Central pattern generator for swimming in Melibe

The nudibranch mollusc Melibe leonina swims by bending from side to side. We have identified a network of neurons that appears to constitute the central pattern generator (CPG) for this locomotor behavior, one of only a few such networks to be described in cellular detail. The network consists of two pairs of interneurons, termed `swim interneuron 1\u27 (sint1) and `swim interneuron 2\u27 (sint2), arranged around a plane of bilateral symmetry. Interneurons on one side of the brain, which includes the paired cerebral, pleural and pedal ganglia, coordinate bending movements toward the same side and communicate via non-rectifying electrical synapses. Interneurons on opposite sides of the brain coordinate antagonistic movements and communicate over mutually inhibitory synaptic pathways. Several criteria were used to identify members of the swim CPG, the most important being the ability to shift the phase of swimming behavior in a quantitative fashion by briefly altering the firing pattern of an individual neuron. Strong depolarization of any of the interneurons produces an ipsilateral swimming movement during which the several components of the motor act occur in sequence. Strong hyperpolarization causes swimming to stop and leaves the animal contracted to the opposite side for the duration of the hyperpolarization. The four swim interneurons make appropriate synaptic connections with motoneurons, exciting synergists and inhibiting antagonists. Finally, these are the only neurons that were found to have this set of properties in spite of concerted efforts to sample widely in the Melibe CNS. This led us to conclude that these four cells constitute the CPG for swimming. While sint1 and sint2 work together during swimming, they play different roles in the generation of other behaviors. Sint1 is normally silent when the animal is crawling on a surface but it depolarizes and begins to fire in strong bursts once the foot is dislodged and the animal begins to swim. Sint2 also fires in bursts during swimming, but it is not silent in non-swimming animals. Instead activity in sint2 is correlated with turning movements as the animal crawls on a surface. This suggests that the Melibe motor system is organized in a hierarchy and that the alternating movements characteristic of swimming emerge when activity in sint1 and sint2 is bound together

NeuroPod: a real-time neuromorphic spiking CPG applied to robotics

Initially, robots were developed with the aim of making our life easier, carrying out repetitive or dangerous tasks for humans. Although they were able to perform these tasks, the latest generation of robots are being designed to take a step further, by performing more complex tasks that have been carried out by smart animals or humans up to date. To this end, inspiration needs to be taken from biological examples. For instance, insects are able to optimally solve complex environment navigation problems, and many researchers have started to mimic how these insects behave. Recent interest in neuromorphic engineering has motivated us to present a real-time, neuromorphic, spike-based Central Pattern Generator of application in neurorobotics, using an arthropod-like robot. A Spiking Neural Network was designed and implemented on SpiNNaker. The network models a complex, online-change capable Central Pattern Generator which generates three gaits for a hexapod robot locomotion. Recon gurable hardware was used to manage both the motors of the robot and the real-time communication interface with the Spiking Neural Networks. Real-time measurements con rm the simulation results, and locomotion tests show that NeuroPod can perform the gaits without any balance loss or added delay.Ministerio de Economía y Competitividad TEC2016-77785-

Cooperative Dynamics of an Artificial Stochastic Resonant System

We have investigated cooperative dynamics of an artificial stochastic resonant system, which is a recurrent ring connection of neuron-like signal transducers (NST) based on stochastic resonance (SR), using electronic circuit experiments. The ring showed quasi-periodic, tunable oscillation driven by only noise. An oscillation coherently amplified by noise demonstrated that SR may lead to unusual oscillation features. Furthermore, we found that the ring showed synchronized oscillation in a chain network composed of multiple rings. Our results suggest that basic functions (oscillation and synchronization) that may be used in the central pattern generator of biological system are induced by collective integration of the NST element.Comment: 13 pages, 4 figure

Conditions for multi-functionality in a rhythm generating network inspired by turtle scratching

Rhythmic behaviors such as breathing, walking, and scratching are vital to many species. Such behaviors can emerge from groups of neurons, called central pattern generators, in the absence of rhythmic inputs. In vertebrates, the identification of the cells that constitute the central pattern generator for particular rhythmic behaviors is difficult, and often, its existence has only been inferred. For example, under experimental conditions, intact turtles generate several rhythmic scratch motor patterns corresponding to non-rhythmic stimulation of different body regions. These patterns feature alternating phases of motoneuron activation that occur repeatedly, with different patterns distinguished by the relative timing and duration of activity of hip extensor, hip flexor, and knee extensor motoneurons. While the central pattern generator network responsible for these outputs has not been located, there is hope to use motoneuron recordings to deduce its properties. To this end, this work presents a model of a previously proposed central pattern generator network and analyzes its capability to produce two distinct scratch rhythms from a single neuron pool, selected by different combinations of tonic drive parameters but with fixed strengths of connections within the network. We show through simulation that the proposed network can achieve the desired multi-functionality, even though it relies on hip unit generators to recruit appropriately timed knee extensor motoneuron activity, including a delay relative to hip activation in rostral scratch. Furthermore, we develop a phase space representation, focusing on the inputs to and the intrinsic slow variable of the knee extensor motoneuron, which we use to derive sufficient conditions for the network to realize each rhythm and which illustrates the role of a saddle-node bifurcation in achieving the knee extensor delay. This framework is harnessed to consider bistability and to make predictions about the responses of the scratch rhythms to input changes for future experimental testing