Dynamic Sensorimotor Interactions in Locomotion (original) (raw)
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Sensorimotor interactions during locomotion: principles derived from biological systems
Autonomous Robots, 1999
Rhythmic movements in biological systems are produced in part by central circuits called central pattern generators (CPGs). For example, locomotion in vertebrates derives from the spinal CPG with activity initiated by the brain and controlled by sensory feedback. Sensory feedback is traditionally viewed as controlling CPGs cycle by cycle, with the brain commanding movements on a top down basis. We present an alternative view which, in sensory feedback alters the properties of the CPG on a fast as well as a slow time scale. The CPG, in turn, provides feedforward filtering of the sensory feedback. This bidirectional interaction is widespread across animals, suggesting it is a common feature of motor systems, and, therefore, might offer a new way to view sensorimotor interactions in all systems including robotic systems. Bidirectional interactions are also apparent between the cerebral cortex and the CPG. The motor cortex doesn't simply command muscle contractions, but rather operates with the CPG to produce adaptively structured movements. To facilitate these adaptive interactions, the motor cortex receives feedback from the CPG that creates a temporal activity pattern mirroring the spinal motor output during locomotion. Thus, the activity of the motor cortical cells is shaped by the spinal pattern generator as they drive motor commands. These common features of CPG structure and function are suggested as offering a new perspective for building robotic systems. CPGs offer a potential for adaptive control, especially when combined with the principles of sensorimotor integration described here.
Experiments and models of sensorimotor interactions during locomotion
Biological Cybernetics, 2006
During locomotion sensory information from cutaneous and muscle receptors is continuously integrated with the locomotor central pattern generator (CPG) to generate an appropriate motor output to meet the demands of the environment. Sensory signals from peripheral receptors can strongly impact the timing and amplitude of locomotor activity. This sensory information is gated centrally depending on the state of the system (i.e., rest vs. locomotion) but is also modulated according to the phase of a given task. Consequently, if one is to devise biologically relevant walking models it is imperative that these sensorimotor interactions at the spinal level be incorporated into the control system.
2006
A computational model of the mammalian spinal cord circuitry incorporating a two-level central pattern generator (CPG) with separate half-centre rhythm generator (RG) and pattern formation (PF) networks has been developed from observations obtained during fictive locomotion in decerebrate cats. Sensory afferents have been incorporated in the model to study the effects of afferent stimulation on locomotor phase switching and step cycle period and on the firing patterns of flexor and extensor motoneurones. Here we show that this CPG structure can be integrated with reflex circuits to reproduce the reorganization of group I reflex pathways occurring during locomotion. During the extensor phase of fictive locomotion, activation of extensor muscle group I afferents increases extensor motoneurone activity and prolongs the extensor phase. This extensor phase prolongation may occur with or without a resetting of the locomotor cycle, which (according to the model) depends on the degree to which sensory input affects the RG and PF circuits, respectively. The same stimulation delivered during flexion produces a temporary resetting to extension without changing the timing of following locomotor cycles. The model reproduces this behaviour by suggesting that this sensory input influences the PF network without affecting the RG. The model also suggests that the different effects of flexor muscle nerve afferent stimulation observed experimentally (phase prolongation versus resetting) result from opposing influences of flexor group I and II afferents on the PF and RG circuits controlling the activity of flexor and extensor motoneurones. The results of modelling provide insights into proprioceptive control of locomotion.
LOCOMOTOR CONTROL: FROM SPRINGLIKE REACTIONS OF MUSCLES TO NEURAL PREDICTION
2000
The sensory control of mammalian locomotion has been studied for around 150 years. Many systems are involved: skeletomuscular actuators, spinal reflex and pattern generating networks, propriospinal and brainstem networks, the vestibular apparatus, cerebellum, deep brain nuclei and the cerebral cortex. All of these systems are directly or indirectly affected by mechanical or sensory input related to the locomotor movements they help control. In this chapter we will argue that since locomotor movements vary tremendously according to task, terrain and context, sensory input is crucial in controlling them. Experimental results as well as control systems simulations will be used to show that sensory input is crucial for determining the timing of phase transitions and thus the cadence (cyclic frequency) of locomotion, as well as the relative scaling of muscle activation and thus the amplitude of locomotor movements. We will argue that stretch reflexes play a relatively minor role in this scheme, basically augmenting the load compensation that occurs by virtue of the intrinsic compliance characteristics of skeletal muscle. With the help of biomechanical models, we will show that in quadrupeds, a carefully constructed pattern of muscle activations can produce sustained locomotion over flat ground in the absence of sensory input. However, small variations in terrain, initial conditions, or biomechanical parameters can disrupt locomotor stability. The situation is more critical in bipedal locomotion, where sensory input is vital for stable step cycles. The main function of the huge flow of multimodal sensory information from limb mechanoreceptors to the CNS is therefore continuously to adapt the locomotor pattern to variations in terrain and posture and to mediate higher level prediction of requirements in upcoming step cycles. Sensory systems must therefore be considered as integral parts of the semi-autonomous locomotor pattern generator. Taking the broad view, at least five levels of locomotor control can therefore be identified: load compensation due to skelotomuscular properties, load compensation due to stretch reflexes, bodily motion resulting from cyclical pattern generation and adaptive and predictive control in relation to terrain and to behavioural goals and contexts.
