Methods in neuronal modeling: From synapses to networks
Methods in neuronal modeling: From synapses to networks
The cascade-correlation learning architecture
Advances in neural information processing systems 2
Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
Introduction to Multiagent Systems
Introduction to Multiagent Systems
Evolving neural networks through augmenting topologies
Evolutionary Computation
A self-organising network that grows when required
Neural Networks - New developments in self-organizing maps
The AMAS theory for complex problem solving based on self-organizing cooperative agents
WETICE '03 Proceedings of the Twelfth International Workshop on Enabling Technologies: Infrastructure for Collaborative Enterprises
Efficient evolution of neural networks through complexification
Efficient evolution of neural networks through complexification
Experiences creating three implementations of the repast agent modeling toolkit
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems
Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems
Evolutionary Function Approximation for Reinforcement Learning
The Journal of Machine Learning Research
A multi-agent system for building dynamic ontologies
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Engineering Self-modeling Systems: Application to Biology
Engineering Societies in the Agents World IX
WI-IAT '11 Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Volume 02
Topology preservation in self-organizing feature maps: exact definition and measurement
IEEE Transactions on Neural Networks
A self-adaptive multi-agent system for abnormal behavior detection in maritime surveillance
KES-AMSTA'12 Proceedings of the 6th KES international conference on Agent and Multi-Agent Systems: technologies and applications
Threshold-Crossing model of human motoneuron
ITIB'12 Proceedings of the Third international conference on Information Technologies in Biomedicine
Adaptive reservoir computing through evolution and learning
Neurocomputing
Simulating Human Single Motor Units Using Self-Organizing Agents
SASO '12 Proceedings of the 2012 IEEE Sixth International Conference on Self-Adaptive and Self-Organizing Systems
Collective Self-Tuning for Complex Product Design
SASO '12 Proceedings of the 2012 IEEE Sixth International Conference on Self-Adaptive and Self-Organizing Systems
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We present a novel computational model that detects temporal configurations of a given human neuronal pathway and constructs its artificial replication. This poses a great challenge since direct recordings from individual neurons are impossible in the human central nervous system and therefore the underlying neuronal pathway has to be considered as a black box. For tackling this challenge, we used a branch of complex systems modeling called artificial self-organization in which large sets of software entities interacting locally give rise to bottom-up collective behaviors. The result is an emergent model where each software entity represents an integrate-and-fire neuron. We then applied the model to the reflex responses of single motor units obtained from conscious human subjects. Experimental results show that the model recovers functionality of real human neuronal pathways by comparing it to appropriate surrogate data. What makes the model promising is the fact that, to the best of our knowledge, it is the first realistic model to self-wire an artificial neuronal network by efficiently combining neuroscience with artificial self-organization. Although there is no evidence yet of the model's connectivity mapping onto the human connectivity, we anticipate this model will help neuroscientists to learn much more about human neuronal networks, and could also be used for predicting hypotheses to lead future experiments.