Neuroethics and fMRI

Here’s a sociologist worrying that we’ll be classifying kids on the basis of their fMRI:

At the annual meeting of the American Sociological Association in 1968, the social activist Martin Nicolaus leveled a blistering critique at traditional criminologists and sociologists. He said — and I am paraphrasing here because it was a panel discussion, not a paper — you people have your eyes down and your hands up, while you should have your eyes up and your hands down.

He was speaking language that social scientists of the era would have easily understood. “Eyes down” meant that almost all the research on deviance and crime was focused on the poor and their behavior, while “hands up” meant that the support for such research was coming from the rich and powerful — from foundations, the government, and corporations. Conversely, of course, “eyes up” meant turning one’s research focus to the study of the pathological behavior of the elite and privileged, and “hands down” meant giving more of a helping hand to the excluded, impoverished, and disenfranchised. What was true of the social scientists’ almost monomaniacal attention to the deviance of the poor in the 1960s is even truer of the neuroscientists of the last decade’s vanguard research.

A common tactic is to do brain scans on people who have already displayed violent or aggressive behavior. While this will net the adolescent boys in juvenile correctional facilities, it will surely miss the spawning white-collar bandits in energy markets or subprime home loans.

This is from the Chronicle of Higher Education. You can see where this is going can’t you? Let’s brain scan Hank Paulson. Somehow I don’t think that’s going to happen.

Jim

Goldilocks on Wall Street

Greetings to all. I am the new Chair of the Dep’t. of Computational Social Science at the Krasnow Institute for Advanced Study at George Mason. Jim has graciously invited me to contribute to his blog. I am an economist with broad interests in economic theory and policy, behavioral economics (how people depart from perfectly rational behavior), cognition (thus my Department’s natural connection to Krasnow), and computation (my Ph.D. is from Carnegie Mellon).

Under normal circumstances I would comment here on matters of basic research and science policy. But the current financial environment is sufficiently grave that I will take the liberty of discussing the proposed bailout of Wall Street.

For the last year or so banks have been sufficiently worried about the risks posed by the mortgage-related assets of their peers that most interbank lending has become expensive (as measured by the so-called TED spread, for instance). Indeed, in the past couple of weeks such interbank activity has nearly dried up—this is the ‘credit crunch.’ Such short term lending is an important activity in the day-to-day operations of major banks, and its demise has led to the Fed providing short term credit facilities to keep overnight and other short term lending and borrowing going. But what we don’t really know (yet) is just how bad bank balance sheets look. It is reasonable to assume that many are weak—thus the urgency with which bailout legislation has been crafted and voted on—but just how weak is not known. The big problem, as I see it, is that bank solvency is not really knowable ex ante, i.e., before a rescue plan is implemented. Here’s why:

Economists are wont to focus on prices to explain the inner workings of the economy. An important part of proposed bailout/rescue plans is use of certain auction mechanisms in order to ‘discover’ the proper prices for ‘toxic’ mortgage-backed securities and related financial assets that troubled firms wish to take off their balance sheets. The functioning of these auction mechanisms is critical to the performance of the bailout, but the exact nature of these mechanisms is not yet specified. Indeed, there is a ‘Goldilocks’ flavor to how such auctions have to function in order to relieve the credit crunch. Currently there is no market for the most toxic of these assets—they are illiquid and their value may be very close to $0. If a government auction for them produces very low prices for such assets then the troubled banks selling them will benefit little from such sales and may be made insolvent. If these auctions produce prices that are too high then taxpayers will be on the hook in a big way and banks will get recapitalized from a true government bail out—welfare for Wall Street even though these same institutions have earned staggering profits in recent years. Instead of auction prices that are either too low or too high it is hoped that the Treasury auctions find prices right in the middle, sufficient to keep the banks operating and thus restoring confidence so interbank lending can resume at reasonable rates. Thus Goldilocks.

The trouble with this whole approach to finding the ‘right’ price for a particular mortgage-backed security (MBS)/collateralized debt obligation (CDO) is that the real determinant of the value of the underlying mortgage assets depends on the health of the overall economy. If the near term recession is mild or even non-existent then stable home prices would result, meaning higher auction prices for distressed mortgage-related securities would be in order. If a longer, deeper recession is in the cards then lower auction prices for MBS/CDOs are justified, even though this would likely ‘take out’ several large banks. In the case of a big recession/depression then the value of many mortgage-related assets is probably close to $0 and many banks will be insolvent.

If one looks at the economy in a static equilibrium way, as is conventional in economics, then one might say there are multiple equilibria in the picture I have laid out: low housing prices and insolvent banks represent one equilibrium and higher housing prices and stabilized institutions are another. Unfortunately, unless one has a reasonably accurate model telling you the effect of a bailout on the real economy, it is going to be guesswork as to which kind of bailout plan leads to which equilibrium. In an economy with multiple equilibria, a specific bailout plan, in essence, selects the final outcome for the economy by picking prices paid for ‘toxic’ securities. Prices that are too low might in advertently ‘kick’ the economy down to a deep recession or depression equilibrium.

The real problem, it seems to me, is that we have only the crudest understanding—zeroth-order models and gray beard guesses—for the overall effect of alternative bailout plans on the real economy. The great 20th Century Economics Nobelist Herbert Simon often argued that we, as a nation, need much more support for basic research in the social sciences. Imagine the ‘return on investment’ today from a few million dollar research program that had created a reasonably-accurate, quantitative model of the current financial system? Maybe it would be saving us a few trillion dollars right now.

