Psychology Research

Readers’ replies to “Zen, choice and procrastination” were insightful and stimulated further writing and learning on my part. Here are some important distinctions about changing our intentions or failing to act on them. I like the title of Clay Shirky’s book Here comes everybody .  He’s writing about the social effects of Web 2.0 where everyone can be a contributor to, not just a consumer of, Internet content. The blog replies here at Psychology Today are a small example of this – here comes everybody (well, not everybody, but thousands of people have read these blog entries, it’s quite the growing community!). I learn from everyone as I write this blog. It’s much like my teaching. It’s a journey with my students. This blog is a journey in learning with you. Of course I can’t reply to every blog-posting comment (even though I would like to). I also get emails from my own Web site www.procrastination.ca . Again, it’s simply not possible to keep up with replies, but I enjoy hearing your perspective on the issues I discuss – sharing is part of learning. This week, in reply to my posting East meets West: Zen, choice and Procrastination , there were two replies that stimulated my writing. I’m going to provide excerpts of each of these replies below and then add some comments of my own. What these readers replied to was the story of the unfulfilled intention to run. As you may recall from this blog entry , having set the alarm for 5 a.m. to go for a run, when the alarm goes off, you don’t feel like running now, so you go back to sleep instead. The readers’ replies focus on two things: 1) the notion of choice, and 2) the difference between intention-update and intention-failure. Here are excerpts from both readers. You can read their full replies here . Reader 1 (MS): ONLY A ROBOT WOULDN’T SEE OPTIONS OR CHOICE I think you’re right in that there need not be choice involved, BUT ONE HAD TO BE A ROBOT NOT TO SEE IMMEDIATELY THE OPTION JUMPING RIGHT AT YOU to stay in bed and exercise another day. So I would certainly have to make the choice. In this case it’s not so hard to actually make it because RUNNING GIVES ALSO IMMEDIATE GRATIFICATION. I always feel better afterwards although I’m not yet fit enough to reach a runner’s high. (emphasis of all uppercase added) Reader 2 (Carl): INTENTION-UPDATE OR INTENTION-FAILURE . . . there’s a difference! It sounds to me as though the “it’s about choice” people are seeing intention revision where you see intention failure. Obviously both phenomena are real and will need to be allowed for in any attempt at describing agency: changing your mind is clearly rational in some cases, and not all cases of going against earlier intentions can honestly be described as rational revision. Both weakness of will and intention-updating exist, the question is how to tell the difference between them . . . the run-don’t run case can’t be a rational case of intention-update because nothing is updated except the intention itself: no new information is gained overnight, we should’ve known for example that we’d likely not want to go for the run , etc etc. Nothing happened that was in anyway novel, we just wantonly decided to go against the earlier intention on the basis of shifting occurant desires. But if we take *that* as being a rational basis for decision-making, then we shouldn’t have been forming intentions in the first place. Rational updating requires new information or a new awareness of earlier error. That’s not present in the case you describe so as described we’re being irrationally inconsistent, plain and simple. Even so there’s a puzzle: the decision/intention-shift/gap being irrational doesn’t itself determine which of the decisions/intentions was the right/best/most rational one to have. I can say I was being irrational to go against the intention, or I can say I was irrational to form *that* intention in the first place (when I should’ve known how little it reflects what I will want when it’s time to carry it out). Either description seems possible: because we often form intentions out of externally derived guilt, wishful thinking or idealism borrowed from others which (if we thought about it) we don’t actually share. We’d need to know more about which intention coheres best with our long-term plans and goals… and therefore have a way to figure out what those are. END OF READER RESPONSES Wow. This is great. This is a discussion! We simply have to address these issues of whether it takes away from our humanity (becoming more like a robot) to exclude choice, and we need to make this crucial distinction between an intention-update (or change) that is rational and an intention-failure that is irrational (and  I have labeled procrastination). Perhaps the most rationale thing we can do is realize that the intention was irrational in the first place. If that’s the case, we have to examine goal setting, and I’ll do that too. I won’t do any of it in this entry, however. It’s long enough (and I write too much for a blog I’m told ☺). So, check in tomorrow where I’ll take on the difference between intention-update and intention-failure.

