just wanted to announce that Michael Pardo and Dennis Patterson have graciously agreed to participate in an on-line reading group here on The Law and Neuroscience Blog later this fall.  We have yet to formally set the date, but once we do I will post the official dates and times.  For now, I just wanted to say a few things about this exciting event.  First, as many of you know, Pardo and Patterson have recently written two widely discussed papers which approach the gathering field of neurolaw with a very critical eye:

1. Pardo, M. and Patterson,D. Forthcoming. “Philosophical Foundations of Law and Neuroscience.” The University of Illinois Law Review.
2. Pardo, M. and Patterson, D. Forthcoming. “Minds, Brains, and Norms.” Neuroethics.

More news to come, of course, and I’m sure I’ll have some thoughts on the subject to share.

That large-heartedness – that concern and regard for the plight of others – is not a partisan feeling.  It is not a Republican or a Democratic feeling.  It, too, is part of the American character.  Our ability to stand in other people’s shoes.  A recognition that we are all in this together; that when fortune turns against one of us, others are there to lend a helping hand.  A belief that in this country, hard work and responsibility should be rewarded by some measure of security and fair play; and an acknowledgement that sometimes government has to step in to help deliver on that promise.

…

You see, our predecessors understood that government could not, and should not, solve every problem.  They understood that there are instances when the gains in security from government action are not worth the added constraints on our freedom.  But they also understood that the danger of too much government is matched by the perils of too little; that without the leavening hand of wise policy, markets can crash, monopolies can stifle competition, and the vulnerable can be exploited.  And they knew that when any government measure, no matter how carefully crafted or beneficial, is subject to scorn; when any efforts to help people in need are attacked as un-American; when facts and reason are thrown overboard and only timidity passes for wisdom, and we can no longer even engage in a civil conversation with each other over the things that truly matter – that at that point we don’t merely lose our capacity to solve big challenges.  We lose something essential about ourselves.

Congressional Democrats may have capitulated to the idea that the moral case for health reform is politically nonviable and, if that’s what it takes to pass legislation, I can’t condemn them.  But that doesn’t mean that we should forget the argument altogether.  If we can escape the suffocating echo chamber of craven Washington politics, the moral case for action is quite strong.

There are many facets to the argument, but one of the strongest is drawn from empirical evidence.  A long-standing, but perhaps not all that well known, research finding is that one’s socioeconomic status in early life is a strong predictor of health outcomes throughout adulthood and old age.  This relationship holds through the exclusion of any number of potentially confounding variables, including physical activity, diet, smoking, occupation, and any number of others.

Scientists have long suspected that there is a critical period in early life for the fine-tuning of the stress-response system in our bodies, and that low early life class can cause disruptions in its function that remain for the duration of one’s life.  A paper published recently in the Proceedings of the National Academy of the Sciences offers evidence that supports this theory.

A group of researchers lead by Gregory Miller from the University of British Columbia examined differences in the expression of certain genetic factors in subjects who had different early life social statuses to search for evidence of altered stress response and immune system function.  In particular, they looked at genes involved in control of the autonomic nervous system and glucocorticoid receptors.

Despite dramatically different early life experiences, the subjects in this study were identically matched in current socioeconomic status as well as a variety of lifestyle factors.  Nevertheless, there were significant differences both in genetic expression and in hormonal function.  Early life misfortune manifested in what the researches called “the adoption of a defensive phenotype,” with higher levels of circulating stress hormones (despite identical perceived stress), elevated autonomic nervous system signaling, and compromised immune function.

The consequences of these biological changes are both real and serious: increased risk of infectious, respiratory, and cardiovascular disease.  Fortunately many of the subjects in this and other similar studies had managed to move up in life, and might be able to afford the medical treatments they will be cursed with.  Others, however, are not so lucky, and with the ever-accelerating income inequality in this country, even more will continue not to be.

Senator Kennedy’s older brother, when speaking at Amherst College in his last public address as President of the United States, remarked that “there is inherited wealth in this country and also inherited poverty.”  This remains true, only now we know that along while some inherit estates, others inherit a lifetime of disease.

I respect the conservative commitment to individual responsibility, but I don’t see how you can look at this science and yet fail to see the moral case for increased collective responsibility in tending to the sick.  It proves that the goal of egalitarian policy is not just the fulfillment of an abstract moral code but the achievement of real consequences for the lives of other Americans. Liberals should care about fairness not as an end in itself but as a means to the end of making the world a better place for others.

And I believe we can do it.  The main focus of this blog is how we might understand our own nature.  Concluding his speech at Amherst, President Kennedy shared Robert Frost’s thoughts on this subject:

Take human nature altogether since time began,
And it must be a little more in favor of man,
Say a fraction of one per cent at the very least,
Our hold on the planet wouldn’t have so increased.

Miller, G., Chen, E., Fok, A., Walker, H., Lim, A., Nicholls, E., Cole, S., & Kobor, M. (2009). Low early-life social class leaves a biological residue manifested by decreased glucocorticoid and increased proinflammatory signaling Proceedings of the National Academy of Sciences, 106 (34), 14716-14721 DOI: 10.1073/pnas.0902971106

It’s surprising, because our brains are essentially massively parallel processing machines.  Even the simple activity of gazing out at the ocean in total bliss requires the coordination of millions of perceptual processes.  When it comes to large-scale goal directed attention or action, however, we struggle to do more than a single thing at once.  A paper published last month in Neuron looked into the brain activity associated with multitasking and attempted to understand why.

