Simulation Tool for Asynchronous Cortical Streams (STACS): Interfacing with Spiking Neural Networks
Author(s) -
Felix Wang
Publication year - 2015
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2015.09.149
Subject(s) - interfacing , computer science , asynchronous communication , spiking neural network , artificial neural network , adaptation (eye) , distributed computing , artificial intelligence , neuroscience , computer network , computer hardware , biology
We present a Simulation Tool for Asynchronous Cortical Streams (STACS) for studying spiking neural networks exhibiting adaptation in a closed-loop system. The goal is to develop a more complete understanding of the emergent behaviors at the network level, and attention is given to methods of analysis at this scale. In particular, STACS facilitates the development of network level metrics of spiking activity. At the same time, emphasis is placed on biologically faithful models of spiking and plasticity with respect to the underlying neural substrate. The essential component, however, is the ability of the neural system in interfacing with the environment. This is because behaviors such as learning and adaptation are inherently closed-loop processes that involve the interaction between an intelligent agent and its environment, here, embodied cognition. To this end, STACS utilizes a portable communication protocol, YARP, for interfacing and interacting with a wide range of external devices, both sensory and motor, as well as the ability to create user-defined methods. In doing so, we may capture and respond to real world input to a neural network, simulating experimentation of live cortical cultures such as on multielectrode arrays
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