Have you ever looked at a piano keyboard and wondered why the notes of an octave were divided up into seven white keys and five black ones? After all, the sounds that lie between one C and another form a continuous range of frequencies. And yet, throughout history and across different cultures, we have consistently divided them into these set of twelve semi-tones. Now, Deborah Ross and colleagues from DukeUniversity have found the answer. These musical intervals actually reflect the sounds of our own speech, and are hidden in the vowels we use. Musical scales just sound right because they match the frequency ratios that our brains are primed to detect. When you talk, your larynx produces sound waves which resonate through your throats. The rest of your vocal tract -your lips, tongue, mouth and more – act as a living, flexible organ pipe, that shifts in shape to change the characteristics of these waves. What eventually escapes from our mouths is a combination of sound waves travelling at different frequencies, some louder than others. The loudest frequencies are called formants , and different vowels have different ‘formant signature’. Our brains use these to distinguish between different vowel sounds. Read the rest of this post… | Read the comments on this post…

A reader asks: What’s the hardest question you’ve gotten about the new book? Is there one you were totally unprepared to answer? This is a slightly embarrassing confession, but one of the most difficult questions I’ve been asked is also one of the most obvious. It goes something like this: “What practical knowledge have we gained by looking at decision-making in the brain that we didn’t already have, either through introspection or behavioral studies?” When I was first asked this question, I think I muttered something about the virtue of curiosity, breaking open the black box and fulfilling that ancient dictum “know thyself”. In other words, I completely avoided the query, like a slippery politician. While I think those are all valid motivations for neuroscience – there is something epic about trying to understand the three pounds of gelatinous flesh inside the skull – they also aren’t particularly practical. And I think it’s also worth pointing out (as I have before) that a tremendous amount of modern neuroscientific ideas have been presciently anticipated by everyone from David Hume to William James to Aristotle to Virginia Woolf. This shouldn’t be too surprising – introspection is a powerful investigative tool. David Hume, for instance, summarizes an awful lot of recent work on the importance of emotional signals during decision-making with this famous line: “Reason is and ought to be the slave of the passions and can never pretend to any other office than to serve and obey them.” So what’s the added benefit of neuroscientific explanations? If Hume was right, and James was such a genius, and we can learn so much from “mere” behavioral studies, then why bother with the amygdala or dopamine? The best answer, I think, is that learning about the brain can help constrain our theories. We haven’t decoded the cortex or solved human nature – we’re not even close – but we can begin to narrow the space of possible theories . We know, for instance, that the rational agent model of Homo Economicus isn’t particularly accurate, at least from the perspective of the brain, and that the deliberative prefrontal cortex is often out-shouted by emotional brain areas like the nucleus accumbens, insula, etc. This supports, of course, lots of observational studies that demonstrate that people rarely rely on explicit calculations of utility (or explicit calculations of anything, really) when making decisions. The anatomical details, in other words, can help settle the argument. Now this might seem rather underwhelming – all those pretty fMRI pictures just constrain our pre-existing theories? – but I actually think it’s rather essential. Consider Freud. The man had an uncanny talent for inventing elegant theories. He was a hypothesis machine, churning out one fantastic sounding idea after another. But which of these ideas are true? Here’s where neuroscience comes to the rescue. I think time and experiments have redeemed some of Freud’s fundamental theories – the unconscious drives much of our behavior, dreams aren’t random narratives, but actually regurgitate scenes and snippets from daily life, etc. – while other Freudian theories have largely fallen flat (your Mom probably isn’t responsible for most of your neuroses). We can take something as vague as the id and began shackling it to particular brain regions, like the aforementioned amygdala. (The prefrontal cortex is some fusion of the ego and super-ego.) By recording from hippocampal cells in the rat, scientists can begin to decode the function of dreams, and see how they’re a crucial component of memory consolidation. And so on. The point is that, while all of Freud’s theories might sound convincing, only a few of them are actually correct. In this sense, neuroscience is what helps us separate the beautiful theory from the definite truth. How would you answer the question? Read the comments on this post…

