Neuroskeptic readers will know that I'm a big fan of theories. Rather than just poking around (or scanning) the brain under different conditions and seeing what happens, it's always better to have a testable hypothesis.I just found a 2007 paper by Israeli computational neuroscientists Niv et al that puts forward a very interesting theory about dopamine. Dopamine is a neurotransmitter, and dopamine cells are known to fire in phasic bursts - short volleys of spikes over millisecond timescales - in response to something which is either pleasurable in itself, or something that you've learned is associated with pleasure. Dopamine is therefore thought to be involved in learning what to do in order to get pleasurable rewards.But baseline, tonic dopamine levels vary over longer periods as well. The function of this tonic dopamine firing, and its relationship, if any, to phasic dopamine signalling, is less clear. Niv et al's idea is that the tonic dopamine level represents the brain's estimate of the average availability of rewards in the environment, and that it therefore controls how "vigorously" we should do stuff.A high reward availability means that, in general, there's lots of stuff going on, lots of potential gains to be made. So if you're not out there getting some reward, you're missing out. In economic terms, the opportunity cost of not acting, or acting slowly, is high - so you need to hurry up. On the other hand, if there's only minor rewards available, you might as well take things nice and slow, to conserve your energy. Niv et al present a simple mathematical model in which a hypothetical rat must decide how often to press a lever in order to get food, and show that it accounts for the data from animal learning experiments.The distinction between phasic dopamine (a specific reward) vs. tonic dopamine (overall reward availability) is a bit like the distinction between fear vs. anxiety. Fear is what you feel when something scary, i.e. harmful, is right there in front of you. Anxiety is the sense that something harmful could be round the next corner.This theory accounts for the fact that if you give someone a drug that increases dopamine levels, such as amphetamine, they become hyperactive - they do more stuff, faster, or at least try to. That's why they call it speed. This happens to animals too. Yet this hyperactivity starts almost immediately, which means that it can't be a product of learning.It also rings true in human terms. The feeling that everything's incredibly important, and that everyday tasks are really exciting, is one of the main effects of amphetamine. Every speed addict will have a story about the time they stayed up all night cleaning every inch of their house or organizing their wardrobe. This can easily develop into the compulsive, pointless repetition of the same task over and over. People with bipolar disorder often report the same kind of thing during (hypo)mania.What controls tonic dopamine levels? A really brilliantly elegant answer would be: phasic dopamine. Maybe every time phasic dopamine levels spike in response to a reward (or something which you've learned to associate with a reward), some of the dopamine gets left over. If there's lots of phasic dopamine firing, which suggests that the availability of rewards is high, the tonic dopamine levels rise.Unfortunately, it's probably not that simple, as signals from different parts of the brain seem to alter tonic and phasic dopamine firing largely independently, and this would mean that tonic dopamine would only increase after a good few rewards, not pre-emptively, which seems unlikely. The truth is, we don't know what sets the dopamine tone, and we don't really know what it does; but Niv et al's account is the most convincing I've come across...Niv Y, Daw ND, Joel D, & Dayan P (2007). Tonic dopamine: opportunity costs and the control of response vigor. Psychopharmacology, 191 (3), 507-20 PMID: 17031711... Read more »
Niv Y, Daw ND, Joel D, & Dayan P. (2007) Tonic dopamine: opportunity costs and the control of response vigor. Psychopharmacology, 191(3), 507-20. PMID: 17031711
Brain maturation continues for longer than previously thought - well up until age 30. That's according to two papers just out, which may be comforting for those lamenting the fact that they're nearing the big Three Oh.This challenges the widespread view that maturation is essentially complete by the end of adolescence, in the early to mid 20s.Petanjek et al show that the number of dendritic spines in the prefrontal cortex increases during childhood and then rapidly falls during puberty - which probably represents a kind of "pruning" process. That's nothing new, but they also found that the pruning doesn't stop when you hit 20. It continues, albeit gradually, up to 30 and beyond.This study looked at post-mortem brain samples taken from people who died at various different ages. Lebel and Beaulieu used diffusion MRI to examine healthy living brains. They scanned 103 people and everyone got at least 2 scans a few year years apart, so they could look at changes over time.They found that the fractional anisotropy (a measure of the "integrity") of different white matter tracts varies with age in a non-linear fashion. All tracts become stronger during childhood, and most peak at about 20. Then they start to weaken again. But not all of them - others, such as the cingulum, take longer to mature.Also, total white matter volume continues rising well up to age 30.Plus, there's a lot of individual variability. Some people's brains were still maturing well into their late 20s, even in white matter tracts that on average are mature by 20. Some of this will be noise in the data, but not all of it.These results also fit nicely with this paper from last year that looked at functional connectivity of brain activity.So, while most maturation does happen before and during adolescence, these results show that it's not a straightforward case of The Adolescent Brain turning suddenly into The Adult Brain when you hit 21, which point it solidifies into the final product,Lebel C, & Beaulieu C (2011). Longitudinal development of human brain wiring continues from childhood into adulthood. The Journal of Neuroscience, 31 (30), 10937-47 PMID: 21795544Petanjek, Z., Judas, M., Simic, G., Rasin, M., Uylings, H., Rakic, P., & Kostovic, I. (2011). Extraordinary neoteny of synaptic spines in the human prefrontal cortex Proceedings of the National Academy of Sciences DOI: 10.1073/pnas.1105108108... Read more »
Lebel C, & Beaulieu C. (2011) Longitudinal development of human brain wiring continues from childhood into adulthood. The Journal of neuroscience : the official journal of the Society for Neuroscience, 31(30), 10937-47. PMID: 21795544
Petanjek, Z., Judas, M., Simic, G., Rasin, M., Uylings, H., Rakic, P., & Kostovic, I. (2011) Extraordinary neoteny of synaptic spines in the human prefrontal cortex. Proceedings of the National Academy of Sciences. DOI: 10.1073/pnas.1105108108
A new paper in the Journal of Neuroscience investigates the neural basis of humour: Why Clowns Taste Funny.The authors note that some things are funny because of ambiguous words. For example:Q: Why don’t cannibals eat clowns?A: Because they taste funny!Previous studies, apparently, have shown that these kinds of jokes lead to activation in the lIFG (left inferior frontal gyrus), although it's also involved in processing ambiguity that's not funny, and indeed, language in general.In this study they gave people fMRI and played them audio clips of sentences that were either funny or not, and that either contained ambiguity or not. Examples of non-funny ambiguity included crackers like this:Q: What happened to the post?A: As usual, it was given to the best-qualified applicant.They found that, relative to straightforward ones, ambiguous sentences led to increased activation in two areas, the lIFG and also the left ITG. That fits with previous work.By contrast, funny stimuli, whether ambiguous or not, sent the brain into overdrive, with humour causing activation all over a wide range of hilarious areas such as the amygdala, ventral striatum, hypothalamus, temporal lobes and more.Many of these areas are known to be involved in emotion and pleasure, although some are fairly random such as visual area BA19.There were strong associations between BOLD signal change and funniness in the midbrain, the left ventral striatum, and the left anterior and posterior IFG.The problem is, like so many neuroimaging studies, it's not clear what this adds to our understanding of the topic. All this really shows is that linguistic ambiguity activates language areas, and enjoyable stimuli activate pleasure areas (amongst many others); it doesn't tell us why some things are funny.So more research is needed, and future neuro-humour studies will need a new set of neuro-jokes in order to maximize the laughs. Here's a few I came up with:Q: Why did the chicken cross the road?A :Because of activation in the motor cortex, causing muscle contractions in his legs.Q: What neuroimaging methodology is most useful for studying the brains of cats and dogs?A: PET scanning.Knock knock.Who's there?John.I doubt that. The 'self' is an illusion. The concept of 'John' as an individual is incompatible with modern neuroscience.Bekinschtein TA, Davis MH, Rodd JM, & Owen AM (2011). Why Clowns Taste Funny: The Relationship between Humor and Semantic Ambiguity. The Journal of neuroscience : the official journal of the Society for Neuroscience, 31 (26), 9665-71 PMID: 21715632... Read more »
Bekinschtein TA, Davis MH, Rodd JM, & Owen AM. (2011) Why Clowns Taste Funny: The Relationship between Humor and Semantic Ambiguity. The Journal of neuroscience : the official journal of the Society for Neuroscience, 31(26), 9665-71. PMID: 21715632
