Neuromodulation for behavior in the locust frontal ganglion

Neuromodulators orchestrate complex behavioral routines by their multiple and combined effects on the nervous system. In the desert locust, Schistocerca gregaria, frontal ganglion neurons innervate foregut dilator muscles and play a key role in the control of foregut motor patterns. To further investigate the role of the frontal ganglion in locust behavior, we currently focus on the frontal ganglion central pattern generator as a target for neuromodulation. Application of octopamine, a well-studied insect neuromodulator, generated reversible disruption of frontal ganglion rhythmic activity. The threshold for the modulatory effects of octopamine was 10^–6 mol l^–1, and 10^–4 mol l^–1 always abolished the ongoing rhythm. In contrast to this straightforward modulation, allatostatin, previously reported to be a myoinhibitor of insect gut muscles, showed complex, tri-modal, dose-dependent effects on frontal ganglion rhythmic pattern. Using a novel cross-correlation analysis technique, we show that different allatostatin concentrations have very different effects not only on cycle period but also on temporal characteristics of the rhythmic bursts of action potentials. Allatostatin also altered the frontal ganglion rhythm in vivo. The analysis technique we introduce may be instrumental in the study of not fully characterized neural circuits and their modulation. The physiological significance of our results and the role of the modulators in locust behavior are discussed.Abbreviation CPG central pattern generator - FG frontal ganglion - JH juvenile hormone - STNS stomatogastric nervous system     

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.     

Multi-neuronal refractory period adapts centrally generated behaviour to reward

Oscillating neuronal circuits, known as central pattern generators (CPGs), are responsible for generating rhythmic behaviours such as walking, breathing and chewing. The CPG model alone however does not account for the ability of animals to adapt their future behaviour to changes in the sensory environment that signal reward. Here, using multi-electrode array (MEA) recording in an established experimental model of centrally generated rhythmic behaviour we show that the feeding CPG of Lymnaea stagnalis is itself associated with another, and hitherto unidentified, oscillating neuronal population. This extra-CPG oscillator is characterised by high population-wide activity alternating with population-wide quiescence. During the quiescent periods the CPG is refractory to activation by food-associated stimuli. Furthermore, the duration of the refractory period predicts the timing of the next activation of the CPG, which may be minutes into the future. Rewarding food stimuli and dopamine accelerate the frequency of the extra-CPG oscillator and reduce the duration of its quiescent periods. These findings indicate that dopamine adapts future feeding behaviour to the availability of food by significantly reducing the refractory period of the brain's feeding circuitry.     

The interrelations between malfunctioning DNA damage response (DDR) and the functionality of the neuro-glio-vascular unit

A hallmark of neurodegenerative diseases is impairment of certain aspects of “brain functionality”. Brain functionality is defined as the total input and output of the brain's neural circuits and networks. A given brain degenerative disorder does not deregulate total brain functionality but rather the activity of specific circuits in a given network, affecting their organization and topology, their cell numbers, their cellular functionality, and the interactions between neural circuits. Similarly, our concept of neurodegenerative diseases, which for many years revolved around neural survival or death, has now been extended to emphasize the role of glia. In particular, the role of glial cells in neuro-vascular communication is now known to be central to the effect of insults to the nervous system. In addition, a malfunctioning vascular system likely plays a role in the etiology of certain neurodegenerative diseases. Thus, the symptoms of neurodegenerative or more correctly brain degenerative disease are, to a very large extent, a result of impairment in glial cells that lead to pathological neuro-vascular interactions that, in turn, generate a rather “hostile” environment in which the neurons fail to function. These events lead to systematic neural cell death on a scale that appears to be proportional to the severity of the neurological deficit.     

