A SpiNNaker Application: Design, Implementation and Validation of SCPGs

In this paper, we present the numerical results of the implementation of a Spiking Central Pattern Generator (SCPG) on a SpiNNaker board. The SCPG is a network of current-based leaky integrateand- fire (LIF) neurons, which generates periodic spike trains that correspond to different locomotion gaits (i.e. walk, trot, run). To generate such patterns, the SCPG has been configured with different topologies, and its parameters have been experimentally estimated. To validate our designs, we have implemented them on the SpiNNaker board using PyNN and we have embedded it on a hexapod robot. The system includes a Dynamic Vision Sensor system able to command a pattern to the robot depending on the frequency of the events fired. The more activity the DVS produces, the faster that the pattern that is commanded will be.Ministerio de Economía y Competitividad TEC2016-77785-

Live Demonstration: neuromorphic robotics, from audio to locomotion through spiking CPG on SpiNNaker.

This live demonstration presents an audio-guided neuromorphic robot: from a Neuromorphic Auditory Sensor (NAS) to locomotion using Spiking Central Pattern Generators (sCPGs). Several gaits are generated by sCPGs implemented on a SpiNNaker board. The output of these sCPGs is sent in a real-time manner to an Field Programmable Gate Array (FPGA) board using an AER-to-SpiNN interface. The control of the hexapod robot joints is performed by the FPGA board. The robot behavior can be changed in real-time by means of the NAS. The audio information is sent to the SpiNNaker board which classifies it using a Spiking Neural Network (SNN). Thus, the input sound will activate a specific gait pattern which will eventually modify the behavior of the robot.Ministerio de Economía y Competitividad TEC2016-77785-

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-

Spiking Central Pattern Generators through Reverse Engineering of Locomotion Patterns

In robotics, there have been proposed methods for locomotion of nonwheeled robots based on artificial neural networks; those built with plausible neurons are called spiking central pattern generators (SCPGs). In this chapter, we present a generalization of reported deterministic and stochastic reverse engineering methods for automatically designing SCPG for legged robots locomotion systems; such methods create a spiking neural network capable of endogenously and periodically replicating one or several rhythmic signal sets, when a spiking neuron model and one or more locomotion gaits are given as inputs. Designed SCPGs have been implemented in different robotic controllers for a variety of robotic platforms. Finally, some aspects to improve and/or complement these SCPG-based locomotion systems are pointed out

Modulation of swimming in the gastropod Melibe leonina by nitric oxide

Nitric oxide (NO) is a gaseous intercellular messenger produced by the enzyme nitric oxide synthase. It has been implicated as a neuromodulator in several groups of animals, including gastropods, crustaceans and mammals. In this study, we investigated the effects of NO on the swim motor program produced by isolated brains and by semi-intact preparations of the nudibranch Melibe leonina. The NO donors sodium nitroprusside (SNP, 1 mmol l–1) and S-nitroso-N-acetylpenicillamine (SNAP, 1 mmol l–1) both had a marked effect on the swim motor program expressed in isolated brains, causing an increase in the period of the swim cycle and a more erratic swim rhythm. In semi-intact preparations, the effect of NO donors was manifested as a significant decrease in the rate of actual swimming. An NO scavenger, reduced oxyhemoglobin, eliminated the effects of NO donors on isolated brains, supporting the assumption that the changes in swimming induced by donors were actually due to NO. The cGMP analogue 8-bromoguanosine 3′,5′-cyclic monophosphate (1 mmol l–1) produced effects that mimicked those of NO donors, suggesting that NO is working via a cGMP-dependent mechanism. These results, in combination with previous histological studies indicating the endogenous presence of nitric oxide synthase, suggest that NO is used in the central nervous system of Melibe leonina to modulate swimming

Neural Correlates of Swimming Behavior in Melibe leonina

The nudibranch Melibe leonina swims by rhythmically bending from side to side at a frequency of 1 cycle every 2–4 s. The objective of this study was to locate putative swim motoneurons (pSMNs) that drive these lateral flexions and determine if swimming in this species is produced by a swim central pattern generator (sCPG). In the first set of experiments, intracellular recordings were obtained from pSMNs in semi-intact, swimming animals. About 10–14 pSMNs were identified on the dorsal surface of each pedal ganglion and 4–7 on the ventral side. In general, the pSMNs in a given pedal ganglion fired synchronously and caused the animal to flex in that direction, whereas the pSMNs in the opposite pedal ganglion fired in anti-phase. When swimming stopped, so did rhythmic pSMN bursting; when swimming commenced, pSMNs resumed bursting. In the second series of experiments, intracellular recordings were obtained from pSMNs in isolated brains that spontaneously expressed the swim motor program. The pattern of activity recorded from pSMNs in isolated brains was very similar to the bursting pattern obtained from the same pSMNs in semi-intact animals, indicating that the sCPG can produce the swim rhythm in the absence of sensory feedback. Exposing the brain to light or cutting the pedal-pedal connectives inhibited fictive swimming in the isolated brain. The pSMNs do not appear to participate in the sCPG. Rather, they received rhythmic excitatory and inhibitory synaptic input from interneurons that probably comprise the sCPG circuit

Effectiveness of an amygdala and insula retraining program combined with mindfulness training to improve the quality of life in patients with long COVID: a randomized controlled trial protocol

Background: There has been growing clinical awareness in recent years of the long-term physical and psychological consequences of the SARS-CoV-2 virus, known as Long COVID. The prevalence of Long COVID is approximately 10% of those infected by the virus. Long COVID is associated with physical and neuropsychological symptoms, including those related to mental health, psychological wellbeing, and cognition. However, research on psychological interventions is still in its early stages, in which means that available results are still limited. The main objective of this study is to evaluate the effects of a program based on amygdala and insula retraining (AIR) combined with mindfulness training (AIR + Mindfulness) on the improvement of quality of life, psychological well-being, and cognition in patients with Long COVID. Methods: This study protocol presents a single-blind randomized controlled trial (RCT) that encompasses baseline, post-treatment, and six-month follow-up assessment time points. A total of 100 patients diagnosed with Long COVID by the Spanish National Health Service will be randomly assigned to either AIR + Mindfulness (n = 50) or relaxation intervention (n = 50), the latter as a control group. The primary outcome will be quality of life assessed using the Short Form-36 Health Survey (SF-36). Additional outcomes such as fatigue, pain, anxiety, memory, and sleep quality will also be evaluated. Mixed effects regression models will be used to estimate the effectiveness of the program, and effect size calculations will be made. Discussion: Long COVID syndrome is a clinical condition characterized by the persistence of symptoms for at least 12 weeks after the onset of COVID-19 that significantly affects people’s quality of life. This will be the first RCT conducted in Spain to apply a psychotherapy program for the management of symptoms derived from Long COVID. Positive results from this RCT may have a significant impact on the clinical context by confirming the beneficial effect of the intervention program being evaluated on improving the symptoms of Long COVID syndrome and aiding the development of better action strategies for these patients. Trial registration: Clinical Trials.gov NCT05956405