A research group at Vanderbilt led by Paul Dux studied the changes that occur when people learn to perform two different tasks–a visual-manual task and an auditory-vocal task–at the same time.  fMRI brain scanning revealed that no areas of the brain respond only when the two activities are undertaken together. In other words, there is no part of the brain explicitly devoted to handling multitasking.  The researchers did find, however, that many regions of the brain were involved in these tasks but that only one, the left inferior frontal junction (IFJ), was more active when they were performed together.

The subjects in this experiment initially found it very difficult to multitask, but they got better with training.  The researchers thus looked at what was happening in the IFJ when these improvements were made to understanding how multitasking works in neural tissue.  They considered three separate hypotheses, each of which made different claims about the neural response to multitasking training.

In the first story, we get better at multitasking because the processing moves away from the slow abstraction of the prefrontal cortex to direct inflexible circuits linking sensory and motor areas.  To test this theory, the researchers looked at the effective connectivity between the regions involved in this task.  Even with training, however, there was no strengthening in the direct circuits between perception and response.  The information was still passing through the IFJ, it was just doing so more quickly.

A second hypothesis, then, was that dedicated circuits formed within the IFJ to segment and accelerate multitasking processes.  Dux and his colleagues performed a pattern classification analysis to evaluate this theory.  Pattern classification works by teaching a computer algorithm to discriminate between the brain response associated with different activities.  According the this second theory, classification performance should improve if the IFJ develops dedicated pipelines to handle the individual requirements of the multitasking procedure.

In fact, however, classification performance slightly decreased with training, indicating that the second hypothesis was also false.  This result does suggest, though, that there were some sort of changes within the IFJ, so the researchers turned to the third hypothesis.  They scanned several additional subjects using high temporal resolution fMRI focused just within the IFJ both before and after multitasking training.

With this new fine-grained data, the researchers were able to reach the conclusion that training leads to gains of efficiency in the central processing module within the IFJ.  The degree of improvement in reaction time corresponded to the acceleration in IFJ processing as revealed by fMRI. This shows that, even though the brain is massively parallel, complicated behaviors must  pass through this bottleneck before they can be executed.

Can this knowledge help us learn to multitask better?  Of course, we probably don’t need anyone to be talking or texting while driving.  But there are plenty of endeavors where better multitasking could be valuable.  An interesting application of this research, on the neurotechnology horizon, would be using real-time fMRI to train people to multitask and let them directly “see” the improvements in their IFJ.  Either way, I found this paper fascinating, and if nothing else it shows how the rapidly expanding toolbox of cognitive neuroscience is allowing us to examine more complicated and interesting questions than we once thought possible.

Dux, P., Tombu, M., Harrison, S., Rogers, B., Tong, F., & Marois, R. (2009). Training Improves Multitasking Performance by Increasing the Speed of Information Processing in Human Prefrontal Cortex Neuron, 63 (1), 127-138 DOI: 10.1016/j.neuron.2009.06.005

But the public’s skittishness about overhauling the system also reflects something else: the deep-seated psychological biases that make people resistant to change. Most of us, for instance, are prey to the so-called “endowment effect”: the mere fact that you own something leads you to overvalue it. A simple demonstration of this was an experiment in which some students in a class were given coffee mugs emblazoned with their school’s logo and asked how much they would demand to sell them, while others in the class were asked how much they would pay to buy them. Instead of valuing the mugs similarly, the new owners of the mugs demanded more than twice as much as the buyers were willing to pay. The academics Ziv Carmon and Dan Ariely showed the same thing in a real-world experiment: posing as ticket scalpers, they phoned people who had entered a raffle to win tickets to a Duke basketball game. People who hadn’t won tickets were willing to pay, on average, a hundred and seventy dollars to get into the game. But those who had won tickets wanted twenty-four hundred dollars to part with them. In other words, those who had, by pure luck, won the tickets thought the ducats were fourteen times as valuable as those who hadn’t.

Also playing a role in Surowieki’s explanation is rampant status quo bias, and, while he doesn’t mention it, I’d throw a health dose of risk aversion into the mix (although that’s somewhat linked with the endowment effect).

When you think about it, it’s probably not too surprising that emotions are running so high.  It’s banal to observe that health care is deeply personal and cuts right to our most deeply rooted survival instincts, but it’s still true.  You can’t really blame the people who were whipped into a frenzy last fall over Barack Obama’s putative “palling around with terrorists” to feel uneasy with letting the man make decisions about health care–despite how unsubstantiated claims about the actual level of government intervention in health care itself actually are (and let’s not forget that Research 2000 poll showing the broad overlap between “birthers”–people committed to the idea that Obama is secretly a foreign national–and those who believe the “death panel” rumors).

Wrap this up with evidence that conservatives are dispositionally inclined towards a stronger threat response, and this mess becomes somewhat more understandable.  Don’t get me wrong, I’m just as dismayed and disgusted by where we are as anyone else who supports reform, but I do think we should countenance the argument that it’s largely a product of our flawed psychologies.  Somehow I find myself feeling mildly sympathetic towards the town-hall nuts, and even though I’m not exactly sure where to go from there, admitting our weaknesses is probably a good first step.