There’s been a ton of research on the impact of working memory: its importance in learning, its effect on math skills, and its relationship to other mental abilities. Yesterday’s entry on The Wild Side discusses working memory’s relationship with IQ. It’s been shown that adults can improve working memory with training, and training has even been shown to work for kids as young as seven. There are clearly tremendous benefits to working memory (and at least one down side ). A related mental function, inhibitory control, is also a key to many cognitive abilities. But if working memory training works for adults and school-age kids, could it also help even younger kids? What about inhibitory control? A team led by Lisa Thorell trained 35 4- and 5-year-olds on either working memory or inhibitory control for 15 minutes a day for five weeks. For working memory, kids saw objects appearing on a computer screen and had to click in the proper order and location they appeared in. The difficulty of the task gradually increased over the weeks. For inhibitory control, the preschoolers were trained on five different tasks, including the SART we’ve discussed recently . Here’s their progress on two of the tasks over the course of the training: Read the rest of this post… | Read the comments on this post…

A general assumption in the sports world is that athletes get better over time. Sprinters get faster, hitters hit more home runs, quarterbacks throw fewer interceptions, etc. And yet, there’s one sports statistic that has refused to budge: the percentage of free-throws made in the NBA. Here’s the NY Times , via Kottke: The consistency of free-throw percentages stands out when contrasted with field-goal shooting over all. In men’s college basketball, field-goal percentage was below 40 percent until 1960, then climbed steadily to 48.1 in 1984, still the highest on record. The long-range 3-point shot was introduced in 1986, and the overall shooting percentage has settled in at about 44 percent. Why can’t players learn to make their free throws? After all, it’s an uncontested shot; you can take as long as you need. Nobody is defending you or thrusting a hand into your face. It’s just you, a ball and the basket. That, I think, is the problem. An expert athlete largely performs on auto-pilot. Manny Ramirez doesn’t think about the mechanics of his swing and Kobe Bryant isn’t contemplating his jump-shot when he pulls up behind the arc in the 4th quarter. They are performers and they’re performing. They might think about these details during batting practice, or during warm-ups, but the best athletes cultivate a kind of mindlessness during the game itself. David Foster Wallace, in his glorious review of Tracy Austin’s horrific memoir of her tennis career, said it best: The real secret behind top athlete’s genius, then, may be as esoteric and obvious and dull and profound as the silence itself. The real, many-veiled answer to the question of just what goes through a great player’s mind as he stands at the center of hostile crowd-noise and lines up the free-throw that will decide the game might well be: nothing at all . At least, their conscious mind should be empty. In my book , I discuss some work done by Sian Beilock on the cognitive neuroscience of choking: Beilock uses putting on the golf green as her experimental paradigm. When people are first learning how to putt, the activity can seem daunting. There are just so many things to think about. Golfers need to assess the lay of the green, calculate the line of the ball, and get a feel for the grain of the turf. Then they have to monitor their putting motion and make sure that they hit the ball with a smooth, straight stroke. For an inexperienced player, a golf putt can seem unbearably hard, like a life-sized trigonometry problem. But the mental exertion pays off, at least at first. Beilock has shown that novice putters hit better shots when they consciously reflect on their actions. The more time they spend thinking about the putt, the more likely they are to sink the ball in the hole. By concentrating on their golf game, by paying attention to the mechanics of their stroke, they can avoid beginner’s mistakes. A little experience, however, changes everything. After golfers have learned how to putt⎯once they have memorized the necessary movements⎯analyzing the stroke is a waste of time. Their brain already knows what to do. It automatically computes the slope of the green, settles on the best putting angle, and decides how hard to hit the ball. Bradley Hatfield, a professor of kinesiology and psychology at the University of Maryland, has monitored the brain wave activity of expert athletes in the midst of performance. (Because the subjects have to wear a bulky plastic cap full of electrodes, Hatfield can only study golfers, archers and Olympic rifle shooters.) The brain waves of novice athletes exhibit a consistent pattern of activity, with lots of erratic spikes and haphazard rhythms. This is the neural signature of a mind that’s humming with conscious thoughts, as it pays attention to all sorts of irrelevant stimuli and bodily cues. The minds of experts, in contrast, look strangely serene. When they are performing their sport, they exhibit a rare mental tranquility, as their cortex deliberately ignores interruptions from the outside world. This is evidence, Hatfield says, of “the zone,” that trance-like mindset allowing experts to perform at peak levels. As the corporate motto says, the best athletes don’t think: they just do it. Beilock’s data further demonstrates the benefits of relying on the automatic brain when playing a familiar sport. She found that when experienced golfers are forced to think about their putts, they hit significantly worse shots. “We bring expert golfers into our