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Shea describes 'vehicles' as 'individuable physical particulars that bear contents and whose causal interactions explain behaviour' (p15). In this context, I assume this means groups of neurons representing something. Examples of vehicles would be the fusiform face area (FFA) representing faces or MT representing motion.

Given how strict Shea is in defining representation elsewhere, it is surprising how lax he seems to be in ascribing the term 'representation' to cortical areas.

Two of the examples covered in these pages are relevant to thinking about how a group of neurons contribute (or not) to perception. Hence (I not sure about this...), Shea's argument would that these are (or are not) vehicles with representational content. Both examples are about ambiguous stimuli, i.e. ones where the external stimulus is the same but the perception can alter radically.

  • Behaviour and a single neuron. This page considers evidence that the firing rate of a single neuron (or cortical column) could affect an animal's perception and choice. But there are many instances (in fact, most) in which it would not. The page discusses the idea that what matters is whether the firing of this neuron (or cortical column of neurons) tips the feature vector, [math]\vec{r}[/math], from one recognised context (voronoi cell) to another. This is a rather different argument, I think, from saying that this neuron is (or these neurons are) a vehicle of representation. It would be good to discuss this.
  • Finding a sensitive neuron. This page describes a really relevant example. A neuron is sensitive to the binocular disparity (depth) of a point in the scene. Without changing the retinal stimulus, the participant's perception is either predictable from the neuron's response (so it seems like a 'vehicle') or not. It is as if in one instance the participant is 'listening' to the neuron whereas in the other it is ignored. The important point here, which makes it a good example to discuss, is that nothing in the outside world changes, the firing rates stay the same, they vary with the outside world appropriately, it is only the perception of the observer (due to other neurons outside this column or vehicle) that changes.

Comments from Nick

Back to notes on Shea (2018).