Intelligence without representation
Artificial Intelligence
Dynamical cell assembly hypothesis—theoretical possibility of spatio-temporal coding in the cortex
Neural Networks - 1996 Special issue: four major hypotheses in neuroscience
Classification as Sensory-Motor Coordination: A Case Study on Autonomous Agents
Proceedings of the Third European Conference on Advances in Artificial Life
Polychronization: Computation with Spikes
Neural Computation
Correlations and population dynamics in cortical networks
Neural Computation
Simple model of spiking neurons
IEEE Transactions on Neural Networks
Dynamic memory for robot control via delay neural networks
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
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This paper investigates the dynamical and control properties of a discrete spiking neural network model with axonal delays. After examining contemporary work on spike timing as a mechanism for neural coding, we introduce a simple axonal delay network model which, via coincidence detection, demonstrates the presence of biologically observed regimes such as sustained firing and the emergence of synchrony. We establish delay criteria allowing for the classification of three distinct regimes including global synchrony, complex firing, and dissipation. We then proceed to test this model in a robot light seeking task. Results show that evolving network delays is sufficient for solving the task. We conclude by hypothesizing that global synchronous firing is more suited to reactive behaviours while complex firing patterns may serve as an organizing mechanism for more indirect processing.