4 ms·

An aberrant precision account of autism (2014)

45 points by danboarder 5y ago

zozbot234 5y ago
Very nice paper! For useful background on neural prediction, see "The brain is a Peirce engine" - http://esr.ibiblio.org/?p=7651 http://esr.ibiblio.org/?p=7651
- pedro2 5y ago
  Oh, an ESR follower. Kinda curious about how he is after the pandemic.
  - Qem 5y ago
    I was curious too. he used to post regularly in his blog, but then he stopped in september 2020 and didn't write since then. I liked his nice technical posts, albeit they were intermingled with some occasional gun nut stuff.
    - bitwize 5y ago
      He tried to fix the database bug that has been plaguing his blog late last year. He appeared to be making some progress, but it reasserted itself. He's in his late 60s now, his brain probably hasn't as much processing power as it used to, and I think faffing about with Linux and all the moving parts that make up a self-maintained blog is becoming just as baffling and tiresome to him as it is to nearly everyone else.
jedimastert 5y ago
Oh this is gonna be a fun deep dive, although a lot has changed around autism, even over the last 7 years or so.
xpuente 5y ago
One might wonder how Predictive Processing/Coding works when the "cortex" is empty (i.e., at birth). I don't know if this is just armchair neuroscience wrapped in a bunch of mathematical flourishes.
- MarkusQ 5y ago
  The cortex is never "empty". The blank slate model is an outdated speculation with no empirical support, akin to "you only use 10% of your brain" or "you can tell things about people's personality by feeling the bumps on their head".
  - xpuente 5y ago
    I'm not sure that there is no empirical support: see [0] [0] A. Roe, S. Pallas, Y. Kwon, and M. Sur, “Visual projections routed to the auditory pathway in ferrets: receptive fields of visual neurons in primary auditory cortex,” J. Neurosci., vol. 12, no. 9, pp. 3651–3664, Sep. 1992. PS: I'm not saying that there is uniform initial connectivity. Just, the prediction level units (cortical columns) are unable to predict anything until they learn "something".
    - MarkusQ 5y ago
      As that paper's abstract says, "Cells in A1 of rewired animals differed from cells in normal V1: they exhibited larger receptive field sizes and poorer visual responsivity, and responded with longer latencies to electrical stimulation of their inputs" -- that is, the aditory cortex expects auditory data, and although it can adapt it doesn't handle it as effectively as the visual cortex does, because it's expectations aren't met. So that's evidence that there are predictions baked in from day one.
gowld 5y ago
Is there a simple English version of this? "aberrant precision" is in't even defined specifically precisely defined, ironically.
- munificent 5y ago
  Here's an attempt with the caveat that I'm not at all an expert on this and may get lots of things wrong: The basic idea is that there is a world "out there", and then each person has a mental model of that world. Our actions are not based on the external world, but on our internal model of it. When sensory information comes in, we use that to update the model. The loop is something like: 1. Stimulus comes in. 2. Figure out what that means. 3. Use that to update the model. 4. Take action based on that. 5. See how our action affected the world and goto 1. Step 2 is the tricky one. Stimulus is often ambiguous and our perceptions of it are imperfect. You see a flash of light. It could mean someone took a photo, the sun glinted off a moving object, or maybe just a spurious firing on our optical nerve. How do we know how to update the model based on that stimulus? We can't just always assume the stimulus is fully accurate and blanket update the model based on it because there's a lot of noise in the data. We also can't just assume that whenever the stimulus disagrees with the model that it's noise and discard it. The whole point of perception is to update our model to reflect a changing world. So we have to decide what a piece of stimulus means (since it's ambiguous) and how much confidence we have in that interpretation (since it's noisy). How might we decide a confidence level? All we know is our own model and that the external stimulus. There are a bunch of different ways that involve things like estimating how likely a stimulus like that is to occur, our previous experience with misinterpreted signals (i.e. what we have learned about our own perceptual hardware), etc. Of course, none of this is happening consciously. It's how the brain itself thinks. The thesis of the article is that those with autism have this process miscalibrated where they treat external stimulus as much more precise (i.e. less noisy or ambiguous) than it actually is. The symptoms of autism are then emergent phenomena of how a brain might try to cope with that problem.
  - goodroot 5y ago
    Signed in just to thank you. Thank you!
deleted 5y ago
[deleted]