Anatomical Organization of Multiple Modulatory Inputs in a Rhythmic Motor System

In rhythmic motor systems, descending projection neuron inputs elicit distinct outputs from their target central pattern generator (CPG) circuits. Projection neuron activity is regulated by sensory inputs and inputs from other regions of the nervous system, relaying information about the current status of an organism. To gain insight into the organization of multiple inputs targeting a projection neuron, we used the identified neuron MCN1 in the stomatogastric nervous system of the crab, Cancer borealis. MCN1 originates in the commissural ganglion and projects to the stomatogastric ganglion (STG). MCN1 activity is differentially regulated by multiple inputs including neuroendocrine (POC) and proprioceptive (GPR) neurons, to elicit distinct outputs from CPG circuits in the STG. We asked whether these defined inputs are compact and spatially segregated or dispersed and overlapping relative to their target projection neuron. Immunocytochemical labeling, intracellular dye injection and three-dimensional (3D) confocal microscopy revealed overlap of MCN1 neurites and POC and GPR terminals. The POC neuron terminals form a defined neuroendocrine organ (anterior commissural organ: ACO) that utilizes peptidergic paracrine signaling to act on MCN1. The MCN1 arborization consistently coincided with the ACO structure, despite morphological variation between preparations. Contrary to a previous 2D study, our 3D analysis revealed that GPR axons did not terminate in a compact bundle, but arborized more extensively near MCN1, arguing against sparse connectivity of GPR onto MCN1. Consistent innervation patterns suggest that integration of the sensory GPR and peptidergic POC inputs occur through more distributed and more tightly constrained anatomical interactions with their common modulatory projection neuron target than anticipated.     

Associative neural network model for the generation of temporal patterns. Theory and application to central pattern generators.

Cyclic patterns of motor neuron activity are involved in the production of many rhythmic movements, such as walking, swimming, and scratching. These movements are controlled by neural circuits referred to as central pattern generators (CPGs). Some of these circuits function in the absence of both internal pacemakers and external feedback. We describe an associative neural network model whose dynamic behavior is similar to that of CPGs. The theory predicts the strength of all possible connections between pairs of neurons on the basis of the outputs of the CPG. It also allows the mean operating levels of the neurons to be deduced from the measured synaptic strengths between the pairs of neurons. We apply our theory to the CPG controlling escape swimming in the mollusk Tritonia diomedea. The basic rhythmic behavior is shown to be consistent with a simplified model that approximates neurons as threshold units and slow synaptic responses as elementary time delays. The model we describe may have relevance to other fixed action behaviors, as well as to the learning, recall, and recognition of temporally ordered information.     

Computer simulation study on central pattern generator: from biology to engineering

Central pattern generator (CPG) is a neuronal circuit in the nervous system that can generate oscillatory patterns for the rhythmic movements. Its simplified format, neural oscillator, is wildly adopted in engineering application. This paper explores the CPG from an integral view that combines biology and engineering together. Biological CPG and simplified CPG are both studied. Computer simulation reveals the mechanism of CPG. Some properties, such as effect of tonic input and sensory feedback, stable oscillation, robustness, entrainment etc., are further studied. The promising results provide foundation for the potential engineering application in future.     

Premotor neurons in the feeding system of Aplysia californica

Central pattern generator (CPG) circuits control cyclic motor output underlying rhythmic behaviors. Although there have been extensive behavioral and cellular studies of food-induced feeding arousal as well as satiation in Aplysia, very little is known about the neuronal circuits controlling rhythmic consummatory feeding behavior. However, recent studies have identified premotor neurons that initiate and maintain buccal motor programs underlying ingestion and egestion in Aplysia. Other newly identified neurons receive synaptic input from feeding CPGs and in turn synapse with and control the output of buccal motor neurons. Some of these neurons and their effects within the buccal system are modulated by endogenous neuropeptides. With this information we can begin to understand how neuronal networks control buccal motor output and how their activity is modulated to produce flexibility in observed feeding behavior.     

On the definition of central pattern generator and its sensory control

A central pattern generator (CPG) is defined here as a neural network responsible for the production of the timing cues of a rhythmic motor output pattern in the isolated CNS. For the intact animal, model considerations show that this term is neither clearly delimited from the concept of a reflex chain nor from the concept of a pattern generator with functional principles different from those of the CPG. Therefore, it cannot be concluded from the existence of a CPG in the isolated nervous system that this CPG also provides the decisive timing cues in the intact animal. Consequences for the study of the neural basis of rhythmic movements are shown.     

