Thursday, September 10, 2009

Does your brain balance prediction and observation?

Sorry for the slight infrequency in my posts. Things are hectic in graduate school, as can be expected. I do still plan to update this blog with thoughts as frequently as I can find time.

So I just watched a talk by Moshe Bar of the Harvard Medical School. The thrust of his research program is that the mind (and neural substrates thereof) do not passively respond to environmental stimuli, but constantly attempt to predict what is about to happen -- what the eyes are about to see happen next, for example. Or, if seeing a blurry outline of an object, inferring what that object is from contextual and shape cues. Bar showed very neat MEG evidence showing that the time course for activation of the (prefrontal) brain area supposed to do the prediction is about right for his hypothesis. In other words, it activates before the area associated more directly with conscious recognition of an object does. Curiously, this means that the prefrontal cortex is involved directly in fairly low level vision. This, in and of itself, is interesting data, and Bar's hypothesis seems plausible. But to my mind, it says too little about the cognitive mechanisms involved. Here is a proposal about what could be going on, from a computational perspective.

This all struck me as very similar to the AI mechanism known as a Kalman filter. Without getting into the math, the basic idea behind a Kalman filter is that it adjusts the balance between prediction and observation in the model of the world that the organism dynamically builds. So, for example, a Kalman-filter-equipped robot that is navigating a ship could rely either on observations of the nearby shoreline combined with the speed reported by its engines to calculate its predicted position in the future. Alternatively, it could rely on "dead reckoning" -- knowing that it left harbor in a particular location, and headed in a particular direction with a particular speed. Which one the robot wants to rely on depends on how noisy each set of information is. If, for example, the robot is in a deep fog where the shoreline is hard to make out, and the engine speed-reporting device is malfunctioning, relying on dead reckoning may be a good idea. If, on the other hand, there is a strong but unpredictable current in the water (say, the ship passed through some whirlpool and came out facing a slightly different direction), then the robot probably wants to rely much more on the shoreline and engine speed readings.

The Kalman filter plays a role in all this by calculating the (mathematically provably) optimal balance between which set of information to rely on (prediction or observation), dependent on the noise of each, such that the model is maximally accurate.

The point of all of this is -- could it be that the neural architecture Bar provides evidence for is actually a neural instantiation of the Kalman filter? One way to test for this might be to see if activation of the prefrontal "predictive" area Bar identifies is lessened when the environmental input is clearer, and strengthened when it is noisier. Of course, even if the neural system is some sort of instantiation of a Kalman-filter-like device, it would not have to behave in this way. Perhaps the prefrontal area Bar identified is just the prediction element of the Kalman filter design, with a further "selective" element being present, which performs the actual computation of determining how the organism should balance relying on prediction versus observation.

Making specific predictions is complicated in this case, but it might also be worthwhile. The idea of a computational mechanism originally proposed in AI being instantiated in neural architecture unites the two fields in a pretty exciting way, shows exactly the kind of thing AI has to contribute to the study of the mind, and might even suggest that we instantiate a computationally, mathematically, theoretically optimal (!!!) mechanism.

Friday, September 4, 2009

The really depressing thing about the Viriginia governor race

If you don't know the story, it's summarized here. Essentially, Republican gubernatorial candidate Bob McDonnell is taking some political flack for a thesis he wrote 20 years ago during his Masters program. The thesis contained many pieces of pretty old school right wing agenda. For example, McDoinnell wrote that working women and feminists are "detrimental" to the family and that government policy should favor married couples over "cohabitators, homosexuals or fornicators."

I won't talk much more about McDonnell -- you can find plenty of bloggers and news stories covering his thesis and the political situation. The part that gets to me is a little different than the political issue of his thesis. Rather, I can't believe CNN is calling his work a "research paper" (Eg. in the article linked above).

Lets be clear here. McDonnell's thesis was written at an unabashedly evangelical university, started by Pat Robertson to further a Christian right-wing social agenda. It was originally named Christian Broadcasting Network University (seriously), eponymous for Pat Robertson's TV network. Here's what The Washington Post has to say on the thesis:

'The thesis wasn't so much a case against government as a blueprint to change what he saw as a liberal model into one that actively promoted conservative, faith-based principles through tax policy, the public schools, welfare reform and other avenues.

He argued for covenant marriage, a legally distinct type of marriage intended to make it more difficult to obtain a divorce. He advocated character education programs in public schools to teach "traditional Judeo-Christian values" and other principles that he thought many youths were not learning in their homes. He called for less government encroachment on parental authority, for example, redefining child abuse to "exclude parental spanking." He lamented the "purging of religious influence" from public schools. And he criticized federal tax credits for child care expenditures because they encouraged women to enter the workforce.

"Further expenditures would be used to subsidize a dynamic new trend of working women and feminists that is ultimately detrimental to the family by entrenching status-quo of nonparental primary nurture of children," he wrote.'


That's what CNN considers research? As far as I can tell, McDonnell's thesis had nothing but public policy proposals in it. There was no research into anything. Do they have any idea how this makes people perceive real research? How am I, a scientist-in-training, supposed to ever be able to tell any layperson that I do "research" too, and expect them to understand that what I do is as different from McDonnell's thesis as any two pieces of academic work can be? Is it any wonder the average non-college-educated American thinks that science and Christian science are kinda sorta pretty much the same thing?

I guess I might be hyperbolizing, but I see this kind of minor, subtle slip-up, where academia isn't even the focus of the news article, to be much more detrimental to the dissemination of academic understanding to the public than bad science writing. This is so small that the average person won't notice it enough to really think about the claim that McDonnell conducted research. Where a bad summary of a real research finding in the scientific press can cause laypeople to question the value of a field of study or a particular finding, or may misinform them about the finding itself, it will at least cause them to engage with and think about it. This kind of sloppy writing, on the other hand, both reflects and reaffirms incorrect public opinion about academia mostly without being consciously acknowledged, let alone challenged.