Proprioceptive feedback modulates coordinating information in a system of segmentally distributed microcircuits.

The system of modular neural circuits that controls crustacean swimmerets drives a metachronal sequence of power-stroke (PS, retraction) and return-stroke (RS, protraction) movements that propels the animal forward efficiently. These neural modules are synchronized by an intersegmental coordinating circuit that imposes characteristic phase differences between these modules. Using a semi-intact preparation that left one swimmeret attached to an otherwise isolated central nervous system (CNS) of the crayfish, Pacifastacus leniusculus, we investigated how the rhythmic activity of this system responded to imposed movements. We recorded extracellularly from the PS and RS nerves that innervated the attached limb and from coordinating axons that encode efference copies of the periodic bursts in PS and RS axons. Simultaneously, we recorded from homologous nerves in more anterior and posterior segments. Maintained retractions did not affect cycle period but promptly weakened PS bursts, strengthened RS bursts, and caused corresponding changes in the strength and timing of efference copies in the module's coordinating axons. Changes in these efference copies then caused changes in the phase and duration, but not the strength, of PS bursts in modules controlling neighboring swimmerets. These changes were promptly reversed when the limb was released. Each swimmeret is innervated by two nonspiking stretch receptors (NSSRs) that depolarize when the limb is retracted. Voltage clamp of an NSSR changed the durations and strengths of bursts in PS and RS axons innervating the same limb and caused corresponding changes in the efference copies of this motor output.

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 -- ASC(E) 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 ASC(E) neuron's target ganglion significantly affected its influence on the output from its home ganglion. We had predicted that ASC(E)'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 ASC(E) neurons showed an unexpected property, one that is partially masked when the bidirectional flow of information between neighboring ganglia is operating normally.

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.

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.

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.

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.