Neuromodulation of central pattern generators in invertebrates and vertebrates

Central pattern generators are subject to extensive modulation that generates flexibility in the rhythmic outputs of these neural networks. The effects of neuromodulators interact with one another, and modulatory neurons are themselves often subject to modulation, enabling both higher order control and indirect interactions among central pattern generators. In addition, modulators often directly mediate the interactions between functionally related central pattern generators. In systems such as the vertebrate respiratory central pattern generator, multiple pacemaker types interact to produce rhythmic output. Modulators can then alter the relative contributions of the different pacemakers, leading to substantial changes in motor output and hence to different behaviors. Surprisingly, substantial changes in some aspects of the circuitry of a central pattern generator, such as a several-fold increase in synaptic strength, can sometimes have little effect on the output of the CPG, whereas other changes have profound effects.     

Central pattern generators and the control of rhythmic movements.

Central pattern generators are neuronal circuits that when activated can produce rhythmic motor patterns such as walking, breathing, flying, and swimming in the absence of sensory or descending inputs that carry specific timing information. General principles of the organization of these circuits and their control by higher brain centers have come from the study of smaller circuits found in invertebrates. Recent work on vertebrates highlights the importance of neuro-modulatory control pathways in enabling spinal cord and brain stem circuits to generate meaningful motor patterns. Because rhythmic motor patterns are easily quantified and studied, central pattern generators will provide important testing grounds for understanding the effects of numerous genetic mutations on behavior. Moreover, further understanding of the modulation of spinal cord circuitry used in rhythmic behaviors should facilitate the development of new treatments to enhance recovery after spinal cord damage.     

Neuromodulation and flexibility in Central Pattern Generator networks

Central Pattern Generator (CPG) networks, which organize rhythmic movements, have long served as models for neural network organization. Modulatory inputs are essential components of CPG function: neuromodulators set the parameters of CPG neurons and synapses to render the networks functional. Each modulator acts on the network by many effects which may oppose one another; this may serve to stabilize the modulated state. Neuromodulators also determine the active neuronal composition in the CPG, which varies with state changes such as locomotor speed. The pattern of gene expression which determines the electrophysiological personality of each CPG neuron is also under modulatory control. It is not possible to model the function of neural networks without including the actions of neuromodulators.     

Neuropeptide modulation of microcircuits

Neuropeptides provide functional flexibility to microcircuits, their inputs and effectors by modulating presynaptic and postsynaptic properties and intrinsic currents. Recent studies have relied less on applied neuropeptide and more on their neural release. In rhythmically active microcircuits (central pattern generators, CPGs), recent studies show that neuropeptide modulation can enable particular activity patterns by organizing specific circuit motifs. Neuropeptides can also modify microcircuit output indirectly, by modulating circuit inputs. Recently elucidated consequences of neuropeptide modulation include changes in motor patterns and behavior, stabilization of rhythmic motor patterns and changes in CPG sensitivity to sensory input. One aspect of neuropeptide modulation that remains enigmatic is the presence of multiple peptide family members in the same nervous system and even the same neurons.     

Invertebrate central pattern generator circuits

There are now a reasonable number of invertebrate central pattern generator (CPG) circuits described in sufficient detail that a mechanistic explanation of how they work is possible. These small circuits represent the best-understood neural circuits with which to investigate how cell-to-cell synaptic connections and individual channel conductances combine to generate rhythmic and patterned output. In this review, some of the main lessons that have appeared from this analysis are discussed and concrete examples of circuits ranging from single phase to multiple phase patterns are described. While it is clear that the cellular components of any CPG are basically the same, the topology of the circuits have evolved independently to meet the particular motor requirements of each individual organism and only a few general principles of circuit operation have emerged. The principal usefulness of small systems in relation to the brain is to demonstrate in detail how cellular infrastructure can be used to generate rhythmicity and form specialized patterns in a way that may suggest how similar processes might occur in more complex systems. But some of the problems and challenges associated with applying data from invertebrate preparations to the brain are also discussed. Finally, I discuss why it is useful to have well-defined circuits with which to examine various computational models that can be validated experimentally and possibly applied to brain circuits when the details of such circuits become available.     