For a bit of brief background, Lynch argues that we’re on the brink of a paradigm shift where basic neuroscience research and the nascent field of neurotechnology will fundamentally alter almost every dimension of the world we live in.  It’s an ambitious thesis, for sure, but probably not a startling one if you’re the type that reads this blog.  Even if it sounds somewhat premature, Lynch’s point is that the revolution is coming, and, even if we’re not exactly sure what form it is going to take, it’s best to get ready for it.

Obviously I agree with all of this.  At the same time, I feel as if the mechanics of the revolution are likely to take a somewhat different course than the one Lynch charts out.  It’s hard to miss the sense of empty trendiness about the many neuro-ized words (for lack of a better term) that mark the movements of his argument: neuroeconomics, neurofinance, neuromarketing, neurolaw, neurowarfare, neuroenhancement, etc.  There was a moment in the talk when, on introducing the fourth or fifth of these terms–I forget which one–he seemed to lose the audience a little bit.

Which is not to say that I don’t think neuroscience will inform economics, law, or even warfare.  Clearly, I do.  But, precisely because I believe the revolution is going to be so thorough and fruitful, it’s not going to take the form of a laundry-list of buzzwords.  The maturation of the biological study of decision-making, for instance, is not a world where universities house a Neuroeconomics department alongside the traditional Economics faculty, but one where the study of economics naturally draws from neuroscience research.  Likewise, the study of neurolaw will not stand outside that of jurisprudence or criminal procedure; instead, legal debate will turn on the insights neuroscientists can offer about guilt, harm and responsibility without causing any sort of fuss.

To offer an analogy, consider how nobody really talks about “dot-coms” or “e-commerce” anymore.  What was new and shiny and reeking of hype only a decade ago has now become just the standard way of operating.  It’s much more noteworthy now to be a company that doesn’t do business online than to be one that does.  I suspect a similar process will occur as the neuro revolution plays out, although this analogy strikes me as limited in several ways so I wouldn’t follow it too far.

This shift will occur because neuroscience will–and already does–challenge our intuitions and alter our fundamental understanding of ourselves.  Esoteric philosophical debates about reductionism and elimitivism aside, the still-surprising notion that the brain is the seat of all our thoughts and actions will become commonplace, and we will start to see brain research as a more powerful and accurate, but not actually all that revolutionary, means to answer questions we already are asking.

Or so I hope.  Of course, in a country where less than half of the population believes in evolution–and, if you look at what people actually think Darwin’s theory entails, that number drops below 10%–it might be asking too much for neuroscience, which is equally if not more existentially challenging than evolution, to gain the necessary breadth of acceptance for the neuro revolution to really succeed.

Something I’ve debated much and still don’t have an answer for is exactly how widespread that acceptance will have to be.  In some cases, such as with neuroeconomics or finance, it might be sufficient for only an engaged elite to reach a full understanding.  The situation is more fraught in the domain of neuroenhancement or law, which necessarily draw from the mores of society at large.  What’s troubling is that many of the implications of neuroscience are not just novel but often deeply counter-intuitive.  But this is probably a question for another post, if not a book.

Again, I want to stress that I haven’t read the book, so I could have gotten the wrong impression from the hour and a half or so that I heard Lynch talk about his ideas.  This isn’t really meant as a criticism; if anything, I’m taking what Lynch was arguing and going a step further.  But, in line with my support for the project, I think this analysis might actually help the neuro revolution avoid the natural skepticism that greets potential hype.  In any case, I’m certainly enthralled to see such vibrant discussions of these topics.  Obviously I’m intellectually exercised by them, but I completely agree with Lynch that the neuro revolution is on the horizon, in some form, and it’s best we prepare.

In the broader neuroeconomic project of moving the determinants of economic choice from abstract theory into the circuits of the brain, an important step will be to account for the cause of this marginal calculation.  Despite its centrality to economic thought, however, previous studies have paid it little attention.  A paper published last month in The Journal of Neuroscience, however, reveals subtle signals in the brain regions previously known to drive economic choice that correspond to the computation of marginal value.

A group at the Wellcome Trust Center and University College, London lead by Alex Pine and Raymond Dolan examined the neural correlates of marginal and intertemporal difference in economic behavior.  They scanned the brains of their participants while they repeatedly chose between different amounts of money that would be available at different points of time in the future.  To ensure realistic decision-making, the subjects received a gift-card corresponding to their choice in a randomly selected trial that was activated at the prescribed time.

This paradigm has been used in many neuroeconomic studies before, but the researchers here engaged in a novel strategy of analysis to reveal the effects of marginal calculation on brain activity.  From the behavioral results, which revealed a clear pattern of diminishing marginal utility (for example, subjects cared less about the difference between $45 and $46 than they did about the difference between $5 and $6), they built an economic model for each participant that revealed his or her individual rates of marginal and intertemporal discounting.

By applying this model to the shifts in blood flow measured by fMRI, the researchers found different response patterns that correlated to separate economic factors.  The activity of some brain regions tracked only the pure dollar amount of each reward or the effects of delayed receipt, but a response within an area called the dorsal striatum–an area commonly implicated in economic valuation–correlated with the integration of these signals into a single unit of marginally and temporally discounted valuation.

That a circuit including the striatum is involved in decision-making is well established (and see here and here for other research drawing on that knowledge), but this study begins to bring into focus the subtleties of neural computation within this large structure that truly determine behavior.  The rapidly maturing field of neuroeconomics is already moving past where gross localization research is useful, and this paper is valuable for demonstrating how increasingly intricate microeconomic models can illuminate–and draw from–brain research.

