How is a spider's web a neural net? If we consider each fiber intersection as an entity, a (simple) neuron, then we can see that each fiber intersection is connected with other entities like itself, and each affects the state of the others, and is affected by the others. (When one moves, they all move--but in ways that reflect their relationship to one another.) In this example, the 'state' of the neurons corresponds to their position in space. Each kind of neural net (and there are many) will have a different definition of 'state' or 'behavior', but in every case, the behavior of one entity in the network will have an effect on the behavior of other entities within the net, with the strength of effect depending on proximity / strength of connections.
The neural net perspective on the spider's web helps us understand how the spider's filament was useful to the spider before it evolved into a fully developed web structure: As a single strand that was hung betwen blades of grass or laid on the ground, it served as an information conduit to the spider's brain about the position of an insect--life-sustaining food. Then evolution worked to elaborate on the phenomenon of a single-thread information conduit.
The spider's web as neural network: Each intersection of filaments is a point that is connected to other points like itself and each conveys information about its position to the other points that it is connected to, thus affecting their state, or what information they then transmit to their neighbors. A classic (and visible) example of a functioning neural net.
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