Neural mechanisms generating locomotion studied in mammalian brain stem-spinal cord in vitro

The neural control system for generation of locomotion is an important system for analysis of neural mechanisms underlying complex motor acts. In these studies, a novel experimental model using neonatal rat brain stem and spinal cord in vitro was developed for investigation of the locomotor system in mammals. The in vitro brain stem and spinal cord system was shown to retain functional circuitry for locomotor command generation, motor pattern generation, and sensorimotor integration. This system was exploited to investigate neurochemical mechanisms involved in neurogenesis of locomotion. Evidence was obtained for peptidergic and gamma-amino-butyric acid-mediated mechanisms in brain-stem circuits generating locomotor commands. Cholinergic, dopaminergic, and excitatory amino acid-mediated mechanisms were shown to activate spinal cord circuits for locomotor pattern generation. Endogenous N-methyl-D-aspartic acid receptors in spinal networks were found to play a central role in the generation of locomotion. The chemically induced patterns of motor activity and rhythmic membrane potential oscillations of spinal motoneurons were characteristic of those during locomotion in other mammals in vivo. The in vitro brain stem and spinal cord model provides a versatile and powerful experimental system with potentially broad application for investigation of diverse aspects of the neurobiology of mammalian motor control systems.     

An inter-segmental network model and its use in elucidating gait-switches in the stick insect

Animal locomotion requires highly coordinated working of the segmental neuronal networks that control the limb movements. Experiments have shown that sensory signals originating from the extremities play a pivotal role in controlling locomotion patterns by acting on central networks. Based on the results from stick insect locomotion, we constructed an inter-segmental model comprising local networks for all three legs, i.e. for the pro-, meso- and meta-thorax, their inter-connections and the main sensory inputs modifying their activities. In the model, the local networks are uniform, and each of them consists of a central pattern generator (CPG) providing the rhythmic oscillation for the protractor-retractor motor systems, the corresponding motoneurons (MNs), and local inhibitory interneurons (IINs) between the CPGs and the MNs. Between segments, the CPGs are connected cyclically by both excitatory and inhibitory pathways that are modulated by the aforementioned sensory inputs. Simulations done with our network model showed that it was capable of reproducing basic patterns of locomotion such as those occurring during tri- and tetrapod gaits. The model further revealed a number of elementary neuronal processes (e.g. synaptic inhibition, or changing the synaptic drive at specific neurons) that in the simulations were necessary, and in their entirety sufficient, to bring about a transition from one type of gait to another. The main result of this simulation study is that exactly the same mechanism underlies the transition between the two types of gait irrespective of the direction of the change. Moreover, the model suggests that the majority of these processes can be attributed to direct sensory influences, and changes are required only in centrally controlled synaptic drives to the CPGs.     

Possible contributions of CPG activity to the control of rhythmic human arm movement

There is extensive modulation of cutaneous and H-reflexes during rhythmic leg movement in humans. Mechanisms controlling reflex modulation (e.g., phase- and task-dependent modulation, and reflex reversal) during leg movements have been ascribed to the activity of spinal central pattern generating (CPG) networks and peripheral feedback. Our working hypothesis has been that neural mechanisms (i.e., CPGs) controlling rhythmic movement are conserved between the human lumbar and cervical spinal cord. Thus reflex modulation during rhythmic arm movement should be similar to that for rhythmic leg movement. This hypothesis has been tested by studying the regulation of reflexes in arm muscles during rhythmic arm cycling and treadmill walking. This paper reviews recent studies that have revealed that reflexes in arm muscles show modulation within the movement cycle (e.g., phase-dependency and reflex reversal) and between static and rhythmic motor tasks (e.g., task-dependency). It is concluded that reflexes are modulated similarly during rhythmic movement of the upper and lower limbs, suggesting similar motor control mechanisms. One notable exception to this pattern is a failure of contralateral arm movement to modulate reflex amplitude, which contrasts directly with observations from the leg. Overall, the data support the hypothesis that CPG activity contributes to the neural control of rhythmic arm movement.     

Comparative strategies in the investigation of neural networks.

