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Tilting At Windmills: Why Ogi Ogas and Sai Gaddam Are Bad Scientists (Neuroscience edition, round 2)
neededalj
[addendum added just before posting].....fuck, ya'll, what can I say. I was an inspired insomniac. I hope this makes sense.

In reply to the response my first essay received, I have decided to attempt a further deconstruction of the Fail Neuroscience of Drs. Ogas and Gaddam. In a different approach from my first post, I am going to take this one from the ground up and start with the basic building blocks of neuroscience. I'm trying to write for an educated layperson; if I'm not clear about something, please ask. I am also limited at this time from being outside the university system (I would dearly love to do a proper *academic* criticism with citations and everything, but that's out of reach right now).



Ok. The Brain.

The brain is composed of networks of neurons. Neurons are single cells in the nervous system that 'talk' to each other, in various ways. One way is through electrical impulses, and another is with chemical signals called neurotransmitters that travel between the cells. A change in one neuron will send a series of messages to the neurons that border it, and then they communicate to the neurons bordering *them* and so on and so forth. An active brain is one where the neurons are continuously changing in response to each other. If they aren't, you're dead. When doctors say that someone is 'brain dead' it means that the neurons have died and stopped communicating to each other.

There are BILLIONS of neurons in the human brain. Billions. They are arranged into differentiated areas and structures. Some of these are very clearly physically defined, like the hippocampus. Others blur together such that you can tell that the areas of different, but it's hard to draw sharp line between them.


Now it's time to take a step back and have a short interlude about Science. The holy grail in scientific research is a theory with predictive ability. That's what scientists are doing when they experiment, theorize, and experiment again. Anyone can make a theory that can be retrofitted onto data you already know. The key to a good theory is to have it predict what happens in the future. Remember this: predictive ability. It's the goal of Ogi and Sai's research. It's what they think they have figured out how to do, and I'll return to this point later in the discussion about models.

Human's can't create a synthetic brain right now. It's far to complex. Your brain as you read this essay is doing something that the most advanced supercomputer can't. Your brain is better and faster than the world's greatest artificial machine at anything that requires a complex response. (Want to know why voice recognition systems are so bad? Scientists initially thought voice recognition would be a piece of cake because language was just a series of discreet inputs. WRONG. Turns out the brain is actually parsing a near continuous nondifferentiated stream of sound. Oops).

Some neuroscientists start by looking at behavior, stimuli, and inputs and attempt to sort things out through imaging and lesions studies (looking at when a brain is damaged to see what cognitive deficits appear). This is more the kind of stuff I studied.

What some neuroscientists and computer scientists do is model brain behavior. Neural models involve using computers to simulate neurons and programming those neurons using *very* complicated math to respond in a certain way, and then applying a stimulus and see if your model makes sense/is doing what it's supposed to/actually resembles the human brain/is properly predicting things (take your pick or all of the above).

Taking a very simple example from vision (vision modeling being the field Ogi Ogas held up as 'more complicated than' subcortical structures and sexual behavior).

Let's say I have neuron A, which is a retinal neuron (a neuron in the eye) and responds to a certain frequency of light. Neuron A is connected to Neurons B and C which are connected to each other, and which are connected each of them to Neurons D and E, and neuron E is connected to neuron F which is also connected to neuron B.

Now I give the system an input; because this is a visual system, our input is light. And neuron A is the only neuron that actually is exposed to the light. But neuron A now fires a signal, which triggers neurons B and C, and they trigger D and E...but remember that E is connected to F which is connected to B. So now F is *also* signaling B. Many responses later down the line the brain recognizes that neuron A fired and you see the light (literally). But it's not a simple chain; it's an overlapping, interwoven network with communication and response flowing 'up' *and* 'down'.

Neural systems are non-linear in structure and response. See how complicated my little example got with just 6 neurons and an input with simple physical properties (light)? The computing power required to model complicated neural networks is intense; take my little example and multiple it thousand thousand of times to get what our most sophisticated modeling systems do now, and multiply it a billion billion times to get what the brain actually does. So modelers write their models and ask 'does this system respond the way the brain does to this stimuli? or 'does this system 'remember' this stimuli'? etc.

Everything following from this point is speculation. Educated speculation, yes, but please do not quote me as saying what Ogi Ogas and Sai Gaddam were actually doing because I DO NOT KNOW for sure.

As far as I can figure out--and I have to caveat this because I literally had to look away from many of their explanations in pure disgust--Ogi Ogas and Sai Gaddam want to do this kind of modeling. Only instead of neurons, they want to use *structures*. And instead of simply physical stimuli, their inputs are...sexual? erotic? pornographic?

