Solving graph algorithms with networks of spiking neurons
Related Experiment Video
Updated: Jul 7, 2026

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
Published on: March 2, 2015
Abstract:
Spatio-temporal coding that combines spatial constraints with temporal sequencing is of great interest to brain-like circuit modelers. In this paper we present some new ideas of how these types of circuits can self-organize. We introduce a temporal correlation rule based on the time difference between the firings of neurons.With the aid of this rule we show an analogy between a graph and a network of spiking neurons. The shortest path, clustering based on the nearest neighbor, and the minimal spanning tree algorithms are solved using the proposed approach.
Related Concept Videos
Neural Circuits
Neuronal pools are collections of nerve cells with similar functions and interact through chemical and electrical signals. These pools include both interneurons (the central neural circuit nodes that...
The Role of Ion Channels in Neuronal Computation
Sometimes a single EPSP is strong enough to induce an action potential in the postsynaptic neuron. However, multiple presynaptic inputs must often create EPSPs around the same time for the postsynaptic neuron to be sufficiently depolarized to fire an action potential.
Neurons: The Axon
The axon attaches to the cell body at a cone-shaped elevation called the axon hillock. The initial part of the axon, closest to the hillock, is known as the initial segment.
Neuronal Communication
Electrical Synapses
Gap junctions allow the current to pass directly from one cell to the next. In contrast, in the chemical synapse, the neurotransmitters carry the information through the synaptic cleft from one neuron to the next. They consist of two...
Network Function of a Circuit