Reverse engineering the brain: not to be taken literally

There’s been some angst among fellow scientists about the use of the above term to describe the current attempts to use experimentation and computational neuroscience together particularly in the context of robotics. The worry is that if we can’t reverse engineer the worm C. elegans or the sea snail, Aplysia–which we can’t at present–then we certainly aren’t in a position to reverse engineer the aspects of higher cognition (e.g. spatial navigation) that are interesting about mammalian brains–especially our own.

I agree with the worriers in that, the prospects of building a robot with fully human-like capabilities is not in the near future. Where I disagree is with the notion of setting a scientific agenda that uses the principles of reverse engineering to build up (incrementally) an understanding of how aspects of higher cognition emerge from neuronal activity. An example of very productive work in this field can be seen in the research coming out of Gerry Edelman’s Neuroscience Institute in La Jolla where computational neuroscience models interact with the real noisy environment. Jeff Krichmar’s work there (he’s now at UC Irvine) is an excellent example of this approach.
And so, when the idea of reverse engineering the brain comes up, from my perspective it is as a metaphor. As far as actual reverse engineering of brains, this will happen in the worm or the fly long before it becomes an actual possibility for vertebrate brains. But the term is a useful metaphor for an approach, whereby experimentally determined characteristics of real brains can be applied to real life engineering problems–like creating better autonomous vehicles.
Jim

Meeting Daniel Schorr somewhat by accident

I had signed up to attend Daniel Schorr’s lecture yesterday evening at the Cosmos Club. There was a reception and in typical fashion, my wife and I picked a table in the very back of the Powell lounge to enjoy some cheese and wine before the lecture. A few minutes after sitting down, an elderly gentleman sat down at our table and introduced himself as Dan Schorr. And so we began to talk about the current financial crisis, foreign policy and Mr. Schorr’s NPR reports. He is really a remarkable journalist–of the old Edward R. Murrow school.

Only in Washington.

Jim

I wonder if this is true with Amazon’s Kindle?

Regarding reading words from your computer screen, from the Chronicle of Higher Education….Money quote:

people took in hundreds of pages “in a pattern that’s very different from what you learned in school.” It looks like a capital letter F. At the top, users read all the way across, but as they proceed their descent quickens and horizontal sight contracts, with a slowdown around the middle of the page. Near the bottom, eyes move almost vertically, the lower-right corner of the page largely ignored. It happens quickly, too. “F for fast,” Nielsen wrote in a column. “That’s how users read your precious content.”

Scientists talking to the media

Here’s a great piece from SCIENCE with some concrete advice on the challenges of being a scientist and having to talk with members of the media about your work. 

The bottom line: there’s a lot of opportunities for things to go wrong, but if you don’t take the chance, someone else will explain your science and probably bumble the job.
Jim

Chronicle on Woods Hole

Here’s an interesting piece from The Chronicle Review by Sam Kean on my favorite marine lab, the MBL in Woods Hole….

Money quote:

This writer soon discovers what Olds means, about both the science and the embarrassment. I’d never seen a sea urchin before, and in short, there’s no easy way to sex them. During a class I’m probing one — a black, spiky tennis ball — with a syringe, looking for soft spots around its (I think) mouth. Injecting seawater supposedly forces it to spew sperm or eggs out its (I think) rear, at the top. He/she is hard to pierce, like sticking needles through a leather work glove, but I drive it home.

Problem is, urchin sperm and eggs look alike at first. After many long days in the lab, my brain is fried. And I’m taking only a dumbed-down version of the core “discovery” class on embryology. In the nicest possible way, our instructors laugh and say my class has no idea what graduate students go through.

Beyond the question about sea urchin reproduction, the piece raises some questions concerning MBL compared with its Long Island neighbor, Cold Spring Harbor Laboratory.

But what Cold Spring had for years that MBL didn’t was the director James Watson, co-discover of the double-helix structure of DNA (and a former summer faculty member at the marine lab). Watson had pretty much stopped working in labs by 1968, when he took over at Cold Spring, but his name and vision drew many eager, hungry scientists. Cold Spring started off with no more than MBL had, possibly less, but has since jumped into a different stratosphere: In 2006, it raised $90-million from private donors, compared with the marine lab’s $12.5-million.

Borisy hopes to add new facilities soon, possibly in biodiversity and regenerative medicine, both of which Maienshein says fit neatly with a marine lab. Scientists also praise Borisy’s new programs in fields like microscopy, a traditional strength at MBL.

But the education laboratories need up to $15-million worth of work first. Plus, the marine laboratory’s core strengths — teaching and providing summer venues for scientists — cost more than they bring in, and probably won’t inspire the proverbial little old lady to donate a million dollars. The education certainly won’t wither away or face cuts, says Borisy. But however much scientists adore the place for what they learned there, some are resigned that the MBL of 30 years ago may not look the same in another 30.

I’m not sure I agree with Sam Kean regarding the fairness of the comparison. CSHL’s focus on molecular biology was being driven by an economic engine that gave us the likes of Amgen and Genentech. That revolution is now behind us I think. A new revolution will have as its engine the need to address the challenges of climate change, microbial diversity and energy security. MBL may end up better placed with its existing strengths combined with some judicious investments.

Jim