Concept
Percolation (from the Latin word percolatio, meaning filtration) is a theoretical model used to understand the way activation and diffusion of neural activity occurs within neural networks. Percolation is a model used to explain how neural activity is transmitted across the various connections within the brain. Percolation theory can be easily understood by explaining its use in epidemiology. Individuals whom are infected with a disease can spread the disease through contact with others in their social network. Those who are more social and come into contact with more people will help to propagate the disease quicker than those who are less social. Factors such as occupation and sociability influence the rate of infection. Now, if one were to think of neurons as individuals and synaptic connections as the social bonds between people, then one can determine how easily messages between neurons will spread. When a neuron fires, the message is transmitted along all synaptic connections to other neurons until it can no longer continue. Synaptic connections are considered either open or closed (like a social or unsocial person) and messages will flow along any and all open connections until they can go no further. Just like occupation and sociability play a key role in the spread of disease, so too do the number of neurons, synaptic plasticity and long-term potentiation when talking about neural percolation. A key aspect of percolation is the concept of percolating clusters, which are single large groups of neurons that are all connected by open bonds and take up the majority of the network. Any signals that originate at any point within the percolating cluster will have a greater impact and diffusion across the network than signals that originate outside of the cluster. This is similar to a teacher spreading an infection to a whole community through contact with the students and subsequently with the families than an isolated businessman that works from home.