lab, and we tell them to pay attention to a particular part of their swing, and they just screw up,” Beilock says. “When you are at a high level, your skills become somewhat automated. You don’t need to pay attention to every step in what you’re doing.” Now back to those free-throws. The very ease of the shot is why it’s so difficult. Because players are alone at the line with their self-conscious thoughts, they tend to think too much. The luxury of time turns out to be a curse. They remember all those pieces of advice from the shooting coach and start focusing on keeping a rigid wrist and holding the ball in the right place and making sure to follow through. And that’s when their shot falls apart. This is the perverse irony of free throws – trying to fix your shot just might destroy it. For instance, I remember watching Shaq struggle to break the 50 percent barrier. The more he tried to improve his free throws (or at least said he tried) the uglier his free throws became, until he was basically hurling the ball with one hand at the rim. Shaq is a world-class athlete, but he hasn’t improved his free throw percentage for the same reason the rest of the NBA hasn’t. I think this also explains why the best free throw shooters tend to have the most elaborate free throw rituals. They’ll lick their hand, grab their shorts, spin the ball, dribble it three times, etc. (Tennis players go through a similar routine before serving.) The purpose of these rituals should now be obvious: they help keep those self-conscious thoughts away, and allow players to segue into a more automated state of mind. Read the comments on this post…

Apologies, once again, for the blogging silence. I was busy in London, on tour for the UK version of the book, which is called ” The Decisive Momen t”. (We got some great press , including being featured as ” Book of the Week ” by BBC Radio 4.) Although book tours can, on occasion, be frustrating and grueling – I’m so sick of airport food that I don’t even like Egg McMuffins anymore, and I’m getting to the point where I detest the sound of my own voice – one of the genuine highlights is getting to answer questions from your readers. As an author, there is nothing more exciting than learning which parts of the book people find interesting and want to know more about or which points they disagree with or which stories resonate with their own experience. It’s the thrill of seeing your words enter the world, of seeing a mass of pixels in a word processor become a collection of ink blots on pages made from dead trees. And then, because these ink blots are arranged just so, they can enter the mind of someone else, so that your sentences get remixed and reanalyzed. A single idea, typed more than a year ago on a laptop keyboard, has multiplied itself into a swarm of ideas. One of the most interesting questions I’ve gotten while on tour goes something like this: “Given the massive decision-making flaws exposed by the current economic mess, what variables should scientists be investigating in the future so that we can better understand how we got here? In other words, what will be the hot topic in decision-making science two years from now?” Here’s my sputtering answer: I think the financial crisis has helped expose a powerful bias in human decision-making, which is our abhorrence of uncertainty . We hate not knowing, and this often leads us to neglect relevant information that might undermine the certainty of our conclusions. I think some of the most compelling research on this topic has been done by Colin Camerer, who has played a simple game called the Ellsberg paradox with subjects in an fMRI machine. To make a long story short, Camerer showed that players in the uncertainty condition – they were given less information about the premise of the game – exhibited increased activity in the amygdala, a center of fear, anxiety and other aversive emotions. In other words, we filled in the gaps of our knowledge with fright. This leads us to find ways to minimize our uncertainty – we can’t stand such negative emotions – and so we start cherry-picking facts and forgetting to question our assumptions. A similar phenomenon is also at work when we’re confronted with too many equivalent options, which is what happens to me every time I have to pick a toothpaste. There’s some suggestive evidence by Akshay Rao that this “trade-off aversion” – do I want the Colgate Total or the Crest Pro-Health? – leads to increased activation in areas that are often associated with cognitive conflict and the detection of errors, such as the anterior cingulate cortex. This helps explain why I start getting anxious whenever I near the toothpaste aisle of the supermarket. While Camerer’s experiment is fascinating, I’d love to see data from a more realistic set of experiments. Why not bring in actual investment bankers and watch how they respond to varying levels of information, or how giving them a quantitative model that’s supposed to assess risk (and thus remove the uncertainty) alters their decision-making process? Which brings me to Dennis Overbye’s fascinating analysis of “The Wall Street Physicists”. He looks at how the rise of quants bearing impossibly complicated mathematical formulas gave financial firms a new kind of confidence to engage in risky trades and investment innovations: The Black-Scholes equation resembles the kinds of differential equations physicists use to represent heat diffusion and other random processes in