of periods. In physiological experiments, we identified three types of intersegmental interneurons that originate in each ganglion and project to its neighbors. These neurons fire bursts at certain parts of the swimmeret cycle in their home ganglion. These three neurons are necessary and sufficient to maintain normal coordination between neighboring segments. Their properties conform to the predictions of the cellular model.