Pine A, Seymour B, Roiser JP, Bossaerts P, Friston KJ, Curran HV, & Dolan RJ (2009). Encoding of marginal utility across time in the human brain. The Journal of neuroscience : the official journal of the Society for Neuroscience, 29 (30), 9575-81 PMID: 19641120

Karl Rove — Obama and the Permanent Campaign: Turning Critics into Enemies isn’t Presidential

Robert Trivers — The Elements of a Scientific Theory of Self-Deception

In the meantime, here’s a quotation to chew over.  My roommate is a consultant, and he brought home some abandoned books from the office the other day.  I was paging through one, called The Evolution of Financial Services, which looks to be a report put out by Oliver Wyman (and written by Niall Ferguson) sometime in the fall of 2007.  Paging through, this caught my eye in the introductory overview:

Imporovements in Risk Management

The consensus view is that aided by regulation and innovative financial products, financial institutions have raised their risk management techniques to a level of sophistication and effectiveness never seen before.  For example, firms are now using derivatives and other tools to diversify balance sheet risk through the purchase of credit default swaps (CDS).

As Figure 5 shows, outstanding CDSs have grown from next to nothing 10 years ago to more than $20 TN today.  Firms are seeking to remove risk from the balance sheet altogether through the sale of repackaged asses such as mortgage-backed securities (MBS) and asset-back securities (ABS).  New entities like conduits and Structured Investment Vehicles (SIVs) have emerged, whose primary purpose is to trade these instruments.  While regulatory demands are a burden to financial institutions, new techniques and instruments have allowed banks to lower their risk profiles significantly. 

Not sure if this needs any comment…

This year, however, it’s not just been the opponents of the policy who have relied on the “mellifluous language of the standard economic theory of markets.” It’s been the advocates of reform. Ask yourself what the administration’s one-line goal is on health-care reform. Is it “equal treatment for everybody?” Is it “if every American is guaranteed a lawyer, why not a doctor?” Is it even “guaranteed health care for everyone?”

No. It’s “bend the curve.” And the problem with “bending the curve” is that it’s a broadly testable proposition. This is, in part, why the Congressional Budget Office’s skeptical assessments pose such a threat to health-care reform. If the White House’s primary objective was health care for every American, or guaranteed care that you could keep even if you lost your job, or choice of insurance plans for every American, you could spend a bit more on health care and say you were achieving your goal. But if you say that the point of health-care reform is to save money, and then the outfit charged with estimating such things says it won’t, that strikes at the heart of the project.

There are basically two points operating together here.  The first, which Ezra draws out, is about confused messaging.  The center of the venn diagram of the bills floating around Congress is legislation that does a pretty good job of offering coverage to everyone and a mediocre job at controlling costs.  Yet, Ezra points out, the messaging out of the White House is all about “bending the curve” and cutting our long-term spending.  I think this is basically true, but it also ignores the perhaps more interesting question: why does the moral case for health care disappear so easily?

Perhaps things would be different if the administration were making its case to the broader public in the language of moral imperatives.  (And, for the record, I do believe it should be the moral imperative of a modern society to ensure health care for all citizens).  But why do congressmen and commentators so quickly dismiss the reality of increased coverage as they haggle over the numbers?  The Blue Dogs are barking rather loudly about cost–particularly with regard to subsidies–but when you follow these complaints to their logical conclusion, they’re arguing that fewer people should have access to health care (or, depending on how the math words, that certain people should have access to less health care).

Imagine that one night a stranger, bloodied from a car accident, knocked on one of these congressman’s door and asked for help.  Were the congressman to refuse and leave the stranger to die on his stoop–or even just to suffer all night until a good Samaritan  passed by–he would be met with universal opprobrium.  Such a decision would be a noxious affront to our moral sensibilities.  And yet, when congressmen take action that, however indirectly, leads to similarly adverse health outcomes for real people, they are praised by institutions of Washington commentary for their centrism and fiscal prudence.

To understand why this happens, it’s worthwhile to consider the (oft-discussed on this blog) work of Joshua Greene in the field of moral psychology.  I won’t spend too much time rehashing the details–for the uninitiated, see my earlier posts or Professor Greene’s website–but the basics are that our moral intuitions often cut in very different ways about situations that have similar consequences but different mechanisms.  Actions that involve close, personal interaction arouse–pushing someone off a footbridge into the path of an oncoming trolley or failing to help the man on our stoop–arouse our moral emotions and move us to express harsh condemnation.  Actions taken at a distance, however, are viewed more calculatingly, which often leads us to a different judgment.

When I worked in Professor Greene’s lab, we used to joke that some of the more complicated scenarios we employed to probe the moral sense seemed almost absurdly complex.  In one example, the protagonist pulls a switch that drops a workman through a trapdoor onto the path of an oncoming trolley, causing a collision that sounds an alarm and stops a separate trolley that would otherwise mow down five other workmen.  Compare that to the almost insane-looking chart of our current health care apparatus (chart thanks to the indispensable Jon Cohn).

The effect of those dense coils of arrows is to wring all of the moral responsibility from the system.  Although it’s true that the decisions of individual congressmen will lead to very real differences in the health outcomes of actual people, the path those decisions must take is far too convoluted for that fact to impress upon the emotional brain.  I’ve also theorized–but haven’t yet been able to test–that just using the language of costs and benefits shifts the brain into a mode that blunts the influence of moral intuition.  We certainly can put moral concerns up against fiscal ones, but I suspect that even if the White House had tried this it would have had limited effect.  Eye-deep in congressional procedure, it’s almost impossible to think in intuitively moral terms.

