This paper critically examines Shagrir’s semantic view of computation according to which representational contents play an indispensable individuative role for vehicles of computation. I show that attempting to use representational contents to individuate vehicles of computation may lead to incoherent computational descriptions. I use an illustrative case-study – locust looming-object avoidance behaviour. A crucial component of the mechanism underlying this phenomenon is the lobula giant motion detector (LGMD) neuron, which multiplies angular velocity of an approaching stimulus with the negative angular size of the same. I show that interpreting the computation performed by the LGMD in semantic terms is exceedingly difficult. The representational contents of the outputs are not related to the representational contents of the inputs by the mathematical operation proposed by the model. The representational contents of the outputs do not individuate the vehicles of computation – these seem to be determined by the prevailing disciplinary norms (membrane voltages, instant firing rates). Furthermore, the representational content ascribed to one of the inputs seems to be unavailable for at least one of the functionally relevant class of stimuli (disconnected sequentially appearing dots). Thus, the utility, or even practicability, of semantically individuating the computation performed by the LGMD is questionable.