My BEST GUESS (and it is at best a guess, because it's so appallingly wrong-headed I can barely bring myself to type this) is that their 'survey' was designed to gather either a)inputs to the system or b)data to program the system; ie, women find THIS sexy which will cause the amygdala to respond'.

Models require data from the beginning. You look at a real-worl example, you say 'Neuron A does this when it is exposed to green light, but not red light or blue light!' and you program that in. If their survey gathering was to get programmable data for the neural network itself I...don't have much to say. They have no way of linking responses to *actual* neural responses because as many people have pointed out, they can't image us through their computers. So they would be firmly in the 'making shit up' category.

If they are using the survey responses as *inputs*, that's a little different. In that case they must be building their model off of a thousand sources which I believe I have seen them list--primate studies, former imaging studies, physiological responses such as blushing or pupil dilation to stimuli (in other people's experiments), and god knows what else. So basically they think they can take complex, complicated real-world stimuli such as an NC-17 slashfic, and say that it calls up a specific set of neural responses (responses that would theoretically include both electrical responses and chemical neurotransmitter responses). And they think they can program a model which predicts that.

They keep harping on about subcortical structures, but scientists barely understand subcortical structures. Here are some of the things subcortical structures have been implicated in: language, movement, learning, emotions, sleep, attention, and yes, arousal. Not by themselves, of course; the cortex is involved in all of this as well.

I don't really want to go into this further, because it goes more and more into speculation. But you probably don't need my help to see where 'deviancy' would enter into this situation. Deviant inputs should elicit different responses than 'normal' inputs. I assume this is where slashfic and 'shemale' pornography would enter into the picture. But I can only guess. I suspect that their model will assume universals as deeply laughable as their survey was a methodological travesty.

They're utterly wrong, of course. Their privilege racism and sexism and homophobia have been detailed at great lengths elsewhere. We don't know much about the brain, relatively speaking, but we do know this: all human beings have one. And human beings are wonderfully diverse, unpredictable creatures. Our cultures are different, our tastes are different, we interact differently in social situations. We have different morals and different traditions, different tastes and different emotions.

And our science is not yet at the point where this can be modeled in any of our artificial technological creations (ETA: there is a very good comment detailing a computer science perspective on neural nets here).



Ogi Ogas and Sai Gaddam's 'research' is a tragic act of biological reductionism.

You are so beautiful to me right now. ♥

Holy shit the rage began to overwhelm me toward the middle of your post but I kept reading because apparently I don't hate these guys enough at this point.

HOLY. SHIT. I barely knew about the kind of model building they're involved in until now (a bit from the Psych angle, a bit from the AI angle, but very little overall) and I was confused about what it is they are actually hoping to GAIN with this survey for their research. This detailed that for me in beautiful and horrifying colors. JESUS FUCKING CHRIST, THESE PEOPLE.

they stated somewhere that the purpose of their research was to show that not just fMRI results should be used in neuroscience and complaining that currently "it's the only way to get published". I JUST CAN NOT BELIEVE THEY ARE BUILDING BEHAVIORAL MODELS.

SUBCORTICAL REGIONS ARE LESS COMPLICATED THAN THE VISUAL SYSTEM?!?! This is like, sci fi levels of unbelievable coming from people with ANY kind of Academic degree (you'd think they'd been taught to research what they didn't know).

I shall now go and try to stop being angry and fail miserably.

An active brain is one where the neurons are continuously changing in response to each other. If they aren't, you're dead.

Uh-oh...

...

x_x

b)data to program the system; ie, women find THIS sexy which will cause the amygdala to respond'.

Oh, my God. I bet you've got it. It makes SO MUCH SENSE when they say that they're not doing social science now.

It makes SO MUCH SENSE when they say that they're not doing social science now.

My own brain is in conflict. On the one hand, you're right, this *might* actually explain what they thought they were doing.

On the other hand, it's such a *stupid* idea that my brain keeps tossing it back out like a slug in a vending machine.

Oh, read this. Read this now. http://ken-jennings.com/blog/?p=568 It's a description of Dr. Ogas on a game show, and here's the key quote:

The more exposure you get to Ogi, the more you see that he’s just like that. He’s not putting on a little show to mess with your mind–he’s just got a very specific, determined way of doing things. Sure, he’s a bit of an oddball, but in the world of game show uber-contestants, that’s hardly a capital crime. The congenial, funny on-line Ogi is the real Ogi too, but unfortunately for him, you can’t close the barn door once the ass is gone. And Ogi explained to me that the greenroom comas had nothing to do with mind games and everything to do with circadian rhythms (or downloading new data from the mothership, or something).