A couple of months ago I pointed out that a Letter published in the American Journal of Psychiatry, critiquing a certain paper about antidepressants, made very similar points to the ones that I did in my blog post about the paper. The biggest difference was that my post came out 9 months sooner.Well, it's happened again. Except I was only 3 months ahead this time. Remember my post Clever New Scheme, criticizing a study which claimed to have found a brilliant way of deciding which antidepressant is right for someone, based on their brain activity?That post went up on July 21st. Yesterday, October 19th, a Letter was published by the journal that ran the original paper. Three months ago, I said -...there were two groups in this trial and they got entirely different sets of drugs. One group also got rEEG-based treatment personalization. That group did better, but that might have nothing to do with the rEEG......it would have been very simple to avoid this issue. Just give everyone rEEG, but shuffle the assignments in the control group, so that everyone was guided by someone else's EEG...This would be a genuinely controlled test of the personalized rEEG system, because both groups would get the same kinds of drugs... Second, it would allow the trial to be double-blind: in this study the investigators knew which group people were in, because it was obvious from the drug choice... Thirdly, it wouldn't have meant they had to exclude people whose rEEG recommended they get the same treatment that they would have got in the control group...Now Alexander C. Tsai says, in his Letter:DeBattista et al. chose a study design that conflates the effect of rEEG-guided pharmacotherapy with the effects of differing medication regimes...A more definitive study design would have been one in which study participants were randomized to receive rEEG-guided pharmacotherapy vs. sham rEEG-guided pharmacotherapy.Such a study design could have been genuinely double blinded,would not have required the inclusion of potential subjects whose rEEG treatment regimen was different from the control, and would be more likely to result in medication regimens that were balanced on average across the intervention vs. control arms.To be fair, he also makes a separate point questioning how meaningful the small between-group difference was.I'm mentioning this not because I want to show off, or to accuse Tsai of ripping me off, but because it's a good example of why people like Royce Murray are wrong. Murray recently wrote an editorial in the academic journal Analytical Chemistry, accusing blogging of being unreliable compared to proper, peer-reviewed science.Murray is certainly right that one could use a blog as a platform to push crap ideas, but one can also use peer reviewed papers to do that, and often it's bloggers who are the first to pick up on this when it happens.Tsai AC (2010). Unclear clinical significance of findings on the use of referenced-EEG-guided pharmacotherapy. Journal of psychiatric research PMID: 20943234... Read more »
Tsai AC. (2010) Unclear clinical significance of findings on the use of referenced-EEG-guided pharmacotherapy. Journal of psychiatric research. PMID: 20943234
A study claims that it's possible to immunize against cocaine: Cocaine Vaccine for the Treatment of Cocaine Dependence in Methadone-Maintained Patients. But does it work? And will it be useful?The idea of an anti-drug vaccine is not new; as DrugMonkey explains in his post on this paper, monkeys were being given experimental anti-morphine vaccines as long ago as the 1970s. This one has been under development for years, but this is the first randomized controlled trial to investigate whether it helps addicts to use less of the drug.Martell et al, a Yale-based group, recruited 115 patients. They all used both cocaine and opiates, and were given methadone treatment to try to reduce their opiate use. The reason why the authors chose to focus on these patients is that the methadone keeps people coming back for more and makes them less likely to drop out of the study, or as they put it, "retention in methadone maintenance programs is substantially better than in primary cocaine treatment programs. We also offered subjects $15 per week to enhance retention."The vaccine consists of a bacterial protein (cholera toxin B-subunit) chemically linked to a cocaine-like molecule, succinylnorcocaine. Like all vaccines, it works by provoking an immune response. The bacterial protein triggers the production of antibodies, proteins which recognize and bind to specific targets.In this case, the antibodies bind cocaine (anti-cocaine IgG) because of the succinylnorcocaine in the vaccine. Once a molecule of cocaine is bound to the antibody, it's effectively out of commission, as it cannot enter the brain. So, the vaccine should reduce or abolish the effects of the drug. The control group were given a dummy placebo vaccine.The results? Biologically speaking, the vaccine worked, but in some people more than others. Out of the 55 subjects who were given the active vaccine, all but one produced anti-cocaine IgG. However, the amount of antibodies produced varied widely. Also, the response was short-lived. The vaccine was given 5 times over the first 12 weeks, but antibody levels did not peak until week 16, after which they fell rapidly.And the key question - did it reduce cocaine use? Well, sort of. The authors measured drug use in terms of the proportion of urine samples which were cocaine-free. In the active vaccine group, the proportion of drug-free urine samples was higher over weeks 9 to 16, when the antibody levels were high, and this was statistically significant (treatment x time interaction: Z=2.4, P=.01). As expected, the benefit was greater in the people who made lots of antibodies (43 μg/mL) (treatment x time interaction: Z=4.8, P less than .001). But the effect was pretty small:The bottom line was about 10% more urine samples testing negative, and even that was only true in the minority (38%) of people who responded well to the vaccine! Not very impressive, but on the other hand, the number of drug-free urine tests is a very crude measure of cocaine use. It doesn't tell us how much coke the patients used at a time, or how many times they used it per day.Also, bear in mind that if it works, this vaccine might increase cocaine use in some people, at least at first. By binding and inactivating some of the cocaine in the bloodstream, the vaccine would mean you'd need to take more of the drug in order to feel the effects. It's curious that the authors relied on just one crude outcome measure and didn't ask the patients to describe the effects in more detail.So, these are some interesting results, but the vaccine clearly needs a lot of work before it becomes clinically useful, as the authors admit - "Attaining high (43 μg/mL) IgG anticocaine antibody levels was associated with significantly reduced cocaine use, but only 38% of the vaccinated subjects attained these IgG levels and they had only 2 months of adequate cocaine blockade. Thus, we need improved vaccines and boosters." Quite an admission given that this study was partially funded by Celtic Pharmaceuticals, who make the vaccine.It's also questionable whether any vaccine will be truly beneficial in treating cocaine addiction. Such a vaccine would be a way of reducing the temptation to use cocaine. In this sense, it would be just like naltrexone for heroin addicts, which blocks the effects of the drug. Or disulifram (Antabuse) for alcoholics, which makes drinking alcohol cause horrible side effects. Essentially, these treatments are ways of artificially boosting your "self-control", and they work.But we've had naltrexone and disulifram for many years. They're cheap and safe. But we still have heroin addicts and alcoholics. This is not to say that they're never helpful - some people find them very useful. But they haven't eradicated addiction because addiction is not something that can be cured with a pill or an injection.Addiction is a pattern of behaviour, and medications might help people to break free of it, but the causes of addiction are social, economic and psychological as well as biological. People turn to drugs and alcohol when there's nowhere else to turn, and unfortunately, there's no vaccine against that.Martell BA, Orson FM, Poling J, Mitchell E, Rossen RD, Gardner T, & Kosten TR (2009). Cocaine vaccine for the treatment of cocaine dependence in methadone-maintained patients: a randomized, double-blind, placebo-controlled efficacy trial. Archives of general psychiatry, 66 (10), 1116-23 PMID: 19805702... Read more »
Martell BA, Orson FM, Poling J, Mitchell E, Rossen RD, Gardner T, & Kosten TR. (2009) Cocaine vaccine for the treatment of cocaine dependence in methadone-maintained patients: a randomized, double-blind, placebo-controlled efficacy trial. Archives of general psychiatry, 66(10), 1116-23. PMID: 19805702
