Is there a Liquid State Machine in the Bacterium Escherichia Coli?

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Abstract
The bacterium Escherichia coli has the capacity to respond to a wide range of environmental inputs, which have the potential to change suddenly and rapidly. Although the functions of many of its signal transduction and gene regulation networks have been identified, E.Coli's capacity for perceptual categorization, especially for discrimination between complex temporal patterns of chemical inputs, has been experimentally neglected. Real-time computations on time-varying inputs can be undertaken by a system possessing a high dimensional analog fading memory, i.e. a liquid-state machine (LSM). For example, the cortical microcolumn is hypothesized to be a LSM. A model of the gene regulation network (GRN) of E.Coli was assessed for its LSM properties for a range of increasingly complex stimuli. Cooperativity between transcription factors (TFs) is necessary for complex temporal discriminations. However, the low recurrence within the GRNs autonomous dynamics decreases its capacity for a rich fading memory, and hence for integrating temporal sequence information. We conclude that coupling of the GRN with signal transduction networks possessing cross-talk, and with metabolic networks is expected to increase the extent of non-autonomous recurrence and hence to facilitate enhanced LSM properties.