That said, the key word is “almost.”  There’s still a sound argument that it’s our absolute imperative to provide health care for all Americans.  Morality is on our side.  But it is not obviously so.  My recommendation for the August recess is to try to make a case for reform so that the public, as much as is possible, understands the moral consequences of the legislative process.

What we have today, however, is knowledge of increasingly complex individual components of the complete physical explanation for the human experience.  To stretch my Apollo metaphor from last week perhaps near its breaking point, it might be fair to say that the field is currently in the “Gemini” stage.  Each Gemini mission demonstrated that individual components of a lunar mission–extra-vehicular activity, orbital rendezvous, docking–were even possible before they could all be woven into the fabric of a full-fledged moonshot.

Likewise, contemporary investigations at the cellular level of the brain attempt to understand core processes in isolation.  I mentioned a critical example in my post about the Blue Brain project last week, and I felt like I should giv e it more attention because it’s an example of an important step towards the ultimate goal (also, because I finally got around to reading the paper).  The study in question was published earlier this month in The Journal of Neuroscience. Authored by Chung-Chuan Lo, it’s the result of a collaboration between the labs of Jeffery Schall at Vanderbilt and Xiao-Jing Wang at Yale.

Schall’s lab has long been involved in understanding the neural basis of cognitive control.  They study the activity of individual neurons in the brains of rhesus macaques as the monkeys perform a seemingly simple task.  The animals are trained to stare at a central point until it disappears, replaced by a new point in the periphery of the animal’s vision.  To get a reward, the monkey just has to look at the new dot.  There’s a catch, though.  Some of the time, the central dot will reappear.  On those trials, the monkey will be rewarded only if it restrains itself from looking to the side.

So the task seems simple, but the processes it recruits are central to our ability to perform goal-directed or intentional actions.  After-all, if we couldn’t inhibit strong habitual responses in the service of an abstract goal, we’d be nothing more than zombies or automatons.  But any responsible neuroscientist could tell you that it’s wrong to think of habits or instincts encoded in our brains as being controlled by “our minds,” as if the two are separable.¹  Which is not to say that it’s easy to understand how they are the same thing.

Schall’s research has identified several classes of neurons thought to be involved.  Some fire when the middle fixation point is present and cease activity when it vanishes.  Others demonstrate a steady increase in activity between that time and when the monkey looks towards the second point.  On trials when the middle point reappears, the first type of neurons rapidly start firing again.  When the monkey successfully restrains itself, the second type of neurons quickly calm down.  Schall has proposed that the decision whether to move is the result of a competition between two independent processes, a GO process and a STOP process, that are apparent in this activity.

The obvious limitation to this approach is that it looks at single cells in isolation.  Of course, there are thousands of neurons involved in this behavior, and the relevant interactions between those neurons can only be inferred from the individual data.  This is where Wang’s work comes in.  Wang’s lab focuses on biophysically realistic modeling of neural circuits.  His models are considerably simpler than the Blue Brain, but the dynamics of each individual “neuron” are carefully tuned to mimic their real-life counterpart.

Wang’s model for this experiment consisted of a handful of discrete groups of several hundred simulated neurons in the circuit.  As suggested by the neurophysiological research, one group responds to the central stimulus and restrains movement, while another group responds to the peripheral stimulus and initiates it.  The first group are further influenced by a “top-down” signal that modulated the level of control in the circuit.  This signal likely arises from the prefrontal cortex, and it probably demonstrates the effects of conscious attention-focusing.

The neural network model, when properly tuned, exactly duplicated the behavioral results of actual monkeys performing the task.  This makes a strong case, in other words, that attempts at self-control result in a competition between independent processes and that the amount of top-down control biases the competition appropriately.

What’s really interesting, though, is looking at the circuit as a whole.  Because of the nature of the model, it acts like a dynamic system that exhibits attractor dynamics around one of the two outcomes.  That’s a way of saying that it produces large-scale coordinated across the hundreds of simulated neurons that was never intentionally programmed into the model.  Each “neuron” was tuned individually, but the way they act together to produce a movement emerges naturally.  It’s likely that this is what’s going on in the Blue Brain video when you see spontaneous waves of activity sweep across the simulated neocortical column after only a few silicon cells are activated.

So this paper models control without actually controlling the model.  The Wang model shows that a mechanistic system, based pretty closely in the actual brain, can control itself, at least in response to an external stimulus.  The next step will be to show that such a system can control itself based on completely internal guidance.  And, in doing so, we’ll step closer and closer to understanding the whole brain and, thus, ourselves.

Lo, C., Boucher, L., Pare, M., Schall, J., & Wang, X. (2009). Proactive Inhibitory Control and Attractor Dynamics in Countermanding Action: A Spiking Neural Circuit Model Journal of Neuroscience, 29 (28), 9059-9071 DOI: 10.1523/JNEUROSCI.6164-08.2009

¹ Of course, there are some neuroscientists who would tell you the mind and the brain are separable, and it’s not as if they’re irresponsible or shoddy scientists, but I do happen to think that they’re wrong.

Most people think that, in a situation where they could act dishonestly to get ahead without any fear of getting caught, they would be able to act honestly but would have to actively fight temptation to do so.  A competing theory holds that honest people genuinely lack any feeling of temptation, and they just do what comes naturally and also happens to be the morally right thing to do.