Me:Basically, he has an area of expertise, and he thinks it explains everything. Everything everywhere.

I think you're right, but it's important to point out that he's not using cognitive neuroscience in an orthodox, extensional way, he also apparently doesn't have any problem *intuiting* what he thinks of as a cog sci *approach* to wildly diverse areas.

I actually think you guys are assuming much too much intellectual honesty on the part of Ogi and co. I doubt his book is a real attempt at cognitive modelling(however flawed) his mention of a repeat with the Right implies to me that he's writing a politicized social science book, with cog sci technobabble laid over it.

Unfortunately, that kind of book where political, moral, or social assumptions are laid out in a nice, self-confirming shallow analysis, with a light glaze of Scientific American-like language is really popular.

I just feel really bad, because things like this end up with me feeling pressure to hide my field, or opinions on it's applicability, because I'm afraid it'll get mixed up with this kind of idiocy.

They say a little bit of knowledge is a dangerous thing, and that goes double if it's knowledge in a really powerful, compelling scientific area. Because people get so excited by what it explains that they then extend that authority as far as it will go. And often further. And then attribute any success they have to the strength of their ideas. And fall further into a black of of self-confirmation, making the rest of us scientists look bad.

Thank you for both the essays.

Very illuminating and clear for people who have little or no background on this subject.

Makes me happy my gut fits with facts.

I haven't really commeted about this on any of the journals because I'm having a hard time just keeping up with reading everyone's fantastic responses. But thank you for this explanation! It does clarify why they say they are not doing social research with their survey.

Thanks for this post! I've been focusing on thinking about the 'datamining' aspects of their work, so it's cool to hear about the modeling side.

You are a much better science teacher than either of those guys. ♥

Thank you--thank you!

Just an additional note which you might have missed: at one point (I think it was in Shaggirl's journal, but I cannot swear to it; maybe it was in a now locked explanation post in Ogi's), he said that some of the questions in the survey were included BY fans, just FOR fans, so they could give something back to the community, even though they were not interested in the questions--he implied (or so I read it as implying) that these were things suggested by their fan correspondents, and in no way that I recall did he identify WHAT ones were fan generated and which ones were real.

Which struck me as bizarre becuase who does that in survey work?

And that also skews any attempt to figure out what they might be doing looking at their survey questions which of course began changing immediately....

This was fascinating to read though, and proof that someone who knows the topic can explain to people who do not. Ogi never managed that, but I don't think he intended to: I think he was obfuscating and bullshitting the whole way through!

Link for info cited above!

ithiliana

2009-09-03 05:30 pm (UTC)

http://shaggirl.livejournal.com/186106.html?thread=3047418#t3047418

This is where he talks about his big mistake was including questions FOR fandom (us ungrateful purported anonymouse types rejected his GIFT)--I found it on unfunnybusiness, yay for them!

Thank you for both essays. Even recognizing your suppositions as educated guesses, I think you've provided much needed insight as to what they thought they were (and probably still are) doing. Sadly, I think they'll still get published, and this idiocy won't even be a blip on anyone's radar.

In this context, it worries me that these guys mentioned nifty as well. Another group of othered self-providers.

And, er. A young woman who has had her sexual socialization guided in part by slashgirls *raises hand* will see nothing deviant about slashfic. It is entirely normal.

Thanks so much for this post. Laying things out in a clear, concise manner for the layfolk was helpful and informative and it was a little way in diffusing my own cynical idea that 'yeah, these guys, having used the fandom community will now write a pseudo-science piece of crap book and make a boatload of money off our backs".

I still think they'll go ahead and do this and I still feel like they used the largesse of people who did their best in a variety of ways to educate them. I suppose I see some small difference in the idea that they seem to feel that since they have their newly-minted diplomas in their field of expertise they now think that their extra-special knowledge entitles them to make a buck off the backs of people they never even took the time to understand. Just because they really, truly feel that way doesn't make it okay, though, and that lame-ass 'apology' on ogi_ogas's now-sealed LJ only reinforces the impression I read from them after things had gone past a certain point, i.e., a pair of condescending, mysogynistic homophobic guys who think way too much of themselves and thier degrees--we don' need no steenkin' ethics!

Again, thanks for the informative post; Aside from the suvey-fail, I learned a thing or two and that's never a bad thing.

