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The perception-as-interpretation view, summarized in the previous post, is useful as an informal ordinary-language hypothesis about consciousness. However, it is obviously a long shot from a final literal scientific theory. While it seems to be a useful way of speaking, I think we should look at it as an interesting suggestion, or perhaps even an inspiration that will lead us toward a more specific and fleshed-out theory.
There is a diverse range of theories that turn out to be special cases of the perception-as-interpretation hypothesis. These theories describe the interpretation-building mechanism alternatively as neuronal ‘model building’, ‘emulation,’ ‘virtual reality construction,’ ‘simulation of a world’, or ‘unconscious inference.’ Each specific theory carries slightly different assumptions about how the brain constructs experience, but most of them share two or more of the general features of the interpretation view delineated in previous posts.
Among psychologists, the most influential of these views is that the brain uses an unconscious inference procedure to construct a hypothesis about the source of a retinal projection. Because this theory of perception is so interesting, influential, and useful, I’ll describe it in a little bit of detail before stepping back to speak more generally about all of these theories.
Marty the Brain Scientist
To help us understand this theory, let’s imagine a tiny scientist, Marty, who lives and works in your brain (Figure 1). His sole occupation, every moment, is to monitor the movies playing on your retinae, and to build a hypothesis about their source in the world. Our conscious experience is identical to the specific hypotheses that Marty generates. For instance, if Marty’s best hypothesis about the source of the stimuli is that there is a red ball three feet to your left, that is precisely what you will see. Marty is fairly motivated to generate hypotheses accurately and quickly: after all, if you die, he dies. The more accurate his hypotheses, the better you will be able to interact with the world.
Figure 1: Marty the brain scientist.
Retinal movies are Marty’s primary source of evidence. He uses such evidence, along with various assumptions and background knowledge about how the world works, to generate hypotheses about the source of the observed projections (that is, he makes an inference about the source of the stimuli). We are only conscious of the outputs of Marty’s vocation, not any details of his inference-generating procedures. Hence the hypothesis that perception is unconscious inference.
Hypothesis formation is a special case of inference. It is a type of inference that doesn't enjoy the level of certainty granted to deductive inferences (as you’d find in mathematical proofs). Rather, when we form a hypothesis we are often throwing out our best hunch, an educated guess based on limited evidence and previous assumptions about the way the world works. Philosophers sometimes call this type of inference an ‘inference to the best explanation’ or ‘abductive inference.’
For instance, say the evidence we wish to explain includes late-night scratching sounds in the cupboard and small fecal nuggets deposited in the pantry. We could use such evidence, and our general understanding of how the world works (mice are nocturnal, etc), to construct a hypothesis that would best explain the evidence. In this case, we would likely hypothesize that there are mice living in our kitchen. Perhaps Marty settles on his hypotheses about visual stimuli using a similar process of abductive reasoning.
Obviously, Marty is merely a useful fiction. Nobody thinks there is literally a little man in your head viewing your retinal movies. Advocates of this theory believe that we will ultimately be able to give a more literal story that describes how brains construct hypotheses based on information coming in from the retinae. In the meantime, I should spell out why the unconscious inference theory appeals to psychologists.
The appeal of the theory
There are three main reasons for the theory’s appeal (aside from its impressive intellectual pedigree since Helmholtz (1866)). For one, the theory would explain how certain illusions are generated. For instance, recall Shepard’s Monsters (Figure 2) from post eleven. Shepard explains the illusion as follows:
[T]he linear perspective of the subterranean tunnel (along with other depth cues, such as the relative heights of the projections of the two monsters on our retinas) supports the automatic perceptual inference that one of the two monsters is farther back in depth. The two monsters, nevertheless being exactly the same size in the drawing, subtend the same visual angle at the eye [i.e., their projections occupy the same surface area on the retinae]. The visual system therefore makes the additional inference that in order to subtend the same visual angle, the monster that is farther back in depth must also be larger.Notice how the idea of inference-making is built into multiple layers of Shepard’s explanation of the illusion. The brain makes inferences about which monster is further away, and then uses this information to make further inferences about which monster is larger, which explains why one monster looks bigger than the other. Note the claim isn’t that the brain only uses inferences in cases of illusions (how would the brain know if it were seeing an illusion or not?), but that illusions help reveal the underlying inferential machinery of normal perception.
Figure 2: Terra Subterranea, or Shepard’s Monsters
A second appeal is that the theory finds a mathematical home in probability theory and statistics. The brain lives in an uncertain world, and even the brain’s own responses to identical stimuli are not the same every single time (that is, the brain itself is a “noisy” processor). In mathematics, the principles of sound inference in such uncertain contexts are provided by statistics. Couching theories of brain function in the language of probability and statistics allows psychologists to state their theories with more rigor than can be done in ordinary language. Perhaps most importantly, such theories allow them to generate quantitative predictions that can be tested against the data.
Figure 3: The eye lives between a noisy brain and an uncertain world.
The third appeal applies to the ‘unconscious’ side of the ‘unconscious inference’ thesis. That is, it seems pretty clear that the processes which generate our perceptual experiences are not consciously accessible to us (as discussed in post ten and post thirteen).
Hopefully this gloss on the unconscious inference theory of perception was half as fair as it was brief. At this point I don’t want to push too hard against it (for instance, you would be right to ask what it means for the brain to perform an inference). Rather, my goal was to showcase the most prominent species of the perception-as-interpretation thesis. More than one-hundred years after Helmholtz initially suggested the hypothesis that perception is unconscious inference, Fodor and Pylyshyn were able to describe the theory, without much overstatement, as the ‘Establishment theory' of perception.
Representations within interpretations
Enough with unconscious inferences: what about all the other theories I mentioned above, such as the view that the brain builds a ‘simulation’ of the world? I am going to avoid jumping down the historical rabbit hole of comparing/contrasting the often subtle differences in this panoply of psychological-level theories of perception. Rather, it will be more productive to extract a common denominator shared by all of these theories, something all of the advocates would agree upon. If such a common factor turns out to be useful and correct, then great. If not, then we will have eliminated an entire class of models of perception with one parsimonious swing of the blade. This seems much easier than starting by contrasting every such theory pair in detail.
The one theoretical commitment shared by all these theories of perception is that the brain constructs representations of the world, and the contents of such neuronal representations are the contents of experience. Our first priority will be to analyze this idea of neuronal ‘representation’: what the heck does it mean, and how far can it take us in our quest to understand visual experiences?
While I won’t analyze the notion yet, the notion of a ‘representation’ should be intuitively familiar to most of us. Three squiggly lines on a map represent water. A photograph of someone represents the person. I’ve already sneaked in the claim that the brain constructs a ‘portrait’ of the world: a portrait of something is one type of representation. The claim we will evaluate is that one component of the brain’s interpretation of a stimulus is an internal representation of the world constructed partly based on that stimulus.
Before heading into brains, however, in the next post I will finish this chapter by posting a broad range of quotations from the literature on the topics we have explored in the last eight posts. This will help us to see how these ideas of interpretation, simulation, representation, etc are used in practice.
References
Fodor, JA, and Pylyshyn ZW (1981) How direct is visual perception? Cognition 9: 139-196.
Helmholtz, H. von 1866 Concerning the perceptions in general. In Treatise on physiological optics, vol. III, 3rd edn (translated by J. P. C. Southall 1925 Opt. Soc. Am. Section 26, reprinted New York: Dover, 1962).
Shepard, RN (1991) Mind Sights, W.H.Freeman & Co Ltd.
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Table of Contents of my posts on consciousness.
