 (relative to its centre). To see this, keep fixating on your closer finger. Close one eye and pay attention to the space that’s visible between your nearer and farther finger. Now switch the eyes – open one and close the other. You’ll notice that the visible space between your fingers is different. If you now bring your farther finger a bit nearer to you and repeat the eye-closing experiment, the effect is less dramatic. When you see one thing as twice as far away as another, part of what is happening is that your visual system computes an estimate of depth by first computing which retinal cells are responding to the same point in the world, and then determining the relative difference (‘disparity’) in the positions or coordinates of those retinal cells (greater disparities = greater depth).
- Contour integration: when looking at the outline shape of an object in a cluttered scene, your visual system initially registers a bunch of tiny, individual segments of lines or contours (imagine lots of dashed lines). The visual system has to determine which line segments go with each other – which segments are parts of a common object’s outline, and which belong to different ones. The visual system computes outlines from line segments on the basis of, among other things, how close together those segments are, how similar in orientation they are, and whether they form an approximately straight line.
- Surface colour from illumination: the light that reaches your eye from a surface is a product of that surface’s colour and the colour of the illumination. So, your white shoes will reflect different types of light depending on whether it is daytime or dusk, or whether you are on the dance floor or in a fluorescent-lit bathroom. Still, you can usually tell that your shoes are white under these different conditions. When you see something as having a certain colour, your visual system is computing an estimate of the object’s colour by taking into account the nature of the illumination. The reason some people saw that dress as blue and black, and others saw it as white and gold, is that their visual systems are computing colours from different estimates of what the illumination is like.
Progress in cognitive science regularly consists in saying with mathematical precision exactly what is being computed – what direction should be estimated from some interaural time difference? – and exactly how the computation is performed. Hypotheses concerning these details can be and are tested against experimental observations, both of how people perform on tests (point to the loud noise, please) and of how populations of neurons respond to stimuli. There’s pretty stable agreement about what would count as evidence for or against hypotheses of this sort. Nobody has any real idea of how else to understand our abilities to, for example, perceive the locations of sounds or the depths, outlines and colours of objects.
Cognitive scientists seem to speak literally when they say that the brain computes
That’s a level of clarity and commitment to a premise that is uncharacteristic of metaphorical claims. Typically, if you press someone to explain just what type of oyster the world is, and where on Earth its gills are, everybody will agree that you’ve missed the point. But in cognitive science, hypothesising what specific kinds of computations the brain carries out and devising experiments to test these hypotheses is, far from missing the point, very often the job description.
Cognitive scientists seem to speak literally when they propose that the brain computes a certain function in a certain way. And the claim that the brain literally computes something implies that the brain is literally a computer (at least in part).
If it were just a metaphor to say that the brain is a computer, then we would expect it to be forever unclear what literal truths we are trying to convey with the use of this (presumably literally false) metaphor. But if the claim is meant literally, then we should hope for some precise account of what one is saying when one says that the br