Edited at 2009-09-03 10:15 pm (UTC)

We don't know much about the brain, relatively speaking, but we do know this: all human beings have one.

You are awesome--and for both of these posts, not just this particular line.

And for what it's worth, I'd definitely agree with your take on Ogi's motives--I've met a fair number of people like him, in academia and outside it, who think that thanks to the fancy initials after their name, they know everything. Or, to be more specific, that their little corner of expertise gives them the Ultimate and Only Angle on the world.

Edited at 2009-09-04 04:21 am (UTC)

Thank you for this wonderful explanation, and for the other post detailing neuroscience for dummies. Your responses to the comments were things of beauty, as well, and I for one am very glad you needed an LJ to write all this out and continue responding.

I couldn't agree more. The idea that these men have, you know, suddenly discovered the perfect model to analyze desire? sexuality? anything at all? is ludicrous.

To come at this from a CS/AI perspective: what we refer to as 'neural nets' are, in fact, hideously, hideously flawed models of any kind of human behavior. Which is something that most CS research at least has the decency to admit. We've come to the conclusion that what we call neural nets are useful in certain types of programming situations, but that they are in no way predictive of human behavior. Which, as you say, is the whole. frickin'. point.

My best anecdote (as told to me by my college AI professor): a neural net computer was designed to recognize the difference between enemy planes and friendlies. After being 'trained' on some number of 'good' and 'bad' images it was able to identify friend from foe... until someone introduced a new set of images that were taken at a different time of day and it suddenly got confused. At which point the scientists working on the neural net discovered that the whole time they assumed the computer had been looking at the planes, it had been drawing its distinctions from the color of the sky and hadn't been looking at the planes at all.

Seeing as this is the most sophisticated computerized model we have right now for the human brain - and we apparently don't understand what it's doing either... I shudder to think what model these men have concocted from combining two whole academic disciplines that have openly, publicly thrown up their hands and said "WELL WE DON'T KNOW YET OK."

So even if they do use this survey data to train up a neural net into telling them the nature! the very essence! of female desire... how would they even know that women are responding to their (exceptionally ill-founded) assumptions, and not just the scenery?

the scientists working on the neural net discovered that the whole time they assumed the computer had been looking at the planes, it had been drawing its distinctions from the color of the sky and hadn't been looking at the planes at all.

It's not just neural nets that have this problem. In the Second World War, the Russians trained dogs to run underneath tanks, carrying explosive charges that would destroy the tank. When it came to battlefield deployment, the dog units hit a number of problems, not least that the dogs had been trained to run underneath Russian tanks, not German tanks. Specifically, the dogs had learned to go towards the smell of the diesel engines used in Russian tanks, and avoided the unfamiliar smell of the German petol engines.

Just wanting to add my voice to the many thank yous on this page: thank you! I couldn't make heads or tails of the two doctors' explanation, neuroscience not being my field, but you've explained it, and their fail, very eloquently. So thank you for taking the time to do that.

Thank you so much for your explanations, they really helped clarify things for me. And oh, Turns out the brain is actually parsing a near continuous nondifferentiated stream of sound. Oops) this? As one of those frustrated early adopters, SO happy to know it wasn't just me. Sheez.

Thanks for posting this. My science background is chemistry, but I kept looking at their "science" explanations (which had I distinct whiff of "you can't possibly understand this") and going …wuh?

In particular, the argument that slash and male interest in "shemales" is clearly linked to the subcortex because it was not what culture predicted, followed quickly by saying that they weren't looking at culture. You're…using culture when convenient to define the boundaries of your interest and then discarding it entirely in interpreting your data? You can't do that!

Even if you set aside all of the assumptions, all the male privilege, all of that, I was amazed at how useless the questions actually were. As many people pointed out, there would be a question with five options, three of which are about frequency of an activity and two are about whether you like it. How can you get any data from that? You have (in one question!) failed to isolate separate effects. There were also a bunch of questions that were impossible to answer in a meaningful way, like the one asking if we identify with the "dominant" or "submissive" character. Because it was so poorly defined, and even if it had been better defined, was looking at the wrong parameters for identification with a character in a story (and failing to see "identification" as a fluid concept that does not mean "picturing myself as that person"), even if they got a thousand people to choose an option, none of those people mean what the authors are going to assume they mean.

The survey was just…vague and irrelevant in a lot of places, clearly designed to support their assumptions.

And if you make crap assumptions, you're going to get crap science from it. I mean, I could assume the universe is made of pudding, but I'm not going to get any useful predictive models if I do that.

I'd totally read the paper, though.

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