Do men and women differ in their cognitive capacities? It's been a popular topic of conversation since as far back as we have records of what people were talking about.While it's now (almost) generally accepted that men and women are at most only very slightly different in average IQ, there are still a couple of lines of evidence in favor of a gender difference.First, there's the idea that men are more variable in their intelligence, so there are more very smart men, and also more very stupid ones. This averages out so the mean is the same.Second, there's the theory that men are on average better at some things, notably "spatial" stuff involving the ability to mentally process shapes, patterns and images, while women are better at social, emotional and perhaps verbal tasks. Again, this averages out overall.According to proponents, these differences explain why men continue to dominate the upper echelons of things like mathematics, physics, and chess. These all tap spatial processing and since men are more variable, there'll be more extremely high achievers - Nobel Prizes, grandmasters. (There are also presumably more men who are rubbish at these things, but we don't notice them.)The male spatial advantage has been reported in many parts of the world, but is it "innate", something to do with the male brain? A new PNAS study says - probably not, it's to do with culture. But I'm not convinced.The authors went to India and studied two tribes, the Khasi and the Karbi. Both live right next to other in the hills of Northeastern India and genetically, they're closely related. Culturally though, the Karbi are patrilineal - property and status is passed down from father to son, with women owning no land of their own. The Khasi are matrilineal, with men forbidden to own land. Moreover, Khasi women also get just as much education as the men, while Karbi ones get much less.The authors took about 1200 people from 8 villages - 4 per culture - and got them to do a jigsaw puzzle. The quicker you do it, the better your spatial ability. Here were the results. I added the gender-stereotypical colours.In the patrilineal group, women did substantially worse on average (remember that more time means worse). In the matrilineal society, they performed as well as men. Well, a tiny bit worse, but it wasn't significant. Differences in education explained some of the effect, but only a small part of it.OK.This was a large study, and the results are statistically very strong. However, there's a curious result that the authors don't discuss in the paper - the matrilineal group just did much better overall. Looking at the men, they were 10 seconds faster in the matrilineal culture. That's nearly as big as the gender difference in the patrilineal group (15 seconds)!The individual variability was also much higher in the patrilineal society, for both genders.Now, maybe, this is a real effect. Maybe being in a patrilineal society makes everyone less spatially aware, not just women; that seems a bit of a stretch, though.There's also the problem that this study essentially only has two datapoints. One society is matrilineal and has low gender difference in visuospatial processing. One is patrilineal and has a high difference. But that's just not enough data to conclude that there's a correlation between the two things, let alone a causal relationship; you would need to study lots of societies to do that. Personally, I have no idea what drives the difference, but this study is a reminder of how difficult the question is.Hoffman M, Gneezy U, List JA (2011). Nurture affects gender differences in spatial abilities. Proceedings of the National Academy of Sciences of the United States of America PMID: 21876159... Read more »
Hoffman M, Gneezy U, & List JA. (2011) Nurture affects gender differences in spatial abilities. Proceedings of the National Academy of Sciences of the United States of America. PMID: 21876159
Watch out! The BBC report that - Deet bug repellent 'toxic worry' While The Telegraph are even more concerned -Insect repellent Deet is bad for your nerves, claim scientists This is in reference to a new paper about the widely-used insect repellent DEET. The BBC, as usual, performed slightly better than the Telegraph here. They included quotes from two experts making it clear that the research in question was preliminary and in no way proves that DEET is dangerous to humans. But they still ran the headline implying that DEET could be "toxic", which is the only thing most people will remember about the article. As you'll see below, this is quite misleading.DEET is an insect repellant, generally used to prevent mosquito bites. You spray it on your skin, clothes, mosquito nets, etc. If you've ever been to a tropical country, you'll probably remember it. It has a distinctive smell, it stings the eyes and throat, and, most distressingly, it dissolves plastics. My watch fell off in Thailand because DEET ate through the strap.That aside, DEET is believed to be safe, so long as you spray it instead of drinking it. Hundreds of millions of people have used it for decades. And it works, which means it saves lives. Mosquitoes spread diseases like malaria, yellow fever, Dengue, and plenty more. They can all kill you. This is why any health professional will advise you to use mosquito-repellants, preferably DEET-based ones, when visiting risk areas.So it would be massive news if DEET was found to be dangerous. But it hasn't. What's been found is that, in animals and in test-tubes, DEET is a cholinesterase inhibitor. Cholinesterase is an enzyme which breaks down acetylcholine (ACh), a neurotransmitter. If you inhibit cholinesterase, ACh levels rapidly increase. This can cause problems because ACh is the transmitter that your nerves use to communicate with your muscles. As ACh builds up, your muscles don't stop contracting, and you suffer paralysis, until you can't breathe. This is how "nerve gas" works.But we know DEET isn't a strong cholinesterase inhibitor, when used normally, because people don't get cholinergic effects after using it. The toxicity of cholinesterase inhibitors is acute. You get paralyzed, and suffer other symptoms like uncontrollable salivation, crying, vomiting, and incontinence. You'd know if this happened to you.Cholinesterase inhibitors are not, as various media reports have said about DEET, "neurotoxic" , they do not cause "neural damage". They act on the nerves, but they do not damage the nerves. In fact people with Alzheimer's take them (in low doses!), as do people with the nerve disease myasthenia gravis.So the fact that DEET can act as a cholinesterase inhibitor in the lab changes nothing. It's still safe, at least until evidence comes along that it actually causes harm in people who use it. You can't show that something is harmful by doing an experiment showing how it could be harmful in theory.To be fair, there is one cause for concern in the paper - in the experiments, DEET interacted with other cholinesterase inhibitors, leading to an amplified effect. That suggests that DEET could become toxic in combination with cholinesterase inhibitor insecticides, but again, the risk is theoretical.The media should never have reported on this paper. The science itself is perfectly good, but the results are completely irrelevant to the average person who might want to use DEET. They are of interest only to biologists. If people decide not to use DEET on the basis of these reports, they are putting themselves in danger. Others have noted that journalists almost always report on laboratory experiments like these as if they were directly relevant to human health. They're not.Appendix: In one of the articles, an expert says that "I also would guess that the actual concentration [of DEET] in the body is much lower than they had to use in the study to see an effect in the mouse tissues." But we don't have to guess, we can work it out. DEET had detectable effects in mammalian tissues at a concentration of 0.5 millimole. A millimole is a unit of concentration; 1 millimole is 0.19 grams DEET per liter of water. (Molar weight of DEET = 191g/mole). The human body is 60% water by weight. A person weighs, say, 75 kg, which means roughly 50 liters of water. That means that to achieve the level of DEET used in this study, you would need to absorb into your body about 50 x 0.19 = 9.5 grams of DEET (assuming it was evenly distributed in your body).That's a huge amount. But maybe it's not completely impossible, bearing in mind that DEET might be absorbed through the skin? Is there any data on DEET levels in humans? Yes. This paper reports on the development of a way of measuring DEET in human blood. This method could detect DEET at levels from 1 ng/mL to 100 ng/mL. I assume that the upper limit was chosen because no-one ever gets more DEET than that. 100 ng / mL = 100 micrograms / L = 0.52 micromolar = 0.0005 millimolar. That's 1000-fold too low, and that's the upper limit.This was just a back-of-the-envelope calculation so please feel free to critique it, but, I find it reassuring.Corbel, V., Stankiewicz, M., Pennetier, C., Fournier, D., Stojan, J., Girard, E., Dimitrov, M., Molgo, J., Hougard, J., & Lapied, B. (2009). Evidence for inhibition of cholinesterases in insect and mammalian nervous systems by the insect repellent deet BMC Biology, 7 (1) DOI: 10.1186/1741-7007-7-47... Read more »
Corbel, V., Stankiewicz, M., Pennetier, C., Fournier, D., Stojan, J., Girard, E., Dimitrov, M., Molgo, J., Hougard, J., & Lapied, B. (2009) Evidence for inhibition of cholinesterases in insect and mammalian nervous systems by the insect repellent deet. BMC Biology, 7(1), 47. DOI: 10.1186/1741-7007-7-47