A paper coming out in next week’s edition of the Proceedings of the National Academy of the Sciences (available as an early edition here; subscribers only) tests these two ideas by examining what’s going on in the brains of people when they cheat or act morally.  fMRI lie detection has received quite a bit of funding and attention recently, and it’s one of the more imminent examples of applied neuroscience research.  Despite that, most fMRI lie detection studies are marked by a potentially critical flaw: the experimenters must ask the participants to lie rather than catching in a moment of genuine dishonesty.

Joshua Greene and Joe Paxton at Harvard* recently devised a clever experimental design to experimentally test authentic dishonesty.  Participants thought they were taking part in a study examining paranormal abilities, and their task in the scanner was simply to make guesses about a basic coin flip.  Half of the time, they recorded their guess ahead of time, but the other half of the time they just told the experimenters whether they had been right or wrong (under the guise of an experiment to test the effect of privacy on predictive ability).

Unless you put credence in the interpretation that paranormal abilities actually exist–and, weirdly enough, the PNAS editors chose not to–some of the subjects turned out to be dirty rotten cheaters.  A group of fourteen participants claimed a success rate above 69%, with a mean of 84%.  If you’re into statistics, the p-value on that actually happening is less than 0.001.  In contrast, another group of 14 scored 52% on the trials when they reported their guesses after knowing the outcome.  In other words, it’s safe to assume that these people were being honest.

One way of examining the act of lying is to look at reaction time data.  The honest group displayed no significant difference in reaction time to a prompt in the trials when they made their predictions before the flip and on those when they reported them after.  The dishonest group also had no difference between those two types of trials when they reported a win, but it took them longer to indicate their choice when they were indicating after the flip that they had lost.

More revealing, though, were the fMRI data.  If it were the case that honest behavior requires the active suppression of a desire to cheat, Greene and Paxton predicted, you would expect to see increased activity in the cognitive control network–roughly, the dlPFC, anterior cingulate cortex, and posterior parietal cortex.  This network responds in all sorts of studies that ask participants to overcome some prepotent habit or desire.  Honest subjects, though, displayed no such effect.  Dishonest subjects, on the other hand, showed more activity in exactly this network.  And the more often subjects cheated, the stronger this effect was.

This is just a preliminary study, designed mostly to establish the validity of this experimental method.  As such, we should proceed with caution when interpreting exactly what these results mean (of course, that should always be the case with fMRI).  The control network activity could be the result of calculations about whether or not to cheat on individual trials (in the hope, theoretically, that the experimenters wouldn’t begin to doubt their paranormal abilities for being just too good).  It might also reveal that cheaters do attempt to control their urges but, more often than not, ultimately fail.

It seems relatively safe to say, however, that these results support the somewhat counter-intuitive theory that good people are such because they are free of temptation, not because they succeed in quelling it.  Certainly, this study opens up lots of really interesting questions.  What’s different about people who don’t feel the allure of the easy buck?  Can this experimental design tell us more about how to use fMRI for genuine lie detection–most current methods are no more reliable than polygraphy.  And, finally, if we can learn why people act dishonestly, can we come up with better ways of convincing them to stop?

Greene, J., & Paxton, J. (2009). Patterns of neural activity associated with honest and dishonest moral decisions Proceedings of the National Academy of Sciences DOI: 10.1073/pnas.0900152106

*For the purposes of disclosure and whatnot, I was working in the Greene lab while the research for this study was going on, but I had very little to do with it.

As exciting as Markram’s work is, I think that still might be a little ambitious.  Then again, this ambition reminds me of President Kennedy in 1962 declaring the goal of landing a man on the moon by the end of that decade.  I’ll keep my eye out for a link to the Ted talk if they decide to put it online soon, but in lieu of that, here’s the timeless clip of Kennedy challenging the country to greatness:

Gives me chills.  (Link to the full speech, if you’re interested, is here).

Hat tip to Mo from Neurophilosophy.

Now, before considering that question, it’s wise to stress an obvious difference.  The space program was, for the most part, an endeavor of applied science, in contrast to the class of basic scientific investigation that modern neuroscience belongs to.  (Which is not to discount the farther-off promise of applied neuroscience, whether in the case of curing psychiatric or neurodegenerative disease or allowing locked-in patients to communicate and potentially regain mobility).  The commonality for me rests in the ability of each, one demonstrated, the other hypothetical, to inspire awe and transcendence while nevertheless remaining rooted in naturalistic science and entirely physical methods.

Before Darwin, of course, the locus of the great debate between science and religion was in the question of Earth’s relation to the rest of the universe.  The truth is that our planet is but one of several revolving around a star that is, itself, insignificant among the uncountable multitude of others.  This conclusion conflicted with our deeply held intuitions about the primacy of our experience.  Perhaps even moreso than Neil Armstrong’s famous words, the most indelible contribution of the Apollo program might be the striking “Earthrise” photograph taken by the crew of Apollo 8.  It starkly reveals the reality that everything we know and cherish resides on a tiny blue marble dwarfed by the immensity of the universe.  This realization, however, was undaunting, as it was paired with inspiring proof of the power of mankind’s ambition when paired with our capacity for scientific reason.

As some have observed, neuroscience has the potential to similarly threaten deeply held beliefs.  Most neuroscientists and philosophers believe that the maturation of our field will yield an understanding of how our intellect, our imagination, and our morality are the products of a physical system, that there is no “ghost in the machine.”  The implications for religious dogma about the soul are obvious, but, as Paul Bloom has argued, we’re all wired to find this conclusion somewhat shocking and unsettling.