nature. Except, instead of molecules or atoms bouncing around randomly, it is the price of the underlying stock. The price of a stock option, Dr. Derman explained, can be interpreted as a prediction by the market about how much bounce, or volatility, stock prices will have in the future. But it gets more complicated than that. For example, markets are not perfectly efficient — prices do not always adjust to right level and people are not perfectly rational. Indeed, Dr. Derman said, the idea of a “right level” is “a bit of a fiction.” As a result, prices do not fluctuate according to Brownian motion. Rather, he said: “Markets tend to drift upward or cascade down. You get slow rises and dramatic falls.” One consequence of this is…that when you need financial models the most — on days like Black Monday in 1987 when the Dow dropped 20 percent — they might break down. The risks of relying on simple models are heightened by investors’ desire to increase their leverage by playing with borrowed money. In that case one bad bet can doom a hedge fund. Dr. Merton and Dr. Scholes won the Nobel in economic science in 1997 for the stock options model. Only a year later Long Term Capital Management, a highly leveraged hedge fund whose directors included the two Nobelists, collapsed and had to be bailed out to the tune of $3.65 billion by a group of banks. The collapse of LTCM is a microcosm of so many of the cognitive flaws that led us to the current mess. Because everybody at LTCM believed in the state-of-the-art model, few were thinking about how the model might be catastrophically incorrect. The hedge-fund executives didn’t spend enough time worrying about the fat tail events that might disprove their theories. Instead, they pretended that the puzzle of the marketplace had been solved – the uncertainty of risk had been elegantly quantified. Once this happens, we start making serious mistakes. The errors inherent in the model are compounded by our desire to prove the model right. Instead of using our reasoning powers to improve our predictions, we use reason to reassure ourselves, to rationalize away the warning signs of failure. Our sense of certainty – the model must be right – is dishonestly preserved. And so LTCM ignored the brewing troubles in the Asian markets. The executives discounted the rumors that Russia might default. They ruled out the possibility of a market meltdown, which led them to take massive risks that didn’t appear risky. Because LTCM was making decisions under the spell of certainty, they ended up making a series of dangerous decisions. Replace LTCM with, well, just about every major financial firm, and replace Russian and Asian markets with “subprime debt,” and it’s the same old story. Models can be a crucial decision-making tool, but they can also lead us to disaster. This isn’t the fault of the models, or even the quants – it’s the fault of all those executives who used these models they didn’t really understand to silence their amygdala, so that their fear of risk disappeared. They were certain there was little to worry about, which is generally a sign that we should start getting scared. Read the comments on this post…

If you wanted to turn a rat into a fearless critter , unfazed by cats or bigger rats, the best way would be to neutralise a small pair of tiny structures in its brain called the dorsal premammillary nuclei , orPMD. According to new research by Simone Motta at the University of Sao Paolo, these small regions, nestled within a rat’s hypothalamus , control its defensive instincts to both predators and other rats. But not all neurons in the PMD are equal. It turns out that the structures are partitioned so that different bits respond to different threats. The front and side parts (the ventrolateral area) are concerned with threats from dominant and aggressive members of the same species. On the other hand, the rear and middle parts (the dorsomedial area) process the threats of cats and other predators. And both areas are distinct from other networks that deal with the fear of painful experiences, such as electric shocks. This complexity is surprising. Until now, scientists have mostly studied the brain’s fear system by focusing on an area called the amydgala , which plays a role in processing memories of emotional reactions.   And they have generally assumed that fearful responses are driven by the same networks of neurons, regardless of the threat’s nature. There’s good reason to think that. Hesitating in the face of danger is a sure-fire way to lose one’s life, so animals respond in a limited number of instinctive ways when danger threatens. They freeze to avoid detection, flee to outrun the threat, or fight to confront it. These automatic ” freeze, fight or flight ” responses are used regardless of the nature of the threat. Rats, for example, behave in much the same way when they are menaced by cats or electrified floors alike, and actually find it very difficult to do anything else. This limited repertoire of action convinced scientists that animals process different fears in the same way, relying on the same network of neurons to save their hides from any and all threats. Motta’s research shows that this idea is wrong, certainly for rats and probably for other mammals too. The brain’s fear system isn’t a one-size-fits-all toolkit; it has different compartments that respond specifically to different classes of threats. Read the rest of this post… | Read the comments on this post…