But only if you voted for him, and only if you're a man. That's according to a PLoS One paper called Dominance, Politics, and Physiology.It's already known that in males, winning competitions - achieving "dominance" - causes a rapid rise in testosterone release, whilst losing does the opposite. That's true in humans, as well as in other mammals. The authors wondered whether the same thing happens when men "win" vicariously - i.e. when someone we identify with triumphs.What better way of testing this than the U.S. Presidential Election? The authors took 163 American voters, and got them to provide saliva samples before, during and after the results came in on the night of the 4th November. Here's what happened -In Obama supporters (the blue line, natch), salivary testosterone levels stayed flat throughout the crucial hours. But supporters of John McCain or Libertarian candidate Bob Barr, suffered a testosterone crash after Obama's victory became apparent. That was only true in men, though; in women, there was no change.Heh. Of course, we hardly needed biology to tell us that people often identify strongly with their preferred political parties, and the fact that social events cause hormonal changes shouldn't surprise anyone - the brain controls the secretion of most hormones.The gender difference is interesting, though. Does this mean that men identify closer with politicians? Or maybe only with male ones - what would have happened if Hilary had won... or Palin? It could be that the testosterone surge accompanying success is strictly a man thing, although it's been shown to occur in women in some studies, but not consistently.Finally, I should mention that this paper contains some excellent quotes, such as "...Robert Barr, who arguably did not have a chance of winning...", "In retrospective reports of their affective state upon the announcement of Obama as the president-elect, McCain and Barr voters felt significantly more unhappy" and my favourite, "men who voted for John McCain or Bob Barr (losers)". That last one may be taken slightly out of context.Stanton, S., Beehner, J., Saini, E., Kuhn, C., & LaBar, K. (2009). Dominance, Politics, and Physiology: Voters' Testosterone Changes on the Night of the 2008 United States Presidential Election PLoS ONE, 4 (10) DOI: 10.1371/journal.pone.0007543... Read more »
Stanton, S., Beehner, J., Saini, E., Kuhn, C., & LaBar, K. (2009) Dominance, Politics, and Physiology: Voters' Testosterone Changes on the Night of the 2008 United States Presidential Election. PLoS ONE, 4(10). DOI: 10.1371/journal.pone.0007543
Absinthe is a spirit. It's very strong, and very green. But is it something more?I used to think so, until I came across this paper taking a skeptical look at the history and science of the drink, Padosch et al's Absinthism a fictitious 19th century syndrome with present impactAbsinthe is prepared by crushing and dissolving the herb wormwood in unflavoured neutral alcohol and then distilling the result; other herbs and spices are added later for taste and colour.It became extremely popular in the late 19th century, especially in France, but it developed a reputation as a dangerous and hallucinogenic drug. Overuse was said to cause insanity, "absinthism", much worse than regular alcoholism. Eventually, absinthe was banned in the USA and most but not all European countries.Much of the concern over absinthe came from animal experiments. Wormwood oil was found to cause hyperactivity and seizures in cats and rodents, whereas normal alcohol just made them drunk. But, Padosch et al explain, the relevance of these experiments to drinkers is unclear, because they involved high doses of pure wormwood extract, whereas absinthe is much more dilute. The fact that authors at the time used the word absinthe to refer to both the drink and the pure extract added to the confusion.It's now known that wormwood, or at least some varieties of it, contains thujone, which can indeed cause seizures, and death, due to being a GABA antagonist. Until a few years ago it was thought that old-style absinthe might have contained up to 260 mg of thujone per litre, a substantial dose.But that was based on the assumption that all of the thujone in the wormwood ended up in the drink prepared from it. Chemical analysis of actual absinthe has repeatedly found that it contains no more than about 6 mg/L thujone. The alcohol in absinthe would kill you long before you drank enough to get any other effects. As the saying goes, "the dose makes the poison", something that is easily forgotten.As Padosch et al point out, it's possible that there are other undiscovered psychoactive compounds in absinthe, or that long-term exposure to low doses of thujone does cause "absinthism". But there is no evidence for that so far. Rather, they say, absinthism was just chronic alcoholism, and absinthe was no more or less dangerous than any other spirit.I'm not sure why, but drinks seem to attract more than their fair share of urban myths. Amongst many others I've heard that the flakes of gold in Goldschläger cause cuts which let alcohol into your blood faster; Aftershock crystallizes in your stomach, so if you drink water the morning afterwards, you get drunk again; and that the little worm you get at the bottom of some tequilas apparently contains especially concentrated alcohol, or hallucinogens, or even cocaine maybe.Slightly more serious is the theory that drinking different kinds of drinks instead of sticking to just one gets you drunk faster, or gives you a worse hangover, or something, especially if you do it in a certain order. Almost everyone I know believes this, although in my drinking experience it's not true, but I'm not sure that it's completely bogus, as I have heard somewhat plausible explanations i.e. drinking spirits alongside beer leads to a concentration of alcohol in your stomach that's optimal for absorption into the bloodstream... maybe.Link: Not specifically related to this but The Poison Review is an excellent blog I've recently discovered all about poisons, toxins, drugs, and such fun stuff.Padosch SA, Lachenmeier DW, & Kröner LU (2006). Absinthism: a fictitious 19th century syndrome with present impact. Substance abuse treatment, prevention, and policy, 1 (1) PMID: 16722551... Read more »
Padosch SA, Lachenmeier DW, & Kröner LU. (2006) Absinthism: a fictitious 19th century syndrome with present impact. Substance abuse treatment, prevention, and policy, 1(1), 14. PMID: 16722551
There was nothing special about Albert Einstein’s brain. Nothing that modern neuroscience can detect, anyway. This is the message of a provocative article by Pace University psychologist Terence Hines, just published in Brain and Cognition: Neuromythology of Einstein’s brain As Hines notes, the story of how Einstein’s brain was preserved is well known. When the […]The post The Myth of Einstein’s Brain? appeared first on Neuroskeptic.... Read more »
It's a cliché, but it's true - "schizophrenia genes" are the Holy Grail of modern psychiatry.Were they to be discovered, such genes would provide clues towards a better understanding of the biology of the disease, and that could lead directly to the development of better medications. It might also allow "genetic counselling" for parents concerned about their children's risk of schizophrenia.Perhaps most importantly for psychiatrists, the definitive identification of genes for a mental illness would provide cast-iron proof that psychiatric disorders are "real diseases", and that biological psychiatry is a branch of medicine like any other. Schizophrenia, generally thought of as the most purely "biological" of all mental disorders, is the best bet.With this in mind, let's look at three articles (1,2,3) published in Nature last month to much excited fanfare along the lines of 'Schizophrenia genes discovered!' All three were based on genome-wide association studies (GWAS). In a GWAS, you examine a huge number of genetic variants in the hope that some of them are associated with the disease or trait you're interested in. Several hundred thousand variants per study is standard at the moment. This is the genetic equivalent of trying to find the person responsible for a crime by fingerprinting everyone in town.The Nature papers were based on three seperate large GWAS projects - the SGENE-plus, the MGS, and the ICS. In total, there were over 8,000 schizophrenia patients and 19,000 healthy controls in these studies - enormous samples by the standards of human genetics research, and large enough that if there were any common genetic variants with even a modest effect on schizophrenia risk, they would probably have found them.What did they find? On the face of it, not much. The MGS(1) "did not produce genome-wide significant findings...power was adequate in the European-ancestry sample to detect very common risk alleles (30–60% frequency) with genotypic relative risks of approximately 1.3 ...The results indicate that there are few or no single common loci with such large effects on risk." In the SGENE-plus(2), likewise, "None of the markers gave P values smaller than our genome-wide significance threshold".The ISC study(3) did find one significantly associated variant in the Major Histocompatability Complex (MHC) region on chromosome 6. The MHC is known to be involved in immune function. When the data from all three studies were pooled together, several variants in the same region were also found to be significantly associated with schizophrenia.Somewhat confusingly, all three papers did this pooling, although they each did it in slightly different ways - the only area in which all three analyses found a result was the MHC region. The SGENE team's analysis, which was larger, also implicated two other, unrelated variants, which were not found in other two papers.To summarize, three very large studies found just one "schizophrenia gene" even after pooling their data. The variant, or possibly cluster of related ones, is presumably involved in the immune system. Although the authors of the Nature papers made much of this finding, the main news here is that there is at most one common variant which raises the relative risk of schizophrenia by even just 20%. Given that the baseline risk of schizophrenia is about 1%, there is at most one common gene which raises your risk to more than 1.2%. That's it.So, what does this mean? There are three possibilites. First, it could be that schizophrenia genes are not "common". This possibility is getting a lot of attention at the moment, thanks to a report from