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.     

Regulation of afferent transmission in the feeding circuitry of Aplysia

Although feeding in Aplysia is mediated by a central pattern generator (CPG), the activity of this CPG is modified by afferent input. To determine how afferent activity produces the widespread changes in motor programs that are necessary if behavior is to be modified, we have studied two classes of feeding sensory neurons. We have shown that afferent-induced changes in activity are widespread because sensory neurons make a number of synaptic connections. For example, sensory neurons make monosynaptic excitatory connections with feeding motor neurons. Sensori-motor transmission is, however, regulated so that changes in the periphery do not disrupt ongoing activity. This results from the fact that sensory neurons are also electrically coupled to feeding interneurons. During motor programs sensory neurons are, therefore, rhythmically depolarized via central input. These changes in membrane potential profoundly affect sensori-motor transmission. For example, changes in membrane potential alter spike propagation in sensory neurons so that spikes are only actively transmitted to particular output regions when it is behaviorally appropriate. To summarize, afferent activity alters motor output because sensory neurons make direct contact with motor neurons. Sensori-motor transmission is, however, centrally regulated so that changes in the periphery alter motor programs in a phase-dependent manner.     

An Approach for Adaptive Limbless Locomotion Using a CPG-Based Reflex Mechanism

Animals＇ free movement in natural environments has attracted many researchers to explore control methods for bio-inspired robots. This paper presents a novel reflex mechanism based on a Central Pattern Generator （CPG） for adaptive locomotion of limbless robots. First, inspired by the concept of reflex arc, the reflex mechanism is designed on a connectionist CPG model. Since the CPG model inspired by the spinal cord of lampreys is developed at the neuron level, it provides a possible natural solution for sensory reflex integration. Therefore, sensory neurons that bridge the external stimuli and the CPG model, together with the concept of reflex arc, are utilized for designing the sensory reflex mechanism. Then, a border reflex and a body reflex are further developed and applied on the ends and the middle part of a limbless robot, respectively. Finally, a ball hitting scenario and a corridor passing scenario are designed to verify the proposed method. Results of simulations and on-site experiments show the feasibility and effectiveness of the reflex mechanism in realizing fast response and adaptive limbless locomotion.     

Adaptive feeding across environmental gradients and its effect on population dynamics

This paper analyzes a consumer's adaptive feeding response to environmental gradients. We consider a consumer-resource system where resources are distributed among many discrete resource patches. Each consumer exhibits a feeding morphology allowing it to remove resources from a patch down to some threshold density (or level) before having to seek resources elsewhere. Assuming consumers trade off resource extraction with patch access and predation, we show that for a given environment there often exists a single evolutionarily stable feeding threshold and it is an evolutionary attractor. We then investigate how the population dynamics of the resource and the consumer change as the environment changes. Two cases are considered: (i) all consumers exhibit a fixed feeding threshold that is adaptive for an intermediate environment; and (ii) the consumer population adapts and adopts the evolutionarily stable feeding threshold associated with the current environment. In less harsh environments (i.e., environments where consumers experience a lower risk of predation, or environments where resource patches are more abundant) the adaptive consumer population is predicted to evolve so that resources within a patch are depleted to lower densities. We show that the change in consumer density due to environmental change can be rather different depending on whether or not the population can adapt. In some situations we observe that when the consumer's environment becomes harsher, the consumer population may increase in density before a rapid crash to extinction. This result has implications for monitoring and managing a population.     

Transfer of habituation in Aplysia: contribution of heterosynaptic pathways in habituation of the gill-withdrawal reflex

Habituation of the Aplysia gill-withdrawal reflex (and siphon-withdrawal reflex) has been attributed to low-frequency homosynaptic depression at central sensory-motor synapses. The recent demonstration that transfer of habituation between stimulation sites occurs in this model system has prompted the hypothesis that heterosynaptic inhibitory pathways also play a role in the mediation of habituation behavior. To test this hypothesis, the sites and mechanisms of neural plasticity which underlie transfer of habituation in Aplysia were examined. Transfer of habituation is a reduction in the reflex evoked at one stimulation site (siphon) due to repeated presentation of a stimulus to a second site (gill). Centrally mediated transfer of habituation, measured in a preparation lacking the siphon-gill peripheral nervous system (PNS), was associated with a reduced excitatory response in central motor neurons. Repeated tactile stimulation of the gill did not attenuate the gill response evoked by electrical stimulation of the branchial nerve nor the mechanoreceptor response recorded in LE sensory neurons. In contrast, repeated stimulation of siphon or gill at a site which was "off" the sensory field of a specific mechanoreceptor led to a diminution in synaptic transmission between that sensory neuron and its followers (motor neurons and inter-neurons). These data demonstrate that centrally mediated transfer of habituation results from heterosynaptic modulation of synaptic transmission at the sensory-motor (and sensory-interneuron) synapses. Therefore, habituation behavior in Aplysia is mediated through the conjoint action of homosynaptic and heterosynaptic inhibitory processes.     