At the same time, neuroscience seems to captivate the public in much the same way as did the early years of manned space flight.  This has, at the moment, troubling consequences for those of us interested in the quality of scientific journalism, but I believe it could pay off in the long-run.  We can only benefit if the quest to uncover the nature of the mind is viewed as an grand achievement of reason rather than as a duplicitous assault of secularism.  Neuroscience is also helped along by the air of glitzy cutting-edge technology, although I fully assume that the current fMRI machines and methods will one-day seem like the Mercury spacecraft: crude progenitors of the true marvels to come.

There are other differences, of course.  Neuroscience is a diffuse field, and there’s not a clear, singular goal like landing on the moon.  Understanding consciousness, perhaps, but the difference is we don’t even understand what that’s going to look like.  And there are no political or nationalistic implications.  It should be obvious that I don’t mean the comparison literally.  Nevertheless, in terms of what the undertakings meant for the relationship between scientific enterprise and the existential truths we hold dear, I think there are clear parallels.

Mankind has always looked outwards; we have always been driven to exploration, and we have always looked towards the heavens.  At the same time, though, we have looked inwards and obsessed over our true nature.  Before Apollo came Magellan and Columbus, to say nothing of the first homo sapiens who decamped from Africa for the fertile crescent.  And likewise, the history of literature and philosophy is one of struggling with the source of wisdom and of the passions.  Neuroscience will, I believe, one day represent the pinnacle of this latter project.

I, for one, hope that the exciting work my colleagues are doing will one day be for others what the accomplishments of NASA are for me today: a source of beauty and inspiration.

Which is why I found this working paper (here’s a link to the PDF) from Harvard Business School so interesting.  It argues that much of legislative impotency can be attributed to loss aversion, which is the idea in behavioral economics that we fear potential losses far more than we desire equivalent gains.  Thinking about higher taxes or decreased services as losses, this would seem to explain the behavior of Congress rather well.  A relatively modest idea like capping the deductability of charitable donations for the wealthiest income brackets (at a level equal to that enjoyed by lower brackets, mind you) is a political non-starter, even when doing so could help pay for universal health insurance.

To combat this problem, the researchers propose “policy bundling,” in which bills that would impose political costs are bundled with other bills that shirk those costs to lessen the effects of loss aversion.  In the example offered by the paper, a program that will cut jobs to protect wildlife is bundled with a similar program that allows logging (or whatever) to continue in a separate location, providing a net job gain.  The idea, I suppose, is that the second program was going to get passed anyway (it certainly would in the Senate), whereas the first one would have a much more difficult time on its own.  The authors supported their idea by performing a behavioral experiment, with subjects acting as legislators, that both confirmed the theory of loss aversion and supported the idea that a particular type of policy bundling can alleviate it.

I suppose the direct application to initiatives like health-care or Waxman-Markey are less clear, as those bills are already thick bundles of many individual components.  Still, Congress’s relative inability to act responsibly on large measures is outweighed only by its complete inability to do so on smaller ones, so I still see a lot of promise in this approach.  And, even if the policy bundling idea bears no fruit, I’m completely behind the application of behavioral economics to congressional action.  There are many institutional problems, to be sure, but let’s not forget that lawmakers are flawed human beings, just like the rest of us.

Update:  Whoops.  Link to the pdf now active.  Read it!

Upsate #2:  Much bigger whoops.  The original link was to the wrong Harvard study.  Links should all be fixed now.  (Here was what I accidentally linked to, by the way, which is certainly an interesting paper in its own right.)

It’s a short WSJ piece on the research of Henry Markram’s lab, where researchers have created a complete, biophysically accurate simulation of a neocortical column from the rat brain in silicon.  The simulation exhibits the sort of independent coordinated waves of activity that are likely going to be understood one day as a central element of consciousness and intentional action.  Obviously, we’re still far away from that understanding, but this sort of work is the way to get there.

Here’s the accompanying article in the Wall Street Journal.

And here’s a link to a paper (subscribers only, unfortunately) published just today in the Journal of Neuroscience reporting on the computational dynamics of similar coordinated activity, and how it might underlie the capacity for self-control (Update: I’ve now blogged this paper here).

Update: I can’t seem to get the video to embed properly, but you can watch it here.

One thing worth noting is that even when restraint can be identified as the best strategy, it’s often emotionally difficult to choose this path. When someone comes after you, you get angry. You want to respond in an intelligent and effective manner, yes, but there’s also a desire to do something that will make you feel better. And lashing out as per the Ledeen Doctrine (”Every ten years or so, the United States needs to pick up some small crappy little country and throw it against the wall, just to show the world we mean business”) often can achieve that goal. And of course there’s a risk that members of Jay-Z’s camp who urge a policy of restraint will be accused of actively harboring pro-Game sympathies or otherwise failing to manifest a sufficient degree of loyalty.

Rap, international strategy, surely there must be a neuroscience angle somewhere in here.  The key point is Yglesias’ observation that “it’s often emotionally difficult to choose this path.”  It’s worth thinking about why we have those emotions in the first place, and that’s where neuroscience and psychology come in.

Emotions are a quick and dirty way to get an animal to act reliably in a particular manner under certain circumstances.  We don’t, of course, know exactly what emotions are like in non-human animals, but it’s safe the assume that they play some role in those animal possessing the same neurological structures implicated in our own passions.  Whether or not they’re widely experienced in the animal kingdom, however, they certainly played a central role in our development as a social species.

