Home » Psychosis: Bending Reality to See Around the Corners: Paul Fletcher (Transcript)

Psychosis: Bending Reality to See Around the Corners: Paul Fletcher (Transcript)

Now, this is a profound statement, because it’s telling us that we are actually bringing something to the act of perceiving reality. And it’s worth considering the nature of that inference.

Hermann Von Helmholtz, a 19th century scientist, thought a lot about perception, perceiving and experiencing the world as an inferential, logical process. And in fact, he said that it’s an act of imagination. He said, “Objects are always imagined as being present in the field of vision as would have to be there in order to create the same impression of the nervous mechanism.”

What he was saying here was that we have impressions, experiences on our nervous system just as Mountcastle suggested. And we then have to imagine what could have caused those.

We back project to the cause of the sensations that we do have. This is a form of inference, and it’s a form of inference that this chap here, Charles Peirce, an early 20th century philosopher, referred to as abductive inference or abduction.

Abductive inference really refers to reasoning backwards from evidence to the causes of those evidence. So we have the evidence in our senses, we need to reason backwards. And Peirce pointed out that actually this is one of the shakiest, most fragile, most tenuous forms of logical inference that you could have. He referred to it as guessing.

And the reason is guessing is that for any given sensory experience that we have, there is a myriad, multiple, infinite number of possible causes that could have given rise to that. And we are stuck with having to make a decision about what could have been that cause. As Peirce put it, he said, “The whole fabric of our knowledge is a matted felt of pure hypothesis.”

But we seem to get by. We do manage. And the reason that we manage is actually captured in a theorem that was developed by this 18th century Presbyterian minister Thomas Bayes. Many of you’ll have heard of Bayes’ theorem. You certainly come across it more and more in neuroscience nowadays. And Bayes pointed out, and in fact, Bayes, although he didn’t use the term, was talking about this form of abductive inference, about working out the causes based on the evidence.

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And he suggested that the optimal way to do this is to take the evidence but also to take what you already know, what your prior experience and expectation is, and fit those together, and resolve the ambiguity like that.

So imagine you’re walking down a country lane – let’s say, in Devon, and you hear the clip-clop of hoof-taps up around the band. You confidently expect that what will come around the corner next is a horse. But actually the evidence you have doesn’t tell you that necessarily. I mean who can tell the hoof-taps of a horse from a zebra, or a camel, or somebody banging a couple of coconut shells together? The evidence itself is ambiguous.

But of course, it’s your prior knowledge that what’s most likely to be around the corner in Devon is a horse not a zebra. And that’s essentially the insight provided by Bayes’ theorem and the notion of the inference that we apply to the world.

There’s good evidence that this sort of inference also occurs at lower unconscious perceptual levels, and we’re doing it all the time. Looking at this image here, to many of you who haven’t seen what I’ve seen, a meaningless collection of black and white blobs. To me it’s not, to me it’s a very, very meaningful picture.

I can see a lot in it. I can see there’s a woman. I can see that she’s young. I can see she’s wearing a hat. I can see that she’s happy. And I can see that she’s kissing a horse. And the reason I can see all that is not necessarily because I am hallucinating – although there’s an element of that actually, I think – but it’s because I’ve seen this image.

And this image was the original image from which the first one was created. Now, having given you that prior information, that prior expectation, it becomes more possible that some of you may now be able to look at the image and see the woman kissing the horse. This also works in the auditory domain.

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If you listen to this… (ambiguous sound) to many of you that will sound like a sort of meaningless bird-songy type of sound. To me actually, it’s highly meaningful. The reason it’s meaningful to me is I have prior expectations and prior knowledge. My prior knowledge comes from having heard this, (voice over) “The camel was kept in a cage at the zoo.” So now you have that prior experience and knowledge.

Will you be able to apply it to the original sound? (Ambiguous sound) It’s very, very striking, just how automatic and easy it is to now make sense of what was previously noise merely because of what you brought to the table. So that’s great.

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