Adaptive rescaling maximizes information transmission

Adaptation is a widespread phenomenon in nervous systems, providing flexibility to function under varying external conditions. Here, we relate an adaptive property of a sensory system directly to its function as a carrier of information about input signals. We show that the input/output relation of a sensory system in a dynamic environment changes with the statistical properties of the environment. Specifically, when the dynamic range of inputs changes, the input/output relation rescales so as to match the dynamic range of responses to that of the inputs. We give direct evidence that the scaling of the input/output relation is set to maximize information transmission for each distribution of signals. This adaptive behavior should be particularly useful in dealing with the intermittent statistics of natural signals.     

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.     

PolyADP-ribose polymerase-1 (PARP-1) and the evolution of learning and memory

PARP-1 is a multifunctional enzyme that can modulate gene expression. Cohen-Armon et al.(1) found that a homologue of PARP-1 is activated in the Aplysia nervous system as the animal responds to an aversive stimulus, which leads to sensitization, and during a more complex form of learning that involves feeding behavior. Significantly, inhibiting PARP-1 activation blocked the learning. Several key pathways in Aplysia neurons are activated both during learning and after injury, suggesting that mechanisms of learning evolved from primitive responses to injury. Since PARP-1 is evolutionarily conserved as a responder to various forms of stress, the finding that PARP-1 is activated during learning supports this idea.     

A model of the basal ganglia in voluntary movement and postural reactions

A basal ganglia central pattern generator (CPG) is developed and its role in voluntary movements on the ground and postural reactions on a disturbed platform are studied and analysed by simulation. Biped dynamics and platform kinematics are utilised. The effects of agonist–antagonist muscular co-activation and joint stiffness are formulated. The implementation of the necessary counter-manoeuvres for maintaining balance and postural stability is studied. A control strategy, applicable to large systems, is formulated. The biped manoeuvres and transitions terminate in pre-specified intervals of time. Gravity is included and compensated for. Certain voluntary and postural adjustment strategies are the same but are initiated differently. Further experimental/computational research may identify the central nervous system and sensory paths that lead to the CPG. All actuator forces linearly evolve in time from their original values to their terminal values. There are no central continuous feedback loops present. Monitoring and sensing, however, are ongoing. The counter-manoeuvres are based on learned human-like voluntary movements that are triggered by the disturbance. The required central inputs to the musculoskeletal system are designed in the CPG. A functional structure for the CPG is proposed. The effect of certain disorders and malfunctions of the CPG are studied by simulation.     

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.     

Shaping embodied neural networks for adaptive goal-directed behavior

The acts of learning and memory are thought to emerge from the modifications of synaptic connections between neurons, as guided by sensory feedback during behavior. However, much is unknown about how such synaptic processes can sculpt and are sculpted by neuronal population dynamics and an interaction with the environment. Here, we embodied a simulated network, inspired by dissociated cortical neuronal cultures, with an artificial animal (an animat) through a sensory-motor loop consisting of structured stimuli, detailed activity metrics incorporating spatial information, and an adaptive training algorithm that takes advantage of spike timing dependent plasticity. By using our design, we demonstrated that the network was capable of learning associations between multiple sensory inputs and motor outputs, and the animat was able to adapt to a new sensory mapping to restore its goal behavior: move toward and stay within a user-defined area. We further showed that successful learning required proper selections of stimuli to encode sensory inputs and a variety of training stimuli with adaptive selection contingent on the animat's behavior. We also found that an individual network had the flexibility to achieve different multi-task goals, and the same goal behavior could be exhibited with different sets of network synaptic strengths. While lacking the characteristic layered structure of in vivo cortical tissue, the biologically inspired simulated networks could tune their activity in behaviorally relevant manners, demonstrating that leaky integrate-and-fire neural networks have an innate ability to process information. This closed-loop hybrid system is a useful tool to study the network properties intermediating synaptic plasticity and behavioral adaptation. The training algorithm provides a stepping stone towards designing future control systems, whether with artificial neural networks or biological animats themselves.     

