Central Pattern Generator Neural Network Research Articles

Central pattern generator network model for the alternating hind limb gait of rats based on the modified Van der Pol equation.

Herein, we employed a central pattern generator (CPG), a spinal cord neural network that regulates lower-limb gait during intra-spinal micro-stimulation (ISMS). Particularly, ISMS was used to determine the spatial distribution pattern of CPG sites in the spinal cord and the signal regulation pattern that induced the CPG network to produce coordinated actions. Based on the oscillation phenomenon of the single CPG neurons of Van der Pol (VDP) oscillators, a double-cell CPG neural network model was constructed to realise double lower limbs, six-joint modelling, the simulation of 12 neural circuits, the CPG loci characterising stimuli-inducing alternating movements and changes in polarity stimulation signals in rat hindlimbs, and leg-state change movements. The feasibility and effectiveness of the CPG neural network were verified by recording the electromyographic burst-release mode of the flexor and extensor muscles of the knee joints during CPG electrical stimulation. The results revealed that the output pattern of the CPG presented stable rhythm and coordination characteristics. The 12-neuron CPG model based on the improved VDP equation realised single-point control while significantly reducing the number of stimulation electrodes in the gait training of spinal cord injury patients. We believe that this study advances motor function recovery in rehabilitation medicine.

Gait regulation using monopolar intraspinal micro-stimulation of spinal cord central pattern generator: New insights for improving Hodgkin–Huxley model

Restoring the motor function of paralyzed limbs has always been an important aim in the field of biomedical engineering. In view of the discovery of the repeatable experimental phenomenon that positive and negative stimulation pulses applied to specific points, identified as central pattern generator (CPG) sites, could induce switching of the movement patterns of bilateral hindlimbs, an improved Hodgkin–Huxley (HH) neuron model was established by introducing the electric field effect principle. A CPG neural network model comprising 12 neural units in six joints of the bilateral hindlimbs was modeled. The simulation results showed the alternating movement patterns of the bilateral hindlimbs through the action potential release of extensor and flexor neurons. The explosive electromyogram of the gastrocnemius (GM) and quadriceps femoris (QF) when stimulating the CPG sites with intraspinal micro-stimulation (ISMS) was consistent with the action potential diagram of the flexor and extensor neurons obtained via simulation. Our research considers the neural network model of electric field radiation, which can facilitate a deep understanding of the dynamic characteristics of neurons in the electric field environment, and verifies the correlation between the location of CPG sites, stimulus polarity and movement patterns to induce alternating left–right coordinated movements.

On a CPG-Based Hexapod Robot: AmphiHex-II With Variable Stiffness Legs

Amphibious robots have attracted more and more attention from researchers for their broad applications, while it also brings great challenges in designing appropriate propulsion mechanisms and effective control algorithms. In this paper, we reported a newly designed amphibious hexapod robot-AmphiHex-II. This robot possesses six newly designed variable stiffness legs for adapting various complex environments. This novel design of the variable stiffness leg seamlessly incorporates the advantages of both semicircular walking legs and the swimming flexible flippers. The legs are constructed by rigid fan-shaped frames, which work as walking legs for terrestrial locomotion and protect the contained flexible flippers used for aquatic locomotion during terrestrial operations. The stiffness of legs can be adjusted to an effective degree by adjusting the positions of sliders manually. The effect of variable stiffness on locomotion performance was experimentally investigated. Moreover, in order to achieve a smooth and quick gait transition, a central pattern generator neural network was introduced to control the system. Different gait generation strategies on land and underwater were demonstrated. A series of field experiments were carried out to evaluate locomotion performance of the AmphiHex-II for terrestrial and aquatic mobility, and the results demonstrate the advantages of the novel leg design and the control system.

