  Bacteria are easily characterizable model organisms with an impressively
complicated set of capabilities. Among their capabilities is quorum sensing, a
detailed cell-cell signaling system that may have a common origin with
eukaryotic cell-cell signaling. Not only are the two phenomena similar, but
quorum sensing, as is the case with any bacterial phenomenon when compared to
eukaryotes, is also easier to study in depth than eukaryotic cell-cell
signaling. This ease of study is a contrast to the only partially understood
cellular dynamics of neurons. Here we review the literature on the strikingly
neuron-like qualities of bacterial colonies and biofilms, including ion-based
and hormonal signaling, and action potential-like behavior. This allows them to
feasibly act as an analog for neurons that could produce more detailed and more
accurate biologically-based computational models. Using bacteria as the basis
for biologically feasible computational models may allow models to better
harness the tremendous ability of biological organisms to make decisions and
process information. Additionally, principles gleaned from bacterial function
have the potential to influence computational efforts divorced from biology,
just as neuronal function has in the abstract influenced countless machine
learning efforts.