Tactile Modulation of Whisking via the Brainstem Loop: Statechart Modeling and Experimental Validation

Rats repeatedly sweep their facial whiskers back and forth in order to explore their environment. Such explorative whisking appears to be driven by central pattern generators (CPGs) that operate independently of direct sensory feedback. Nevertheless, whisking can be modulated by sensory feedback, and it has been hypothesized that some of this modulation already occurs within the brainstem. However, the interaction between sensory feedback and CPG activity is poorly understood. Using the visual language of statecharts, a dynamic, bottom-up computerized model of the brainstem loop of the whisking system was built in order to investigate the interaction between sensory feedback and CPG activity during whisking behavior. As a benchmark, we used a previously quantified closed-loop phenomenon of the whisking system, touched-induced pump (TIP), which is thought to be mediated by the brainstem loop. First, we showed that TIPs depend on sensory feedback, by comparing TIP occurrence in intact rats with that in rats whose sensory nerve was experimentally cut. We then inspected several possible feedback mechanisms of TIPs using our model. The model ruled out all hypothesized mechanisms but one, which adequately simulated the corresponding motion observed in the rat. Results of the simulations suggest that TIPs are generated via sensory feedback that activates extrinsic retractor muscles in the mystacial pad. The model further predicted that in addition to the touching whisker, all whiskers found on the same side of the snout should exhibit a TIP. We present experimental results that confirm the predicted movements in behaving rats, establishing the validity of the hypothesized interaction between sensory feedback and CPG activity we suggest here for the generation of TIPs in the whisking system.     

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.     

Sensory Feedback Mechanism Underlying Entrainment of Central Pattern Generator to Mechanical Resonance

Rhythmic body motions observed in animal locomotion are known to be controlled by neuronal circuits called central pattern generators (CPGs). It appears that CPGs are energy efficient controllers that cooperate with biomechanical and environmental constraints through sensory feedback. In particular, the CPGs tend to induce rhythmic motion of the body at a natural frequency, i.e., the CPGs are entrained to a mechanical resonance by sensory feedback. The objective of this paper is to uncover the mechanism of entrainment resulting from the dynamic interaction of the CPG and mechanical system. We first develop multiple CPG models for the reciprocal inhibition oscillator (RIO) and examine through numerical experiments whether they can be entrained to a simple pendulum. This comparative study identifies the neuronal properties essential for the entrainment. We then analyze the simplest model that captures the essential dynamics via the method of harmonic balance. It is shown that robust entrainment results from a strong, positive-feedback coupling of a lightly damped mechanical system and the RIO consisting of neurons with the complete adaptation property     

The adaptive dynamics of function-valued traits

This study extends the framework of adaptive dynamics to function-valued traits. Such adaptive traits naturally arise in a great variety of settings: variable or heterogeneous environments, age-structured populations, phenotypic plasticity, patterns of growth and form, resource gradients, and in many other areas of evolutionary ecology. Adaptive dynamics theory allows analysing the long-term evolution of such traits under the density-dependent and frequency-dependent selection pressures resulting from feedback between evolving populations and their ecological environment. Starting from individual-based considerations, we derive equations describing the expected dynamics of a function-valued trait in asexually reproducing populations under mutation-limited evolution, thus generalizing the canonical equation of adaptive dynamics to function-valued traits. We explain in detail how to account for various kinds of evolutionary constraints on the adaptive dynamics of function-valued traits. To illustrate the utility of our approach, we present applications to two specific examples that address, respectively, the evolution of metabolic investment strategies along resource gradients, and the evolution of seasonal flowering schedules in temporally varying environments.     