a few months back, Walsh et al, suggesting that some cases of schizophrenia are caused by just one rare, high-impact mutation, but a different mutation in each case. In other words, each case of schizophrenia could be genetically almost unique. GWAS studies would be unable to detect such effects.Second, there could be lots of common variants, each with an effect on risk so tiny that it wasn't found even in these three large projects. The only way to identify them would be to do even bigger studies. The ISC team's paper claims that this is true, on the basis of this graph: They took all of the variants which were more common in schizophrenics than in controls, even if they were only slightly more common, and totalled up the number of "slight risk" variants each person has.The graph shows that these "slight risk" markers were more common in people with schizophrenia from two entirely seperate studies, and are also more common in people with bipolar disorder, but were not associated with five medical illnesses like diabetes. This is an interesting result, but these variants must have such a tiny effect on risk that finding them would involve spending an awful lot of time (and money) for questionable benefit.The third and final possibility is that "schizophrenia" is just less genetic than most psychiatrists think, because the true causes of the disorder are not genetic, and/or because "schizophrenia" is an umbrella term for many different diseases with different causes. This possibility is not talked about much in respectable circles, but if genetics doesn't start giving solid results soon, it may be.Purcell, S., & et Al (2009). Common polygenic variation contributes to risk of schizophrenia and bipolar disorder Nature DOI: 10.1038/nature08185Shi, J., & et Al (2009). Common variants on chromosome 6p22.1 are associated with schizophrenia Nature DOI: 10.1038/nature08192... Read more »
Purcell, S., & et Al. (2009) Common polygenic variation contributes to risk of schizophrenia and bipolar disorder. Nature. DOI: 10.1038/nature08185
Shi, J., & et Al. (2009) Common variants on chromosome 6p22.1 are associated with schizophrenia. Nature. DOI: 10.1038/nature08192
A few months ago, I asked Why Do We Sleep?That post was about sleep researcher Jerry Siegel, who argues that sleep evolved as a state of "adaptive inactivity". According to this idea, animals sleep because otherwise we'd always be active, and constant activity is a waste of energy. Sleeping for a proportion of the time conserves calories, and also keeps us safe from nocturnal predators etc.Siegel's theory in what we might call minimalist. That's in contrast to other hypotheses which claim that sleep serves some kind of vital restorative biological function, or that it's important for memory formation, or whatever. It's a hotly debated topic.But Siegel wasn't the first sleep minimalist. J. Allan Hobson and Robert McCarley created a storm in 1977 with The Brain As A Dream State Generator; I read somewhere that it provoked more letters to the Editor in the American Journal of Psychiatry than any other paper in that journal.Hobson and McCarley's article was so controversial because they argued that dreams are essentially side-effects of brain activation. This was a direct attack on the Freudian view that we dream as a result of our subconscious desires, and that dreams have hidden meanings. Freudian psychoanalysis was incredibly influential in American psychiatry in the 1970s.Freud believed that dreams exist to fulfil our fantasies, often though not always sexual ones. We dream about what we'd like to do - except we don't dream about it directly, because we find much of our desires shameful, so our minds disguise the wishes behind layers of metaphor etc. "Steep inclines, ladders and stairs, and going up or down them, are symbolic representations of the sexual act..." Interpreting the symbolism of dreams can therefore shed light on the depths of the mind.Hobson and McCarley argued that during REM sleep, our brains are active in a similar way to when we are awake; many of the systems responsible for alertness are switched on, unlike during deep, dreamless, non-REM sleep. But of course during REM there is no sensory input (our eyes are closed), and also, we are paralysed: an inhibitory pathway blocks the spinal cord, preventing us from moving, except for our eyes - hence why it's Rapid Eye Movement sleep.Dreams are simply a result of the "awake-like" forebrain - the "higher" perceptual, cognitive and emotional areas - trying to make sense of the input that it's receiving as a result of waves of activation arising from the brainstem. A dream is the forebrain's "best guess" at making a meaningful story out of the assortment of sensations (mostly visual) and concepts activated by these periodic waves. There's no attempt to disguise the shameful parts; the bizarreness of dreams simply reflects the fact that the input is pretty much random.Hobson and McCarley proposed a complex physiological model in which the activation is driven by the giant cells of the pontine tegmentum. These cells fire in bursts according to a genetically hard-wired rhythm of excitation and inhibition.The details of this model are rather less important than the fact that it reduces dreaming to a neurological side effect. This doesn't mean that the REM state has no function; maybe it does, but whatever it is, the subjective experience of dreams serves no purpose.A lot has changed since 1977, but Hobson seems to have stuck by the basic tenets of this theory. A good recent review came out in Nature Neuroscience last year, REM sleep and dreaming. In this paper Hobson proposes that the function of REM sleep is to act as a kind of training system for the developing brain.The internally-generated signals that arise from the brainstem (now called PGO waves) during REM help the forebrain to learn how to process information. This explains why we spend more time in REM early in life; newborns have much more REM than adults; in the womb, we are in REM almost all the time. However, these are not dreams per se because children don't start reporting experiencing dreams until about the age of 5.Protoconscious REM sleep could therefore provide a virtual world model, complete with an emergent imaginary agent (the protoself) that moves (via fixed action patterns) through a fictive space (the internally engendered environment) and experiences strong emotion as it does so.This is a fascinating hypothesis, although very difficult to test, and it begs the question of how useful "training" based on random, meaningless input is.While Hobson's theory is minimalist in that it reduces dreams, at any rate in adulthood, to the status of a by-product, it doesn't leave them uninteresting. Freudian dream re-interpretation is probably ruled out ("That train represents your penis and that cat was your mother", etc.), but if dreams are our brains processing random noise, then they still provide an insight into how our brains process information. Dreams are our brains working away on their own, with the real world temporarily removed.Of course most dreams are not going to give up life-changing insights. A few months back I had a dream which was essentially a scene-for-scene replay of the horror movie Cloverfield. It was a good dream, scarier than the movie itself, because I didn't know it was a movie. But I think all it tells me is that I was paying attention when I watched Cloverfield.On the other hand, I have had several dreams that have made me realize important things about myself and my situation at the time. By paying attention to your dreams, you can work out how you really think, and feel, about things, what your preconceptions and preoccupations are. Sometimes.Hobson JA, & McCarley RW (1977). The brain as a dream state generator: an activation-synthesis hypothesis of the dream process. The American journal of psychiatry, 134 (12), 1335-48 PMID: 21570Hobson, J. (2009). REM sleep and dreaming: towards a theory of protoconsciousness Nature Reviews Neuroscience, 10 (11), 803-813 DOI: 10.1038/nrn2716... Read more »
Hobson JA, & McCarley RW. (1977) The brain as a dream state generator: an activation-synthesis hypothesis of the dream process. The American journal of psychiatry, 134(12), 1335-48. PMID: 21570
Hobson, J. (2009) REM sleep and dreaming: towards a theory of protoconsciousness. Nature Reviews Neuroscience, 10(11), 803-813. DOI: 10.1038/nrn2716
According to Mormon author and fruit grower "Dr" Robert O. Young, pretty much all diseases are caused by our bodies being too acidic. By adopting an "alkaline lifestyle" to raise your internal pH (lower pH being more acidic), you'll find that
if you maintain the saliva and the urine pH, ideally at 7.2 or above, you will never get sick. That’s right you will NEVER get sick!
Wow. Important components of the alkaline lifestyle include eating plenty of the right sort of fruits and vegetables, ideally ones grown by Young, and taking plenty of nutritional supplements. These don't come cheap, but when the payoff is being free of all diseases, who could complain?
Young calls his amazing theory the Alkavorian Approach™, aka the New Biology™. Almost everyone else calls it quack medicine and pseudoscience. Because it is quack medicine and pseudoscience. But a paper just published in Cell suggests an interesting role for pH in, of all things, anxiety and panic - The amygdala is a chemosensor that detects carbon dioxide and acidosis to elicit fear behavior.
The authors, Ziemann et al, were interested in a protein called Acid Sensing Ion Channel 1a, ASIC1a, which as the name suggests, is acid-sensitive. Nerve cells expressing ASIC1a are activated when the fluid around them becomes more acidic.