A Bio-Inspired Control Strategy for Locomotion of a Quadruped Robot

In order to effectively plan the robot gaits and foot workspace trajectory (WT) synchronously, a novel biologically inspired control strategy for the locomotion of a quadruped robot based on central pattern generator—neural network—workspace trajectory (CPG-NN-WT) is presented in this paper. Firstly, a foot WT is planned via the Denavit-Hartenberg (D-H) notation and the inverse kinematics, which has the advantages of low mechanical shock, smooth movement, and sleek trajectory. Then, an improved central pattern generator (CPG) based on Hopf oscillators is proposed in this paper for smooth gait planning. Finally, a neural network is designed and trained to convert the CPG output to the preplanned WT, which can make full use of the advantages of the CPG-based method in gait planning and the WT-based method in foot trajectory planning simultaneously. Furthermore, virtual prototype simulations and experiments with a real quadruped robot are presented to validate the effectiveness of the proposed control strategy. The results show that the gait of the quadruped robot can be controlled easily and effectively by the CPG with its internal parameters; meanwhile, the foot trajectory meets the preplanned WT well.

Spinal Locomotor Circuits Develop Using Hierarchical Rules Based on Motorneuron Position and Identity

The coordination of multi-muscle movements originates in the circuitry that regulates the firing patterns of spinal motorneurons. Sensory neurons rely on the musculotopic organization of motorneurons to establish orderly connections, prompting us to examine whether the intraspinal circuitry that coordinates motor activity likewise uses cell position as an internal wiring reference. We generated a motorneuron-specific GCaMP6f mouse line and employed two-photon imaging to monitor the activity of lumbar motorneurons. We show that the central pattern generator neural network coordinately drives rhythmic columnar-specific motorneuron bursts at distinct phases of the locomotor cycle. Using multiple genetic strategies to perturb the subtype identity and orderly position of motorneurons, we found that neurons retained their rhythmic activity-but cell position was decoupled from the normal phasing pattern underlying flexion and extension. These findings suggest a hierarchical basis of motor circuit formation that relies on increasingly stringent matching of neuronal identity and position.

Optical Imaging of Neurons in the Crab Stomatogastric Ganglion with Voltage-sensitive Dyes

Voltage-sensitive dye imaging of neurons is a key methodology for the understanding of how neuronal networks are organised and how the simultaneous activity of participating neurons leads to the emergence of the integral functionality of the network. Here we present the methodology of application of this technique to identified pattern generating neurons in the crab stomatogastric ganglion. We demonstrate the loading of these neurons with the fluorescent voltage-sensitive dye Di-8-ANEPPQ and we show how to image the activity of dye loaded neurons using the MiCAM02 high speed and high resolution CCD camera imaging system. We demonstrate the analysis of the recorded imaging data using the BVAna imaging software associated with the MiCAM02 imaging system. The simultaneous voltage-sensitive dye imaging of the detailed activity of multiple neurons in the crab stomatogastric ganglion applied together with traditional electrophysiology techniques (intracellular and extracellular recordings) opens radically new opportunities for the understanding of how central pattern generator neural networks work.

Optical Imaging of Neurons in the Crab Stomatogastric Ganglion with Voltage-sensitive Dyes

Voltage-sensitive dye imaging of neurons is a key methodology for the understanding of how neuronal networks are organised and how the simultaneous activity of participating neurons leads to the emergence of the integral functionality of the network. Here we present the methodology of application of this technique to identified pattern generating neurons in the crab stomatogastric ganglion. We demonstrate the loading of these neurons with the fluorescent voltage-sensitive dye Di-8-ANEPPQ and we show how to image the activity of dye loaded neurons using the MiCAM02 high speed and high resolution CCD camera imaging system. We demonstrate the analysis of the recorded imaging data using the BVAna imaging software associated with the MiCAM02 imaging system. The simultaneous voltage-sensitive dye imaging of the detailed activity of multiple neurons in the crab stomatogastric ganglion applied together with traditional electrophysiology techniques (intracellular and extracellular recordings) opens radically new opportunities for the understanding of how central pattern generator neural networks work.