One of the most common ways to understand the interrelation of distributed neurons is in terms of neural networks, which display many of the most important features of complex adaptive systems. Neural nets are made of nodes, which receive, transmit, and send signals. When numerus nodes are connected, complex behavior becomes virtually inevitable. “The function of the net,” Terence Deacon explains, “is determined by the global patterning of signals from output nodes with respect to patterns presented to input nodes. These input-pattern-to-output-pattern relationships are thus mediated via the patterning of signals distributed through web of interconnections that link output to input nodes, by way of the intervening hidden nodes, and not by the state or activity of any individual node.” When understood in this way, the brain is a global network made up of multiple micro- or local-area networks, which are constantly emerging changing. The relation of the brain’s neurons, axons, and dendrites is analogous to nodes joined in nets through which electrical impulses circulate. The brain, like the world in which it is enmeshed, then, operates according to network logic. Changes in the structure and function of the brain result both from the coadaptation of neural networks within the brain and from the coadaptation between the brain and its environment.
As a result of its coadaptive capacity, the brain is not hardwired but, like all complex networks, functions between fixity and flux. The constraints facilitating brain functions and mental activity are not completely predetermined but change in relation to other physical, chemical, and biological processes.