One of the most common causes of acidosis (a fall in body pH) is carbon dioxide, CO2. Breathing is how we get rid of the CO2 produced by our bodies; if breathing is impaired, for example during suffocation, CO2 levels rise, and pH falls as CO2 is converted to carbonic acid in the bloodstream.
In previous work, Ziemann et al found that the amygdala contains lots of ASIC1a. This is intriguing, because the amygdala is a brain region believed to be involved in fear, anxiety and panic, although it has other functions as well. It's long been known that breathing air with added CO2 can trigger anxiety and panic, especially in people vulnerable to panic attacks.
What's unclear is why this happens; various biological and psychological theories have been proposed. Ziemann et al set out to test the idea that ASIC1a in the amygdala mediates anxiety caused by CO2.
In a number of experiments they showed that mice genetically engineered have no ASIC1a (knockouts) were resistant to the anxiety-causing effects of air containing 10% or 20% CO2. Also, unlike normal mice, the knockouts were happy to enter a box with high CO2 levels - normal mice hated it. Injections of a weakly acidic liquid directly into the amygdala caused anxiety in normal mice, but not in the knockouts.
Most interestingly, they found that knockout mice could be made to fear CO2 by giving them ASIC1a in the amygdala. Knockouts injected in the amygdala with a virus containing ASIC1a DNA, which caused their cells to start producing the protein, showed anxiety (freezing behaviour) when breathing CO2. But it only worked if the virus was injected into the amygdala, not nearby regions.
This is a nice series of experiments which shows convincingly that ASIC1a mediates acidosis-related anxiety, at least in mice. What's most interesting however is that it also seems to involved in other kinds of anxiety and fear. The ASIC1a knockout mice were slightly less anxious in general; injections of an alkaline solution prevented CO2-related anxiety, but also reduced anxiety caused by other scary things, such as the smell of a cat.
The authors conclude by proposing that amygdala pH might be involved in fear more generally
Thus, we speculate that when fear-evoking stimuli activate the amygdala, its pH may fall. For example, synaptic vesicles release protons, and intense neural activity is known to lower pH.
But this is, as they say, speculation. The link between CO2, pH and panic attacks seems more solid. As the authors of another recent paper put it
We propose that the shared characteristics of CO2/H+ sensing neurons overlap to a point where threatening disturbances in brain pH homeostasis, such as those produced by CO2 inhalations, elicit a primal emotion that can range from breathlessness to panic.
ResearchBlogging.orgZiemann, A., Allen, J., Dahdaleh, N., Drebot, I., Coryell, M., Wunsch, A., Lynch, C., Faraci, F., Howard III, M., & Welsh, M. (2009). The Amygdala Is a Chemosensor that Detects Carbon Dioxide and Acidosis to Elicit Fear Behavior Cell, 139 (5), 1012-1021 DOI: 10.1016/j.cell.2009.10.029... Read more »
Ziemann, A., Allen, J., Dahdaleh, N., Drebot, I., Coryell, M., Wunsch, A., Lynch, C., Faraci, F., Howard III, M., & Welsh, M. (2009) The Amygdala Is a Chemosensor that Detects Carbon Dioxide and Acidosis to Elicit Fear Behavior. Cell, 139(5), 1012-1021. DOI: 10.1016/j.cell.2009.10.029
There's a lot of talk, much of it rather speculative, about "neuroethics" nowadays.But there's one all too real ethical dilemma, a direct consequence of modern neuroscience, that gets very little attention. This is the problem of incidental findings on MRI scans.An "incidental finding" is when you scan someone's brain for research purposes, and, unexpectedly, notice that something looks wrong with it. This is surprisingly common: estimates range from 2–8% of the general population. It will happen to you if you regularly use MRI or fMRI for research purposes, and when it does, it's a shock. Especially when the brain in question belongs to someone you know. Friends, family and colleagues are often the first to be recruited for MRI studies.This is why it's vital to have a system in place for dealing with incidental findings. Any responsible MRI scanning centre will have one, and as a researcher you ought to be familiar with it. But what system is best?Broadly speaking there are two extreme positions:Research scans are not designed for diagnosis, and 99% of MRI researchers are not qualified to make a diagnosis. What looks "abnormal" to Joe Neuroscientist BSc or even Dr Bob Psychiatrist is rarely a sign of illness, and likewise they can easily miss real diseases. So, we should ignore incidental findings, pretend the scan never happened, because for all clinical purposes, it didn't.You have to do whatever you can with an incidental finding. You have the scans, like it or not, and if you ignore them, you're putting lives at risk. No, they're not clinical scans, they can still detect many diseases. So all scans should be examined by a qualified neuroradiologist, and any abnormalities which are possibly pathological should be followed-up.Neither of these extremes is very satisfactory. Ignoring incidental findings sounds nice and easy, until you actually have to do it, especially if it's your girlfriend's brain. On the other hand, to get every single scan properly checked by a neuroradiologist would be expensive and time-consuming. Also, it would effectively turn your study into a disease screening program - yet we know that screening programs can cause more harm than good, so this is not necessarily a good idea.Most places adopt a middle-of-the-road approach. Scans aren't routinely checked by an expert, but if a researcher spots something weird, they can refer the scan to a qualified clinician to follow up. Almost always, there's no underlying disease. Even large, OMG-he-has-a-golf-ball-in-his-brain findings can be benign. But not always.This is fine but it doesn't always work smoothly. The details are everything. Who's the go-to expert for your study, and what are their professional obligations? Are they checking your scan "in a personal capacity", or is this a formal clinical referral? What's their e-mail address? What format should you send the file in? If they're on holiday, who's the backup? At what point should you inform the volunteer about what's happening?Like fire escapes, these things are incredibly boring, until the day when they're suddenly not.A new paper from the University of California Irvine describes a computerized system that made it easy for researchers to refer scans to a neuroradiologist. A secure website was set up and publicized in University neuroscience community.Suspect scans could be uploaded, in one of two common formats. They were then anonymized and automatically forwarded to the Department of Radiology for an expert opinion. Email notifications kept everyone up to date with the progress of each scan.This seems like a very good idea, partially because of the technical advantages, but also because of the "placebo effect" - the fact that there's an electronic system in place sends the message: we're serious about this, please use this system.Out about 5,000 research scans over 5 years, there were 27 referrals. Most were deemed benign... except one which turned out to be potentially very serious - suspected hydrocephalus, increased fluid pressure in the brain, which prompted an urgent referral to hospital for further tests.There's no ideal solution to the problem of incidental findings, because by their very nature, research scans are kind of clinical and kind of not. But this system seems as good as any.Cramer SC, Wu J, Hanson JA, Nouri S, Karnani D, Chuang TM, & Le V (2011). A system for addressing incidental findings in neuroimaging research. NeuroImage PMID: 21224007... Read more »
Cramer SC, Wu J, Hanson JA, Nouri S, Karnani D, Chuang TM, & Le V. (2011) A system for addressing incidental findings in neuroimaging research. NeuroImage. PMID: 21224007
Have you ever wanted to know whether a mouse is in pain?Of course you have. And now you can, thanks to Langford et al's paper Coding of facial expressions of pain in the laboratory mouse.It turns out that mice, just like people, display a distinctive "Ouch!" facial expression when they're suffering acute pain. It consists of narrowing of the eyes, bulging nose and cheeks, ears pulled back, and whiskers either pulled back or forwards.With the help of a high-definition video camera and a little training, you can reliably and accurately tell how much pain a mouse is feeling. It works for most kinds of mouse pain, although it's not seen in either extremely brief or very long-term pain.Langford et al tried it out on mice with a certain genetic mutation, which causes severe migraines in humans. These mice displayed the pain face even in the absence of external painful stimuli, showing that they were suffering internally. A migraine drug was able to stop the pain.Finally, lesions to a part of the brain called the anterior insula stopped mice from expressing their pain. This is exactly what happens in people as well, suggesting that our displays of suffering are an evolutionary ancient mechanism. Of course this kind of study can't prove that animals consciously feel pain in the same way that we do, but I see no reason to doubt it: we feel pain as a result of neural activity, and mammals have exactly the same brain systems.Langford, D., Bailey, A., Chanda, M., Clarke, S., Drummond, T., Echols, S., Glick, S., Ingrao, J., Klassen-Ross, T., LaCroix-Fralish, M., Matsumiya, L., Sorge, R., Sotocinal, S., Tabaka, J., Wong, D., van den Maagdenberg, A., Ferrari, M., Craig, K., & Mogil, J. (2010). Coding of facial expressions of pain in the laboratory mouse Nature Methods, 7 (6), 447-449 DOI: 10.1038/nmeth.1455... Read more »
