Phantoms in the brain

I’ve spent way too much money on books this autumn, as well as arguably too much time as well, so I’ve been feeling guilty about that. This guilty conscience has had as a consequence that I didn’t stock up on reading materials after I’d read the interesting stuff from the last amazon batch, something I usually do so that I always have a few books available that I’d potentially like to read if I find myself in the mood. I basically haven’t had many interesting unread books standing on my shelf, and so I haven’t read very much – a fact that I’ve also felt guilty about. Yesterday the contribution to my guilty conscience from not engaging in offline book-reading finally surpassed the contribution to it from spending money and time on reading too much ‘irrelevant stuff’ (i.e. non-exam-related-stuff), and so I ended up reading Ramachandran’s book.

Overall it’s better than Sacks, but I don’t really think that’s saying all that much. At least there aren’t any Wittgenstein quotes in this one (though there are Shakespeare quotes). I think this is the last book of this nature I’ll read – they’re too unsystematic, speculative and messy in their structure and I’d learn a lot more from just reading some chapters in a textbook like this (I probably won’t start out with that as I have this one standing on my shelf..). This is not to say that I didn’t learn anything from the book, and if you want to have a go at one of these easy-to-read introductory pop-sci neurology books, you can do worse (as I have realized). There’s less focus on patients and more focus on the specifics of the stuff that goes wrong and what those specifics tell us about how specific elements of the human brain works than in Sacks, and particularly important here is the fact that Ramachandran has included figures with illustrations of how the brain looks like and which structures are placed where, which was a big help to me during the reading.

I found the stuff on vision and how it works very interesting, so I’ll quote some stuff from that part of the book:

“The human brain contains multiple areas for processing images, each of which is composed of an intricate network of neurons that is specialized for extracting certain types of information from the image. […] every act of perception, even something as simple as viewing a drawing of a cube, involves an act of judgment by the brain.
In making these judgments, the brain takes advantage of the fact that the world we live in is not chaotic and amorphous; it has stable physical properties. During evolution—and partly during childhood as a result of learning— these stable properties became incorporated into the visual areas of the brain as certain “assumptions” or hidden knowledge about the world that can be used to eliminate ambiguity in perception. For example, when a set of dots move in unison—like the spots on a leopard—they usually belong to a single object. So, any time you see a set of dots moving together, your visual system makes the reasonable inference that they’re not moving like this just by coincidence—that they probably are a single object. And therefore, that’s what you see.” […]
“because of some quirk in our evolutionary history, each side of your brain sees the opposite half of the world (Figure 4.4). If you look straight ahead, the entire world on your left is mapped onto your right visual cortex and the world to the right of your center of gaze is mapped onto your left visual cortex. […] this first map serves as a sorting and editorial office where redundant or useless information is discarded wholesale and certain defining attributes of the visual image—such as edges—are strongly emphasized. […] This edited information is then relayed to an estimated thirty distinct visual areas in the human brain, each of which thus receives a complete and partial map of the visual world. […] Why do we need thirty areas?6 We really don’t know the answer, but they appear to be highly specialized for extracting different attributes from the visual scene—color, depth, motion and the like. When one or more areas are selectively damaged, you are confronted with paradoxical mental states of the kind seen in a number of neurological patients. […]

One of the most important principles in vision is that it tries to get away with as little processing as it can to get the job done. To economize on visual processing, the brain takes advantage of statistical regularities in the world—such as the fact that contours are generally continuous or that table surfaces are uniform—and these regularities are captured and wired into the machinery of the visual pathways early in visual processing. When you look at your desk, for instance, it seems likely that the visual system extracts information about its edges and creates a mental representation that resembles a cartoon sketch of the table (again, this initial extraction of edges occurs because your brain is mainly interested in regions of change, of abrupt discontinuity, at the edge of the desk, which is where the information is). The visual system might then apply surface interpolation to “fill in” the color and texture of the table, saying in effect, “Well, there’s this grainy stuff here; it must be the same grainy stuff all over.” This act of interpolation saves an enormous amount of computation; your brain can avoid the burden of scrutinizing every little section of the desk and can simply employ loose guesswork instead […] what we call perception is really the end result of a dynamic interplay between sensory signals and high-level stored information about visual images from the past. Each time one of us encounters an object, the visual system begins a constant questioning process. Fragmentary evidence comes in and the higher centers say, “Hmmmmm, maybe this is an animal.” Our brains then pose a series of visual questions: as in a twenty questions game. Is it a mammal? A cat? What kind of cat? Tame? Wild? Big? Small? Black or white or tabby? The higher visual centers then project partial “best fit” answers back to lower visual areas including the primary visual cortex. In this manner, the impoverished image is progressively worked on and refined (with bits “filled in,” when appropriate). I think that these massive feed forward and feedback projections are in the business of conducting successive iterations that enable us to home in on the closest approximation to the truth.16 To overstate the argument deliberately, perhaps we are hallucinating all the time and what we call perception is arrived at by simply determining which hallucination best conforms to the current sensory input.”

When I include quotes like the ones above in the post, I feel that I also have to quote some different stuff in order to give you a more complete picture. Here’s one quote which says a lot: “Contrary to what many of my colleagues believe, the message preached by physicians like Deepak Chopra and Andrew Weil is not just New Age psychobabble. It contains important insights into the human organism—ones that deserve serious scientific scrutiny.” So, yeah… Fortunately that quote was on page 221 (if it had been on page 20, I would not have read the rest of the book). In all fairness, he calls for rigorous tests but he also writes that “We have no idea which ones (if any) [of the alternative ‘medicine’ interventions] work and which ones do not” – which is a, problematic, claim. ‘Alternative medicine’ is ‘alternative’ because it doesn’t work – when health interventions of one kind or another can be shown to work in controlled experiments, they stop being ‘alternative’ treatments; the stuff that works is just called medicine. I know that there are institutional obstacles at play that keeps out treatment options which likely work but will never be profitable enough to justify trying to get through FDA approval, to take an example, but at least as a first approximation that’s how it works. You should probably also know, before you rush out to find the book, that I felt compelled to write words like ‘fool’ and ‘WTF’ in the margin at various occasions – the quote is not the only one of its kind. It’s safe to say that I very rarely do this when I read a book.


November 29, 2012 - Posted by | Biology, Books, Medicine, Neurology


  1. It seems that Ramachandran is very prone to fuzzy thinking sometimes:

    Comment by Miao | November 30, 2012 | Reply

    • Yes, ‘prone to fuzzy thinking’ is not a bad way to put it.

      I know I already linked you to this post in a previous conversation, but others are reading along as well here and I thought I might as well share it with them. As Yudkowsky puts it:

      “If, outside of their specialist field, some particular scientist is just as susceptible as anyone else to wacky ideas, then they probably never did understand why the scientific rules work. Maybe they can parrot back a bit of Popperian falsificationism; but they don’t understand on a deep level, the algebraic level of probability theory, the causal level of cognition-as-machinery. They’ve been trained to behave a certain way in the laboratory, but they don’t like to be constrained by evidence; when they go home, they take off the lab coat and relax with some comfortable nonsense. And yes, that does make me wonder if I can trust that scientist’s opinions even in their own field – especially when it comes to any controversial issue, any open question, anything that isn’t already nailed down by massive evidence and social convention.”

      I know that you agree with that sentiment – so do I.

      Comment by US | November 30, 2012 | Reply

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