Emotions are somewhat more complex than habitual or instinctual reactions, but they’re far less sophisticated than what you might call our intellect.  To be sure, there is advantage in this simplicity.  Unlike cognitive control and deductive reasoning, emotions don’t burn through cognitive resources.  They prompt swift action unfettered by the niggling uncertainty that accompanies any serious attempt at analysis.  As for whether emotions or reason are objectively better?  It’s probably a pointless question.  They’re different animals, and each is better in the proper circumstances.

Increasingly, however, we find ourselves in circumstances that favor reason.  Lynch has highlighted two such instances.  I don’t really know much about rap, so I’ll stay away from that one.  But in the IR case, it’s clear.  When you actually sit down and think about it, it becomes unarguable that the emotional response is the wrong one.  If you want to get really technical and fully employ the powers of our neocortex, you can think about it in game theory terms.

International relations are not a zero-sum game.  We got angry after 9/11, and we tried to pick Iraq up and throw it against the wall.  Unsurprisingly, this did not go as well as planned.  Even if the post-Saddam occupation hadn’t been such a mess, the war weakened our alliances with the rest of the western world and severely alienated those in the Muslim world that might have otherwise been sympathetic.  We eliminated a country that was in no serious way a threat.  And on the Iraqi side, although Saddam Hussein was for sure a blameworthy dictator, it would be difficult to argue that life has been better these past 6 years for the majority of the Iraqi population, to say nothing of the thousands who lost their lives as collateral damage.

A more principled approach would surely not have lead to the Iraq war.   But the problem with intellect and emotion is that, even when they are opposite, they are not inverse.  Becoming persuaded that your emotions are wrong often does little or nothing to make them go away.  We can learn to control our emotions–it seems that this is a central role of the dlPFC–but the fact remains that it’s hard.  It requires constant effort.  And, perhaps most troublingly, there’s no real correlation between how wrong the emotion is and how easy it is to overrule.

Of course, the problem of sensationalism and technical illiteracy is endemic to science writing (and I would strongly recommend this Bloggingheads diavlog from the past weekend that discusses the depressing state of scientific understanding and science journalism).  But neuroscience research undeniably draws a special degree of attention–we’re of course fascinated with understanding ourselves, and the technological glitz of fMRI seemingly promises the ultimate means of accomplishing that–and so it likewise carries a greater responsibility to communicate the facts fully and accurately.

One ubiquitous fault in the popular discussion of neuroscience, which even the NPR piece stands guilty of, is the use of the phrase “lights up” to describe what putatively involved brain regions are doing during some activity.  I hate this phrase, and I wish it could be forever expunged from the vocabulary of science writers.  I’d be extremely interested to hear where this idiom was invented, but it’s not hard to see why it’s so common: the pretty “spot on brain” pictures appear to capture neural tissue flashing like a beacon.  In reality, though, those figures are just a way of communicating the result of a statistical test comparing activity between two conditions.

If we’re right about fMRI, of course, a well-designed experiment will lead to one or several brain regions doing something interesting, and they might even experience more activity, as the “lights up” trope implies.  The problem with the image, though, is that there is electrical activity going on all over your brain at all times.  And fMRI does not even measure this activity, it measures blood flow.  From increased neural firing to a rush of oxygenated blood, out through the magnet to a computer, transformed by a half-dozen measures of pre-processing and than statistical analysis, the steps between brain activity and finalized neuroimaging data are many and large.  Talking about brain activity as “lighting up” and implying that the pretty pictures accompanying your article show this happening only serves to reinforce a misleading perception of how the science works.  It’s easy to understand why science journalists lean so heavily on that phrase.  Talking about what’s really going on in a way that isn’t confusing or boring–or probably both–is really quite difficult.  It’s snappy and concise to say that “your fusiform face area lights up when you look at a face.”  On the other hand, “compared to baseline or the viewing of inanimate objects, viewing a face stimulus is associated with increased BOLD (blood oxygen level dependent) signal in voxels centered around the putative fusifrom face area on the ventral temporal lobe” is liable to make any copy editor cringe.  And even that explanation elides all of the various decisions made in the processing of the data that play a causal role in the discovery of scientific conclusions.

Don’t get me wrong: I believe fMRI holds great potential.  Already, the young field is starting to move past relatively simple “spot on brain” type experimental designs to sophisticated pattern classification, functional connectivity analyses, multimodal imaging with DTI (diffusion tensor imaging–a method that determines the extent of structural connectivity between different regions) and other cutting edge techniques that show significant promise in expanding what we can do with a brain scanner.  And we’re likely going to learn that many of our early theories were wrong, perhaps to the degree where they seem foolish.  Remember how physicists used to be convinced that we all existed in the ether?

Ultimately, I’m sure that neuroscience is the means to unlock all of the deep secrets about our nature.  But there are a whole host of reasons we should be wary of getting ahead of ourselves.  Ill-gotten scientific “conclusions” have, in the past, been extorted to nefarious ends, and there is not insignificant potential of the same with brain research.  Too much sensationalism also runs the risk of a disillusioned public, who will give the field up for quackery long before we get to the real answers.  But perhaps most importantly, science is fundamentally about the pursuit of truth.  Even without a risk of negative consequences, to ignore truth is to betray the very nature of science.  Without that, what’s the point?

Pretty brain image via http://prefrontal.org