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The dynamical properties of the brain and the dynamics of the body strongly influence one another. Their interaction generates complex adaptive behavior. While a wide variety of simulation tools exist for neural dynamics or biomechanics separately, there are few options for integrated brain-body modeling. Here, we provide a tutorial to demonstrate how the widely-used NEURON simulation platformcan support integrated neuromechanicalmodeling. As a first step toward incorporating biomechanics into a NEURON simulation, we provide a framework for integrating inputs from a "periphery" and outputs to that periphery. In other words, "body" dynamics are driven in part by "brain" variables, such as voltages or firing rates, and "brain" dynamics are influenced by "body" variables through sensory feedback. To couple the "brain" and "body" components, we use NEURON's pointer construct to share information between "brain" and "body" modules. This approach allows separate specification of brain and body dynamics and code reuse. Though simple in concept, the use of pointers can be challenging due to a complicated syntax and several different programming options. In this paper, we present five different computational models, with increasing levels of complexity, to demonstrate the concepts of code modularity using pointers and the integration of neural and biomechanical modeling within NEURON. The models include: (1) a neuromuscular model of calcium dynamics and muscle force, (2) a neuromechanical, closed-loop model of a half-center oscillator coupled to a rudimentary motor system, (3) a closed-loop model of neural control for respiration, (4) a pedagogical model of a non-smooth "brain/body" system, and (5) a closed-loop model of feeding behavior in the sea hare Aplysia californica that incorporates biologically-motivated non-smooth dynamics. This tutorial illustrates how NEURON can be integrated with a broad range of neuromechanical models. [ABSTRACT FROM AUTHOR]

This work presents an in-depth numerical investigation into a hypothesized two-layer central pattern generator (CPG) that controls mammalian walking and how different parameter choices might affect the stepping of a simulated neuromechanical model. Particular attention is paid to the functional role of features that have not received a great deal of attention in previous work: the weak cross-excitatory connectivity within the rhythm generator and the synapse strength between the two layers. Sensitivity evaluations of deafferented CPG models and the combined neuromechanical model are performed. Locomotion frequency is increased in two different ways for both models to investigate whether the model's stability can be predicted by trends in the CPG's phase response curves (PRCs). Our results show that the weak cross-excitatory connection can make the CPG more sensitive to perturbations and that increasing the synaptic strength between the two layers results in a trade-off between forced phase locking and the amount of phase delay that can exist between the two layers. Additionally, although the models exhibit these differences in behavior when disconnected from the biomechanical model, these differences seem to disappear with the full neuromechanical model and result in similar behavior despite a variety of parameter combinations. This indicates that the neural variables do not have to be fixed precisely for stable walking; the biomechanical entrainment and sensory feedback may cancel out the strengths of excitatory connectivity in the neural circuit and play a critical role in shaping locomotor behavior. Our results support the importance of including biomechanical models in the development of computational neuroscience models that control mammalian locomotion. [ABSTRACT FROM AUTHOR]

Some behaviors occur in obligatory sequence, such as reaching before grasping an object. Can the earlier behavior serve to prepare the musculature for the later behavior? If it does, what is the underlying neural mechanism of the preparation? To address this question, we examined two feeding behaviors in the marine mollusk Aplysia californica, one of which must precede the second: biting and swallowing. Biting is an attempt to grasp food. When that attempt is successful, the animal immediately switches to swallowing to ingest food. The main muscle responsible for pulling food into the buccal cavity during swallowing is the I3 muscle, whose motor neurons B6, B9, and B3 have been previously identified. By performing recordings from these neurons in vivo in intact, behaving animals or in vitro in a suspended buccal mass preparation, we demonstrated that the frequencies and durations of these motor neurons increased from biting to swallowing. Using the physiological patterns of activation to drive these neurons intracellularly, we further demonstrated that activating them using biting-like frequencies and durations, either alone or in combination, generated little or no force in the I3 muscle. When biting-like patterns preceded swallowing-like patterns, however, the forces during the subsequent swallowing-like patterns were significantly enhanced. Sequences of swallowing-like patterns, either with these neurons alone or in combination, further enhanced forces in the I3 muscle. These results suggest a novel mechanism for enhancing force production in a muscle, and may be relevant to understanding motor control in vertebrates. [ABSTRACT FROM AUTHOR]

