*** Excursus: Does sensory adaptation imply the occurrence of mental states?

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Case study: sensory adaptation in bacteria


Left: Franco di Primio. Photo courtesy of Fraunhofer Institute for Autonomous Intelligent Systems.
Right: Staph bacteria. Picture courtesy of Janice Carr/CDC via BBC.

Di Primio, Muller and Lengeler also cite a case of sensory adaptation as evidence of learning in bacteria:

Interestingly, when a suspension of stimulated bacteria is rapidly mixed with a solution containing no ... attractant ..., they first increase tumbling ... From the observer's point of view the above finding could also be interpreted as if the bacteria were "surprised" about the disappearance of the attractant they were first following and the ... tumbling could be a sign of them "expecting" it (while "looking around") to reappear. After a while (we could say, because they "notice" that there is no advantage in doing so), they resume the normal unbiased run-tumble rhythm (2000, pp. 6 - 7).

However, the chemical basis of this adaptation is well understood. The presence of an attractant activates a chemical sensor which causes the cell's motor to "run" toward the attractant, while immediate removal of the attractant generates unco-ordinated motion or cell tumbling. In the meantime, a gradual "demethylation" process (which takes several minutes) switches the sensors and causes the cell to return to its usual run-tumble rhythm (Di Primio, Muller and Lengeler, 2000, p. 7).

The point I wish to make here is not that a chemical explanation precludes a mentalistic one. Rather, the point is that if we are to adopt a mentalistic account, it has to do some extra scientific explanatory "work" which a chemical account cannot do.

A further reason for rejecting a mentalistic explanation here is that the bacteria's behaviour conforms to a fixed pattern, as defined in the previous section, and as such, does not warrant the ascription of cognitive mental states (Conclusion F.2). Roughly, the direction of the bacteria's motion is a function of the recent changes in the concentration of the attractant and the rate of demethylation of the sensors. To represent this mathematically, we need three variables: the current concentration of attractant; the last measurement, made 3 seconds ago (a time-lag variable); and the rate of demethylation.

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*** SUMMARY of Conclusions reached References