Title
Closed loop interactions between spiking neural network and robotic simulators based on MUSIC and ROS.
Abstract
In order to properly assess the function and computational properties of simulated neural systems, it is necessary to account for the nature of the stimuli that drive the system. However, providing stimuli that are rich and yet both reproducible and amenable to experimental manipulations is technically challenging, and even more so if a closed-loop scenario is required. In this work, we present a novel approach to solve this problem, connecting robotics and neural network simulators. We implement a middleware solution that bridges the Robotic Operating System (ROS) to the Multi-Simulator Coordinator (MUSIC). This enables any robotic and neural simulators that implement the corresponding interfaces to be efficiently coupled, allowing real-time performance for a wide range of configurations. This work extends the toolset available for researchers in both neurorobotics and computational neuroscience, and creates the opportunity to perform closed-loop experiments of arbitrary complexity to address questions in multiple areas, including embodiment, agency, and reinforcement learning.
Year
DOI
Venue
2016
10.3339/fninf.2016.00031
FRONTIERS IN NEUROINFORMATICS
Keywords
DocType
Volume
neural network simulations,robotic simulations,neurorobotics,closed-loop,real-time
Journal
10
Citations 
PageRank 
References 
1
0.37
16
Authors
4
Name
Order
Citations
PageRank
Philipp Weidel141.12
Mikael Djurfeldt229822.07
Renato Carlos Farinha Duarte350.81
Abigail Morrison476153.95