The sensory control of mammalian locomotion has been studied for around 150 years. Many systems are involved: skeletomuscular actuators, spinal reflex and pattern generating networks, propriospinal and brainstem networks, the vestibular apparatus, cerebellum, deep brain nuclei and the cerebral cortex. All of these systems are directly or indirectly affected by mechanical or sensory input related to the locomotor movements they help control. In this chapter we will argue that since locomotor movements vary tremendously according to task, terrain and context, sensory input is crucial in controlling them. Experimental results as well as control systems simulations will be used to show that sensory input is crucial for determining the timing of phase transitions and thus the cadence (cyclic frequency) of locomotion, as well as the relative scaling of muscle activation and thus the amplitude of locomotor movements. We will argue that stretch reflexes play a relatively minor role in this scheme, basically augmenting the load compensation that occurs by virtue of the intrinsic compliance characteristics of skeletal muscle. With the help of biomechanical models, we will show that in quadrupeds, a carefully constructed pattern of muscle activations can produce sustained locomotion over flat ground in the absence of sensory input. However, small variations in terrain, initial conditions, or biomechanical parameters can disrupt locomotor stability. The situation is more critical in bipedal locomotion, where sensory input is vital for stable step cycles. The main function of the huge flow of multimodal sensory information from limb mechanoreceptors to the CNS is therefore continuously to adapt the locomotor pattern to variations in terrain and posture and to mediate higher level prediction of requirements in upcoming step cycles. Sensory systems must therefore be considered as integral parts of the semi-autonomous locomotor pattern generator. Taking the broad view, at least five levels of locomotor control can therefore be identified: load compensation due to skelotomuscular properties, load compensation due to stretch reflexes, bodily motion resulting from cyclical pattern generation and adaptive and predictive control in relation to terrain and to behavioural goals and contexts.
Afferent control of locomotor CPG: insights from a simple neuromechanical model
Annals of the New York Academy of Sciences, 2010
A simple neuromechanical model has been developed that describes a spinal central pattern generator (CPG) controlling the locomotor movement of a single-joint limb via activation of two antagonist (flexor and extensor) muscles. The limb performs rhythmic movements under control of the muscular, gravitational and ground reaction forces. Muscle afferents provide length-dependent (types Ia and II) and force-dependent (type Ib from the extensor) feedback to the CPG. We show that afferent feedback adjusts CPG operation to the kinematics and dynamics of the limb providing stable "locomotion." Increasing the supraspinal drive to the CPG increases locomotion speed by reducing the duration of stance phase. We show that such asymmetric, extensor-dominated control of locomotor speed (with relatively constant swing duration) is provided by afferent feedback independent of the asymmetric rhythmic pattern generated by the CPG alone (in "fictive locomotion" conditions). Finally, we demonstrate the possibility of reestablishing stable locomotion after removal of the supraspinal drive (associated with spinal cord injury) by increasing the weights of afferent inputs to the CPG, which is thought to occur following locomotor training.
Control of Locomotor Cycle Durations
Journal of Neurophysiology, 2005
In intact animals and humans, increases in locomotor speed are usually associated with decreases in step cycle duration. Most data indicate that the locomotor central pattern generator (CPG) shortens cycle duration mainly by shortening the durations of extensor rather than flexor phases of the step cycle. Here we report that in fictive locomotion elicited by electrical stimulation of the midbrain locomotor region (MLR) in the cat, spontaneous variations in cycle duration were due more to changes in flexor rather than extensor phase durations in 22 of 31 experiments. The locomotor CPG is therefore not inherently extensor-or flexor-biased. We coined the term "dominant" to designate the phase (flexion or extension) showing the larger variation. In a simple half-center oscillator model, experimental phase duration plots were fitted well by adjusting two parameters that corresponded to background drive ("bias") and sensitivity ("gain") of the oscillator's timing elements. 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Sensory Control of Locomotion: Reflexes Versus Higher-Level Control
Advances in Experimental Medicine and Biology, 2002
In the absence of sensory input, the central nervous system can generate a rhythmical pattern of coordinated activation of limb muscles. Contracting muscles have spring-like properties. If synergistic muscles are co-activated in the right way, sustained locomotion can occur. What is the role of sensory input in this scheme? In this chapter we first discuss the implications of positive force feedback control in hindlimb extensor reflexes in the cat. We then raise the question of whether the sensory-evoked responses, which are modest in size and quite delayed in the stance phase, contribute to any significant extent. A locomotor model is used to show that when centrally generated activation levels are low, stretch reflexes can be crucial. However, when these levels are higher, stretch reflexes have a less dramatic role. The more important role for sensory input is probably in mediating higher level control decisions.
The mammalian central pattern generator for locomotion
Brain Research Reviews, 2009
At the beginning of the 20th century, Thomas Graham Brown conducted experiments that after a long hiatus changed views on the neural control of locomotion. His seminal work supported by subsequent evidence generated largely from the 1960s onwards showed that across species walking, flying, and swimming are controlled largely by a neuronal network that has been referred to as the central pattern generator (CPG) for locomotion. In mammals, this caudally localized spinal cord network was found to generate the basic command signals sent to muscles of the limbs for locomotor rhythm and pattern generation. This article constitutes a comprehensive review summarizing key findings on the organization and properties of this network.