45 points by danboarder 5y ago

Very nice paper! For useful background on neural prediction, see "The brain is a Peirce engine" - http://esr.ibiblio.org/?p=7651 http://esr.ibiblio.org/?p=7651

pedro2 5y ago
Oh, an ESR follower. Kinda curious about how he is after the pandemic.
- Qem 5y ago
  I was curious too. he used to post regularly in his blog, but then he stopped in september 2020 and didn't write since then. I liked his nice technical posts, albeit they were intermingled with some occasional gun nut stuff.
  - bitwize 5y ago
    He tried to fix the database bug that has been plaguing his blog late last year. He appeared to be making some progress, but it reasserted itself. He's in his late 60s now, his brain probably hasn't as much processing power as it used to, and I think faffing about with Linux and all the moving parts that make up a self-maintained blog is becoming just as baffling and tiresome to him as it is to nearly everyone else.

jedimastert 5y ago

Oh this is gonna be a fun deep dive, although a lot has changed around autism, even over the last 7 years or so.

xpuente 5y ago

One might wonder how Predictive Processing/Coding works when the "cortex" is empty (i.e., at birth). I don't know if this is just armchair neuroscience wrapped in a bunch of mathematical flourishes.

MarkusQ 5y ago
The cortex is never "empty". The blank slate model is an outdated speculation with no empirical support, akin to "you only use 10% of your brain" or "you can tell things about people's personality by feeling the bumps on their head".
- xpuente 5y ago
  I'm not sure that there is no empirical support: see [0] [0] A. Roe, S. Pallas, Y. Kwon, and M. Sur, “Visual projections routed to the auditory pathway in ferrets: receptive fields of visual neurons in primary auditory cortex,” J. Neurosci., vol. 12, no. 9, pp. 3651–3664, Sep. 1992. PS: I'm not saying that there is uniform initial connectivity. Just, the prediction level units (cortical columns) are unable to predict anything until they learn "something".
  - MarkusQ 5y ago
    As that paper's abstract says, "Cells in A1 of rewired animals differed from cells in normal V1: they exhibited larger receptive field sizes and poorer visual responsivity, and responded with longer latencies to electrical stimulation of their inputs" -- that is, the aditory cortex expects auditory data, and although it can adapt it doesn't handle it as effectively as the visual cortex does, because it's expectations aren't met. So that's evidence that there are predictions baked in from day one.

gowld 5y ago

Is there a simple English version of this? "aberrant precision" is in't even defined specifically precisely defined, ironically.

munificent 5y ago
Here's an attempt with the caveat that I'm not at all an expert on this and may get lots of things wrong: The basic idea is that there is a world "out there", and then each person has a mental model of that world. Our actions are not based on the external world, but on our internal model of it. When sensory information comes in, we use that to update the model. The loop is something like: 1. Stimulus comes in. 2. Figure out what that means. 3. Use that to update the model. 4. Take action based on that. 5. See how our action affected the world and goto 1. Step 2 is the tricky one. Stimulus is often ambiguous and our perceptions of it are imperfect. You see a flash of light. It could mean someone took a photo, the sun glinted off a moving object, or maybe just a spurious firing on our optical nerve. How do we know how to update the model based on that stimulus? We can't just always assume the stimulus is fully accurate and blanket update the model based on it because there's a lot of noise in the data. We also can't just assume that whenever the stimulus disagrees with the model that it's noise and discard it. The whole point of perception is to update our model to reflect a changing world. So we have to decide what a piece of stimulus means (since it's ambiguous) and how much confidence we have in that interpretation (since it's noisy). How might we decide a confidence level? All we know is our own model and that the external stimulus. There are a bunch of different ways that involve things like estimating how likely a stimulus like that is to occur, our previous experience with misinterpreted signals (i.e. what we have learned about our own perceptual hardware), etc. Of course, none of this is happening consciously. It's how the brain itself thinks. The thesis of the article is that those with autism have this process miscalibrated where they treat external stimulus as much more precise (i.e. less noisy or ambiguous) than it actually is. The symptoms of autism are then emergent phenomena of how a brain might try to cope with that problem.
- goodroot 5y ago
  Signed in just to thank you. Thank you!

deleted 5y ago

[deleted]