Comparative studies on nervous systems, though infrequently undertaken for the purpose of comparison, have yielded some important generalities about the formats of nervous networks, and about the cell biology of certain neural types. In the first category, it is clear that convergent evolutionary processes arrived at very similar networks to accomplish reciprocal and lateral inhibition, and load-compensation in "resistance reflexes." A newer general network format is described, command-derived inhibition, in which the central nervous elements controlling a rapid movement deliver presynaptic inhibition to the terminals of sensory neurons that carry reafferent excitation from the movement. It is argued that such circuits occur in several groups of animals, and that they include as a special class the efferent inhibitory neurons innervating acoustico-lateralis receptors in vertebrates. The properties of circuit elements that now seem to constitute useful generalizations include size principle (the inverse relationship between size and excitability in a variety of neurons), and the late differentiation of sensory neurons, failure to decussate, and their inability to mediate inhibition. Many other generalities have emerged, only to fall; one conclusion from such searches is that many supposedly "basic" properties of cell types or neural circuits are in fact not phylogenetically conservative, however much the physiologist may expect them to be.     

Resonance tuning in a neuro-musculo-skeletal model of the forearm

In rhythmic movements, humans activate their muscles in a robust and energy efficient way. These activation patterns are oscillatory and seem to originate from neural networks in the spinal cord, called central pattern generators (CPGs). Evidence for the existence of CPGs was found for instance in lampreys, cats and rats. There are indications that CPGs exist in humans as well, but this is not proven yet. Energy efficiency is achieved by resonance tuning: the central nervous system is able to tune into the resonance frequency of the limb, which is determined by the local reflex gains. The goal of this study is to investigate if the existence of a CPG in the human spine can explain the resonance tuning behavior, observed in human rhythmic limb movement. A neuro-musculo-skeletal model of the forearm is proposed, in which a CPG is organized in parallel to the local reflexloop. The afferent and efferent connections to the CPG are based on clues about the organization of the CPG, found in literature. The model is kept as simple as possible (i.e., lumped muscle models, groups of neurons are lumped into half-centers, simple reflex model), but incorporates enough of the essential dynamics to explain behavior—such as resonance tuning—in a qualitative way. Resonance tuning is achieved above, at and below the endogenous frequency of the CPG in a highly non-linear neuro- musculo-skeletal model. Afferent feedback of muscle lengthening to the CPG is necessary to accomplish resonance tuning above the endogenous frequency of the CPG, while feedback of muscle velocity is necessary to compensate for the phase lag, caused by the time delay in the loop coupling the limb to the CPG. This afferent feedback of muscle lengthening and velocity represents the Ia and II fibers, which—according to literature—is the input to the CPG. An internal process of the CPG, which integrates the delayed muscle lengthening and feeds it to the half-center model, provides resonance tuning below the endogenous frequency. Increased co-contraction makes higher movement frequencies possible. This agrees with studies of rhythmic forearm movements, which have shown that co-contraction increases with movement frequency. Robustness against force perturbations originates mainly from the CPG and the local reflex loop. The CPG delivers an increasing part of the necessary muscle activation for increasing perturbation size. As far as we know, the proposed neuro-musculo-skeletal model is the first that explains the observed resonance tuning in human rhythmic limb movement.     

Neural networks for perceptual processing: from simulation tools to theories

Neural networks are modelling tools that are, in principle, able to capture the input-output behaviour of arbitrary systems that may include the dynamics of animal populations or brain circuits. While a neural network model is useful if it captures phenomenologically the behaviour of the target system in this way, its utility is amplified if key mechanisms of the model can be discovered, and identified with those of the underlying system. In this review, we first describe, at a fairly high level with minimal mathematics, some of the tools used in constructing neural network models. We then go on to discuss the implications of network models for our understanding of the system they are supposed to describe, paying special attention to those models that deal with neural circuits and brain systems. We propose that neural nets are useful for brain modelling if they are viewed in a wider computational framework originally devised by Marr. Here, neural networks are viewed as an intermediate mechanistic abstraction between 'algorithm' and 'implementation', which can provide insights into biological neural representations and their putative supporting architectures.