Mesoscopic Organization Reveals the Constraints Governing Caenorhabditis elegans Nervous System

One of the biggest challenges in biology is to understand how activity at the cellular level of neurons, as a result of their mutual interactions, leads to the observed behavior of an organism responding to a variety of environmental stimuli. Investigating the intermediate or mesoscopic level of organization in the nervous system is a vital step towards understanding how the integration of micro-level dynamics results in macro-level functioning. The coordination of many different co-occurring processes at this level underlies the command and control of overall network activity. In this paper, we have considered the somatic nervous system of the nematode Caenorhabditis elegans, for which the entire neuronal connectivity diagram is known. We focus on the organization of the system into modules, i.e., neuronal groups having relatively higher connection density compared to that of the overall network. We show that this mesoscopic feature cannot be explained exclusively in terms of considerations such as, optimizing for resource constraints (viz., total wiring cost) and communication efficiency (i.e., network path length). Even including information about the genetic relatedness of the cells cannot account for the observed modular structure. Comparison with other complex networks designed for efficient transport (of signals or resources) implies that neuronal networks form a distinct class. This suggests that the principal function of the network, viz., processing of sensory information resulting in appropriate motor response, may be playing a vital role in determining the connection topology. Using modular spectral analysis we make explicit the intimate relation between function and structure in the nervous system. This is further brought out by identifying functionally critical neurons purely on the basis of patterns of intra- and inter-modular connections. Our study reveals how the design of the nervous system reflects several constraints, including its key functional role as a processor of information.     

Local hormonal modulation of neural activity in Aplysia

The abdominal ganglion of Aplysia provides a convenient experimental system for cellular studies on the roles of peptides as chemical messengers in the nervous system. There are indications that the bag cells, a group of neuroendocrine cells, synthesize and release egg laying hormone (ELH), a peptide with an apparent molecular weight of 6000. Our recent investigations indicate that a burst of impulse activity in the bag cells produces five types of long-lasting responses, some excitatory, others inhibitory, in 26 identified neurons and 2 identified cell clusters located near the bag cells in the abdominal ganglion. The responses have slow, smoothly graded onsets, and many of them result in modulation of neuronal activity for 3 hours or more. Physiological and ultrastructural data support the hypothesis that they are induced by a bag cell hormone (or hormones) that is released into vascular and interstitial spaces of the ganglion to act on the target neurons. Local application of purified ELH to one of the target neurons provides evidence that the bag cell effect is mediated by ELH. Many of the target neurons are known to be parts of neuronal circuits that control specific behavioral and homeostatic processes. Since egg laying is initiated by the bag cell discharge and is associated with a stereotyped behavior pattern lasting several hours, the actions of these peptide-secreting neurons on the central nervous system may serve to regulate certain elements of behavior and homeostasis during egg laying.     

On the applicability of the decentralized control mechanism extracted from the true slime mold: a robotic case study with a serpentine robot

A systematic method for an autonomous decentralized control system is still lacking, despite its appealing concept. In order to alleviate this, we focused on the amoeboid locomotion of the true slime mold, and extracted a design scheme for the decentralized control mechanism that leads to adaptive behavior for the entire system, based on the so-called discrepancy function. In this paper, we intensively investigate the universality of this design scheme by applying it to a different type of locomotion based on a 'synthetic approach'. As a first step, we implement this design scheme to the control of a real physical two-dimensional serpentine robot that exhibits slithering locomotion. The experimental results show that the robot exhibits adaptive behavior and responds to the environmental changes; it is also robust against malfunctions of the body segments due to the local sensory feedback control that is based on the discrepancy function. We expect the results to shed new light on the methodology of autonomous decentralized control systems.     

Aging in Sensory and Motor Neurons Results in Learning Failure in Aplysia californica

The physiological and molecular mechanisms of age-related memory loss are complicated by the complexity of vertebrate nervous systems. This study takes advantage of a simple neural model to investigate nervous system aging, focusing on changes in learning and memory in the form of behavioral sensitization in vivo and synaptic facilitation in vitro. The effect of aging on the tail withdrawal reflex (TWR) was studied in Aplysia californica at maturity and late in the annual lifecycle. We found that short-term sensitization in TWR was absent in aged Aplysia. This implied that the neuronal machinery governing nonassociative learning was compromised during aging. Synaptic plasticity in the form of short-term facilitation between tail sensory and motor neurons decreased during aging whether the sensitizing stimulus was tail shock or the heterosynaptic modulator serotonin (5-HT). Together, these results suggest that the cellular mechanisms governing behavioral sensitization are compromised during aging, thereby nearly eliminating sensitization in aged Aplysia.