An article on the psychological characteristic of vicious dog owners has just appeared online in the compelling academic publication, The Journal of Forensic Sciences , finding that those who who own dangerous dogs are more likely to endorse antisocial and psychopathic character traits and more likely to report criminal behaviour. The study was led by psychologist Laurie Ragatz who collected data from 869 college students who completed an anonymous online questionnaire assessing type of dog owned, criminal behaviors, attitudes towards animal abuse, psychopathy, and personality. It’s only a correlational study but the introduction has a nice summary of the research findings as well as a previous study on the same topic: Each year, 4.7 million people are bitten by dogs, of which 386,000 are seriously injured and over 200 die. Several dog breeds have been labeled “vicious” or of “high-risk” for aggression. To date, only one empirical study has examined the characteristics of persons who choose to own their high-risk dogs. Barnes et al. reports that owners of Akitas, Chow-Chows, Dobermans, Pit Bulls, Rottweilers, and Wolf-mixes endorsed approximately 10 times more criminal convictions than owners of nonvicious dogs. Further, vicious dog owners reported more crimes involving aggression, children, alcohol, and domestic violence than owners of nonvicious dogs. The current research sought to replicate and extend these findings with a college sample. The present study compared nondog owners and owners of vicious, large, and small dogs on engagement in criminal behavior, general personality traits (i.e., impulsive sensation seeking, neuroticism-anxiety, aggression-hostility, activity, and sociability), psychopathy, and attitude towards animal maltreatment. …As hypothesized, a significant difference in criminal behavior was found based on dog ownership type. Owners of vicious dogs were significantly more likely to admit to violent criminal behavior, compared to large dog owners, small dog owners, and controls. The vicious dog owner sample also engaged in more types (i.e., violent, property, drug, and status) of criminal behavior compared to all other participant groups. Personality traits were examined and vicious dog owners were significantly higher than controls on impulsive sensation seeking. Examining psychopathic traits, owners of high-risk dogs endorsed significantly more characteristics of primary psychopathy (e.g., carelessness, selfishness, and manipulative tendencies) than small dog owners. Comparing owners of vicious dogs to other groups, no significant differences were found regarding secondary psychopathy (e.g., impulsiveness or self-defeating behaviors) or attitudes towards animal maltreatment. Among the college sample, the vicious dogs were predominantly male and weighed 68 pounds. The owners had more self-reported overall criminal behaviors as well as violent criminal behavior. They endorsed significantly more sensation seeking and primary psychopathic traits. Link to article. Link to DOI entry for same.

That question has an answer: they crouched like birds. A 198 million year old fossil trackway from Utah has preserved a print of a theropod dinosaur taking a break, resting with hands curled inward and knuckle down, and legs bent. Except for the forelimbs, of course, it’s very birdlike. Restoration of Early Jurassic environment preserved at the SGDS, with the theropod Dilophosaurus wetherilli in bird-like resting pose, demonstrating the manufacture of SGDS.18.T1 resting trace. Here’s the section of the trace fossil they used to reconstruct the animal’s posture. A, Overhead, slightly oblique angle photograph of SGDS.18.T1 resting trace. Note normal Eubrontes track cranial to resting traces (top center) made by track maker during first step upon getting up. Scale bar equals 10 cm. B, Schematic of SGDS.18.T1 to scale with A: first resting traces (manus, pes, and ischial callosity) in red, second (shuffling, pes only) traces in gold, final resting traces (pes and ischial callosity) in green, and tail drag marks made as track maker moved off in blue. Note long metatarsal (“heel”) impressions on pes prints. C, Direct overhead photograph and D, computerized photogrammetry with 5 mm contour lines of Eubrontes trace SGDS.18.T1. Color banding reflects topography (blue-green = lowest, purple-white = highest); a portion of the berm on which the track maker crouched is discernible. Abbreviations: ic = ischial callosity, lm = left manus, lp = left pes, rm = right manus, rp = right pes, td = tail drag marks. Milner ARC, Harris JD, Lockley MG, Kirkland JI, Matthews NA (2009) Bird-Like Anatomy, Posture, and Behavior Revealed by an Early Jurassic Theropod Dinosaur Resting Trace . PLoS ONE 4(3): e4591. doi:10.1371/journal.pone.0004591 Read the comments on this post…

We’ve reported before on brain imaging research that shows brain activity in those in a ‘persistent vegetative state’. What I didn’t know until today was that one subject in this research, Kate, has since woken up. This YouTube video tells Kate’s story: Kate suffered from what was probably brain stem encephalitis at the age of 23. She was the first patient to be scanned by Adrian Owen as part of his research into the mental lives of those in persistent vegetative states. Findings from this research support what Kate herself is able to say in the video: we need to be very careful before making life and death decisions on behalf of people who appear unresponsive.