Langford, D., Bailey, A., Chanda, M., Clarke, S., Drummond, T., Echols, S., Glick, S., Ingrao, J., Klassen-Ross, T., LaCroix-Fralish, M.... (2010) Coding of facial expressions of pain in the laboratory mouse. Nature Methods, 7(6), 447-449. DOI: 10.1038/nmeth.1455
What if there was a drug that didn't just affect the levels of chemicals in your brain, it turned off genes in your brain? That possibility - either exciting or sinister depending on how you look at it - could be remarkably close, according to a report just out from a Spanish group.The authors took an antidepressant, sertraline, and chemically welded it to a small interfering RNA (siRNA). A siRNA is kind of like a pair of genetic handcuffs. It selectively blocks the expression of a particular gene, by binding to and interfering with RNA messengers. In this case, the target was the serotonin 5HT1A receptor.The authors injected their molecule into the brains of some mice. The sertraline was there to target the siRNA at specific cell types. Sertraline works by binding to and blocking the serotonin transporter (SERT), and this is only expressed on cells that release serotonin; so only these cells were subject to the 5HT1A silencing.The idea is that this receptor acts as a kind of automatic off-switch for these cells, making them reduce their firing in response to their own output, to keep them from firing too fast. There's a theory that this feedback can be a bad thing, because it stops antidepressants from being able to boost serotonin levels very much, although this is debated.Anyway, it worked. The treated mice showed a strong and selective reduction in the density of the 5HT1A receptor in the target area (the Raphe nuclei containing serotonin cells), but not in the rest of the brain.Note that this isn't genetic modification as such. The gene wasn't deleted, it was just silenced, temporarily one hopes; the effect persisted for at least 3 days, but they didn't investigate just how long it lasted.That's remarkable enough, but what's more, it also worked when they administered the drug via the intranasal route. In many siRNA experiments, the payload is injected directly into the brain. That's fine for lab mice, but not very practical for humans. Intranasal administration, however, is popular and easy.So siRNA-sertraline, and who knows what other drugs built along these lines, may be closer to being ready for human consumption than anyone would have predicted. However... the mouse's brain is a lot closer to its nose than the human brain is, so it might not go quite as smoothly.The mind boggles at the potential. If you could selectively alter the gene expression of selective neurons, you could do things to the brain that are currently impossible. Existing drugs hit the whole brain, yet there are many reasons why you'd prefer to only affect certain areas. And editing gene expression would allow much more detailed control over those cells than is currently possible.Currently available drugs are shotguns and sledgehammers. These approaches could provide sniper rifles and scalpels. But whether it will prove to be safe remains to be seen. I certainly wouldn't want to be first one to snort this particular drug.Bortolozzi, A., Castañé, A., Semakova, J., Santana, N., Alvarado, G., Cortés, R., Ferrés-Coy, A., Fernández, G., Carmona, M., Toth, M., Perales, J., Montefeltro, A., & Artigas, F. (2011). Selective siRNA-mediated suppression of 5-HT1A autoreceptors evokes strong anti-depressant-like effects Molecular Psychiatry DOI: 10.1038/mp.2011.92... Read more »
Bortolozzi, A., Castañé, A., Semakova, J., Santana, N., Alvarado, G., Cortés, R., Ferrés-Coy, A., Fernández, G., Carmona, M., Toth, M.... (2011) Selective siRNA-mediated suppression of 5-HT1A autoreceptors evokes strong anti-depressant-like effects. Molecular Psychiatry. DOI: 10.1038/mp.2011.92
The past decade has been a bad one for antidepressant manufacturers. Quite apart from all the bad press these drugs have been getting lately, there's been a remarkable lack of new antidepressants making it to the market. The only really novel drug to hit the shelves since 2000 has been agomelatine. There were a couple of others that were just minor variants on old molecules, but that's it.This makes "Lu AA21004" rather special. It's a new antidepressant currently in development and by all accounts it's making good progress. It's now in Phase III trials, the last stage before approval. And a large clinical trial has just been published finding that it works.But is it a medical advance or merely a commercial one?Pharmacologically, Lu AA21004 is kind of a new twist on an old classic . Its main mechanism of action is inhibiting the reuptake of serotonin, just like Prozac and other SSRIs. However, unlike them, it also blocks serotonin 5HT3 and 5HT7 receptors, activates 5HT1A receptors and partially agonizes 5HT1B.None of these things cry out "antidepressant" to me, but they do at least make it a bit different.The new trial took 430 depressed people and randomized them to get Lu AA21004, at two different doses, 5mg or 10mg, or the older antidepressant venlafaxine at the high-ish dose of 225 mg, or placebo.It worked. Over 6 weeks, people on the new drug improved more than those on placebo, and equally as well as people on venlafaxine; the lower 5 mg dose was a bit less effective, but not significantly so.The size of the effect was medium, with a benefit over-and-above placebo of about 5 points on the MADRS depression scale, which considering that the baseline scores in this study averaged 34, is not huge, but it compares well to other antidepressant trials.Now we come to the side effects, and this is the most important bit, as we'll see later. The authors did not specifically probe for these, they just relied on spontaneous report, which tends to underestimate adverse events.Basically, the main problem with Lu AA21004 was that it made people sick. Literally - 9% of people on the highest dose suffered vomiting, and 38% got nausea. However, the 5 mg dose was no worse than venlafaxine for nausea, and was relatively vomit-free. Unlike venlafaxine, it didn't cause dry mouth, constipation, or sexual problems.So that's lovely then. Let's get this stuff to market!Hang on.The big selling point for this drug is clearly the lack of side effects. It was no more effective than the (much cheaper, because off-patent) venlafaxine. It was better tolerated, but that's not a great achievement to be honest. Venlafaxine is quite notorious for causing side effects, especially at higher doses.I take venlafaxine 300 mg and the side effects aren't the end of the world, but they're no fun, and the point is, they're well known to be worse than you get with other modern drugs, most notably SSRIs.If you ask me, this study should have compared the new drug to an SSRI, because they're used much more widely than venlafaxine. Which one? How about escitalopram, a drug which is, according to most of the literature, one of the best SSRIs, as effective as venlafaxine, but with fewer side effects.Actually, according to Lundbeck, who make escitalopram, it's even better than venlafaxine. Now, they would say that, given that they make it - but the makers of Lu AA21004 ought to believe them, because, er, they're the same people. "Lu" stands for Lundbeck.The real competitor for this drug, according to Lundbeck, is escitalopram. But no-one wants to be in competition with themselves.This may be why, although there are no fewer than 26 registered clinical trials of Lu AA21004 either ongoing or completed, only one is comparing it to an SSRI. The others either compare it to venlafaxine, or to duloxetine, which has even worse side effects. The one trial that will compare it to escitalopram has a narrow focus (sexual dysfunction).Pharmacologically, remember, this drug is an SSRI with a few "special moves", in terms of hitting some serotonin receptors. The question is - do those extra tricks actually make it better? Or is it just a glorified, and expensive, new SSRI? We don't know and we're not going to find out any time soon.If Lu AA21004 is no more effective, and no better tolerated, than tried-and-tested old escitalopram, anyone who buys it will be paying extra for no real benefit. The only winner, in that case, being Lundbeck.Alvarez E, Perez V, Dragheim M, Loft H, & Artigas F (2011). A double-blind, randomized, placebo-controlled, active reference study of Lu AA21004 in patients with major depressive disorder. The International Journal of Neuropsychopharmacology , 1-12 PMID: 21767441... Read more »
Alvarez E, Perez V, Dragheim M, Loft H, & Artigas F. (2011) A double-blind, randomized, placebo-controlled, active reference study of Lu AA21004 in patients with major depressive disorder. The international journal of neuropsychopharmacology / official scientific journal of the Collegium Internationale Neuropsychopharmacologicum (CINP), 1-12. PMID: 21767441
