How Everything is Connected

A complex network is a framework for studying the ways things are connected together. A network is a set of dots and lines, where dots are things (e.g. people) and lines represent relationships between pairs of dots (e.g. a friendship between two people). Some networks change over time, either by adding new lines (really called edges) between existing dots (really called nodes), or by adding new nodes along with new edges. Networks can also have weighted edges, so instead of a relationship just existing or not, it can be quantified with some value (e.g. value in dollars of exports between countries).

Neural systems can be regarded as networks, where the nodes are the neurons and the edges are synaptic connections. These edges can be weighted, reflecting the different effectiveness of communication between some pairs of neurons. These weights change depending on the activity of the neurons. I use dynamics to study how networks of neurons change while learning.

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