Back in the beginning of 2017, we had a great NRP Hackathon @FZI in Karlsruhe, where Alexander Kroner (SP4) presented his deep learning model for computing visual saliency.
We now presented this integration at the Human Brain Summit 2017 in Glasgow as a collaboration in CDP4 – visuo-motor integration. During this presentation we also shown how to integrate any deep learning models in the Neurorobotics Platform, as was already presented in the Young Researcher Event by Kenny Sharma.
We will continue this collaboration with SP4 by connecting the saliency model to eye movements and memory modules.
The goal of this project is to uncover the functional role of proprioceptive sensorimotor circuits in motor control, and to understand how their recruitment through electrical stimulation can elicit treadmill locomotion in the absence of brain inputs. This understanding is pivotal for the translation of experimental spinal cord stimulation therapies into a viable clinical application.
To this aim, we developed a closed loop neuromusculoskeletal model that encompass a spiking neural network of the muscle spindle pathway of two antagonist muscles, a musculoskeletal model of the mouse hindlimb, and a model of epidural electrical stimulation (Figure 1). The network includes alpha motoneurons, Ia inhibitory interneurons, group II excitatory interneurons, and group Ia and group II afferent fibers. The number of cells, the connectivity, and the firing behavior of alpha motor neurons was tuned according to experimental values found in literature. The effect of epidural electrical stimulation was integrated in the neuronal network by modelling every stimulation pulse as a supra threshold synaptic input in all the cells recruited by the stimulation. An experimentally validated FEM model of the lumbar rat spinal cord was used to compute the percentage of fibers recruited by the stimulation.
Closed loop simulations were performed by using the firing rates of the motoneurons populations as a signal to control the muscles activity of the musculoskeletal model, while using the muscles length information coming from the musculoskeletal model to estimate the firing rates of the neural network afferent fibers. In particular, the firing rates of Ia and II afferent fibers were estimated using an experimentally derived muscles spindle model.
The preliminary results show that muscle spindle feedback circuits alone can produce alternated movements typical of locomotion, when biomechanics and gravity are considered.
Current work is being performed in order to expand the modeled muscle spindle circuitry to control all the main hindlimb muscles together. To this purpose, the developed network will be used as a template for every couple of antagonist muscles and heteronymous connections across the different joints will be implemented. With this complete model of the hindlimb muscle spindle circuitry we will be able to assess whether this single sensorimotor pathway is sufficient to produce treadmill locomotion in combination with EES, or whether other spinal neural networks are necessarily involved.
Figure 1 : Closed loop simulation framework of Spinal Cord model and rodent hind limb to study epidural electrical stimulation
- Emanuele Formento (PhD, TNE & G-Lab, EPFL)
- Shravan Tata Ramalingasetty (PhD, BioRob, EPFL)
Venue: FZI, Karlsruhe, Germany
Thanks to all of the 17 participants for making this workshop a great time.
Last week, we held a successful Neurorobotics Platform (NRP) User Workshop in FZI, Karlsruhe. We welcomed 17 attendants over three days, coming from various sub-projects (such as Martin Pearson, SP3) and HBP outsiders (Carmen Peláez-Moreno and Francisco José Valverde Albacete). We focused on hands-on sessions so that users got comfortable using the NRP themselves.
Thanks to our live boot image with the NRP pre-installed, even users who did not follow the local installation steps beforehand could run the platform locally in no time. During the first day, we provided a tutorial experiment, exclusively developed for the event, which walked the users through the many features of the NRP. This tutorial experiment is inspired from the baby playing ping pong video, which is here simulated with an iCub robot. This tutorial experiment will soon get released with the official build of the platform.
On the second and third days, more freedom was given to the users so that they could implement their own experiments. We had short hands-on sessions on the Robot Designer as well as Virtual Coach, for offline optimization and analysis. Many new experiments were successfully integrated into the platform: the Miro robot from Consequential Robotics, a snake-like robot moving with Central Patterns Generators (CPG), revival of the Lauron experiment, …
We received great feedback from the users. We are looking forward for the organization of the next NRP User Workshop!
On 11th March we had the honor of welcoming Terrence Stewart from the University of Waterloo (http://compneuro.uwaterloo.ca/people/terrence-c-stewart.html) at the Technical University of Munich. During these two days, he first gave a fascinating presentation on Nengo and neural engineering in general.
This was followed by extensive discussions with our developers to investigate a possible integration of Nengo into our platform after it had been installed on his laptop. To this extent, we discussed what overlaps already exist and identified missing parts to make this integration happen.
This yields the opportunity for our NRP to offer additional spiking neuron simulators aside from NEST.
This collaboration would be benefitial for both sides, with us offereing a platform to interface Nengo with Roboy or other muscle based simulations.