What are the mechanisms of multifunctionality, i.e. the use of the same peripheral structures for multiple behaviors? We studied this question using the multifunctional feeding apparatus of the marine mollusk Aplysia californica, in which the same muscles mediate biting (an attempt to grasp food) and swallowing (ingestion of food). Biting and swallowing responses were compared using magnetic resonance imaging of intact, behaving animals and a three-dimensional kinematic model. Biting is associated with larger amplitude protractions of the grasper (radula/odontophore) than swallowing, and smaller retractions. Larger biting protractions than in swallowing appear to be due to a more anterior position of the grasper as the behavior begins, a larger amplitude contraction of protractor muscle 12, and contraction of the posterior portion of the I1/I3/jaw complex. The posterior I1/I3/jaw complex may be context-dependent, i.e. its mechanical context changes the direction of the force it exerts. Thus, the posterior of I1/I3 may aid protraction near the peak of biting, whereas the entire I1/I3/jaw complex acts as a retractor during swallowing. In addition, larger amplitude closure of the grasper during swallowing allows an animal to exert more force as it ingests food. These results demonstrate that differential deployment of the periphery can mediate multifunctionality. [ABSTRACT FROM AUTHOR]

How are the same muscles and neurons used to generate qualitatively different behaviors? We studied this question by analyzing the biomechanical and neural mechanisms of rejection responses in the marine mollusk Aplysia californica and compared these mechanisms with those used to generate swallowing responses (Ye et al., 2006). During rejection, the central grasper of the feeding structure closes to push inedible food out of the buccal cavity. This contrasts with swallowing, during which the grasper is open as it moves toward the jaws (protracts). We examined how the shape change of the grasper during rejection mechanically reconfigured the surrounding musculature. Grasper shape change increased the effectiveness of protractor muscle I2. The closed grasper alters the function of another muscle, the hinge, which becomes capable of inducing ventral rotations of rejected material. In contrast, during large-amplitude swallows, the hinge muscle mediates dorsal rotations of ingested material. Finally, after the grasper opens, its change in shape induces a delay in the activation of other surrounding muscles, the I1/I3/jaw complex, whose premature activation would close the halves of the grasper and induce it to pull inedible material back inward. The delay in activation of the I1/I3/jaw complex is partially attributable to identified multiaction neurons B4/B5. The results suggest that multifunctionality emerges from a periphery in which flexible coalitions of muscles may perform different functions in different mechanical contexts and in which neural circuitry is capable of reorganizing to exploit these coalitions by changes in phasing, duration, and intensity of motor neuronal activation. [ABSTRACT FROM AUTHOR]

Bernstein (1967) hypothesized that preparation of the periphery was crucial for correct responses to motor output. To test this hypothesis in a behaving animal, we examined the roles of two identified motor neurons, B7 and B8, which contribute to feeding behavior in the marine mollusk Aplysia californica. Neuron B7 innervates a hinge muscle and has no overt behavioral effect during smaller-amplitude (type A) swallows, because the hinge muscle is too short to exert force. Neuron B8 activates a muscle (I4) that acts solely to grasp material during type A swallows. During larger-amplitude (type B) swallows, the behavioral actions of both motor neurons change, because the larger-amplitude anterior movement of the grasper sets up the periphery to respond differently to motor outputs. The larger anterior movement stretches the hinge muscle, so that activating neuron B7 mediates the initial retraction phase of swallowing. The changed position of the I4 muscle allows neuron B8 not only to induce grasping but also to pull material into the buccal cavity, contributing to retraction. Thus, larger-amplitude swallows are associated with the expression of two new degrees of freedom (use of the hinge to retract and use of the grasper to retract) that are essential for mediating type B swallows. These results provide a direct demonstration of Bernstein's hypothesis that properly positioning the periphery can be crucial for its ability to correctly respond to motor output and also demonstrate that biomechanical context can alter the functions of identified motor neurons. [ABSTRACT FROM AUTHOR]

Explains adaptive behavior within the context of biomechanics of the body, structure of the organism's environment and the feedback between the nervous system, the body and the environment. Processing of inputs to and outputs from the nervous system; Matching of neural and peripheral properties; Importance of feedback in generation of adaptive behavior.