"Prevention is better than cure", so they say. And in most branches of medicine, preventing diseases, or detecting early signs and treating them pre-emptively before the symptoms appear, is an important art.Not in psychiatry. At least not yet. But the prospect of predicting the onset of psychotic illnesses like schizophrenia, and of "early intervention" to try to prevent them, is a hot topic at the moment.Schizophrenia and similar illnesses usually begin with a period of months or years, generally during adolescence, during which subtle symptoms gradually appear. This is called the "prodrome" or "at risk mental state". The full-blown disorder then hits later. If we could detect the prodromal phase and successfully treat it, we could save people from developing the illness. That's the plan anyway.But many kids have "prodromal symptoms" during adolescence and never go on to get ill, so treating everyone with mild symptoms of psychosis would mean unnecessarily treating a lot of people. There's also the question of whether we can successfully prevent progression to illness at all, and there have been only a few very small trials looking at whether treatments work for that - but that's another story.Stephan Ruhrmann et al. claim to have found a good way of predicting who'll go on to develop psychosis in their paper Prediction of Psychosis in Adolescents and Young Adults at High Risk. This is based on the European Prediction of Psychosis Study (EPOS) which was run at a number of early detection clinics in Britain and Europe. People were referred to the clinics through various channels if someone was worried they seemed a bit, well, prodromalReferral sources included psychiatrists, psychologists, general practitioners, outreach clinics, counseling services, and teachers; patients also initiated contact. Knowledge about early warning signs (eg, concentration and attention disturbances, unexplained functional decline) and inclusion criteria was disseminated to mental health professionals as well as institutions and persons who might be contacted by at-risk persons seeking help.245 people consented to take part in the study and met the inclusion criteria meaning they were at "high risk of psychosis" according to at least one of two different systems, the Ultra High Risk (UHR) or the COGDIS criteria. Both class you as being at risk if you show short lived or mild symptoms a bit like those seen in schizophrenia i.e.COGDIS: inability to divide attention; thought interference, pressure, and blockage; and disturbances of receptive and expressive speech, disturbance of abstract thinking, unstable ideas of reference, and captivation of attention by details of the visual field...UHR: unusual thought content/ delusional ideas, suspiciousness/persecutory ideas, grandiosity, perceptual abnormalities/hallucinations, disorganized communication, and odd behavior/appearance... Brief limited intermittent psychotic symptoms (BLIPS) i.e. hallucinations, delusions, or formal thought disorders that occurred resolved spontaneously within 1 week...Then they followed up the 245 kids for 18 months and saw what happened to them.What happened was that 37 of them developed full-blown psychosis: 23 suffered schizophrenia according to DSM-IV criteria, indicating severe and prolonged symptoms; 6 had mood disorders, i.e depression or bipolar disorder, with psychotic features, and the rest mostly had psychotic episodes too short to be classed as schizophrenia. 37 people is 19% of the 183 for whom full 18 month data was available; the others dropped out of the study, or went missing for some reason.Is 19% high or low? Well, it's much higher than the rate you'd see in randomly selected people, because the risk of getting schizophrenia is less than 1% lifetime and this was only 18 months; the risk of a random person developing psychosis in any given year has been estimated at 0.035% in Britain. So the UHR and COGDIS criteria are a lot better than nothing.On the other hand 19% is far from being "all": 4 out of 5 of the supposedly "high risk" kids in this study didn't in fact get ill, although some of them probably developed illness after the 18 month period was over.The authors also came up with a fancy algorithm for predicting risk based on your score on various symptom rating scales, and they claim that this can predict psychosis much better, with 80% accuracy. As this graph shows, the rate of developing psychosis in those scoring highly on their Prognostic Index is really high. (In case you were wondering the Prognostic Index is [1.571 x SIPS-Positive score 16] + [0.865 x bizarre thinking score] + [0.793 x sleep disturbances score] + [1.037 x SPD score] + [0.033 x (highest GAF-M score in the past year – 34.64)] + [0.250 x (years of education – 12.52)]. Use it on your friends for hours of psychiatric fun!)However they came up with the algorithm by putting all of their dozens of variables into a big mathematical model, crunching the numbers and picking the ones that were most highly correlated with later psychosis - so they've specifically selected the variables that best predict illness in their sample, but that doesn't mean they'll do so in any other case. This is basically the non-independence problem that has so troubled fMRI, although the authors, to their credit, recognize this and issue the appropriate cautions.So overall, we can predict psychosis, a bit, but far from perfectly. More research is needed. One of the proposed additions to the new DSM-V psychiatric classification system is "Psychosis Risk Syndrome" i.e. the prodrome; it's not currently a disorder in DSM-IV. This idea has been attacked as an invitation to push antipsychotic drugs on kids who aren't actually ill and don't need them. On the other hand though, we shouldn't forget that we're talking about terrible illnesses here: if we could successfully predict and prevent psychosis, we'd be doing a lot of good.Ruhrmann, S., Schultze-Lutter, F., Salokangas, R., Heinimaa, M., Linszen, D., Dingemans, P., Birchwood, M., Patterson, P., Juckel, G., Heinz, A., Morrison, A., Lewis, S., Graf von Reventlow, H., & Klosterkotter, J. (2010). Prediction of Psychosis in Adolescents and Young Adults at High Risk: Results From the Prospective European Prediction of Psychosis Study ... Read more »
Ruhrmann, S., Schultze-Lutter, F., Salokangas, R., Heinimaa, M., Linszen, D., Dingemans, P., Birchwood, M., Patterson, P., Juckel, G., Heinz, A.... (2010) Prediction of Psychosis in Adolescents and Young Adults at High Risk: Results From the Prospective European Prediction of Psychosis Study. Archives of General Psychiatry, 67(3), 241-251. DOI: 10.1001/archgenpsychiatry.2009.206
You've just finished doing some research using fMRI to measure brain activity. You designed the study, recruited the volunteers, and did all the scans. Phew. Is that it? Can you publish the findings yet?Unfortunately, no. You still need to do the analysis, and this is often the most trickiest stage. The raw data produced during an fMRI experiment are meaningless - in most cases, each scan will give you a few hundred almost-identical grey pictures of the person's brain. Making sense of them requires some complex statistical analysis.The very first step is choosing which software to use. Just as some people swear by Firefox while others prefer Internet Explorer for browsing the web, neuroscientists have various options to choose from in terms of image analysis software. Everyone's got a favourite. In Britain, the most popular are FSL (developed at Oxford) and SPM (London), while in the USA BrainVoyager sees a lot of use.These three all do pretty much the same thing, give or take a few minor technical differences, so which one you use ultimately makes little difference. But just as there's more than one way to skin a cat, there's more than one way to analyze a brain. A paper from Fusar-Poli et al compares the results you get with SPM to the results obtained using XBAM, a program which uses a quite different statistical approach.Here's what happened, according to SPM, when 15 volunteers looked at pictures of faces expressing the emotion of fear, and their brain activity was compared to when they were just looking at a boring "X" on the screen (I think - either that it's compared to looking at neutral faces; the paper isn't clear, but given the size of the blobs I doubt it's that.)Various bits of the brain were more activated by the scared face pics, as you can see by the huge, fiery blobs. The activation is mostly at the back of the brain, in occipital cortex areas which deal with vision, which is as you'd expect. The cerebellum was also strongly activated, which is a bit less expected.Now, here's what happens if you analyze exactly the same data using XBAM, setting the statistical threshold at the same level (i.e. in theory being no more or less "strict") -You get the same visual system blobs, but you also see activation in a number of other areas. Or as Fusar-Poli et al put it -Analysis using both programs revealed that during the processing of emotional faces, as compared to the baseline stimulus, there was an increased activation in the visual areas (occipital, fusiform and lingual gyri), in the cerebellum, in the parietal cortex [etc] ... Conversely, the temporal regions, insula and putamen were found to be activated using the XBAM analysis software only.*This begs two questions: why the difference, and which way is right?The difference must be a product of the different methods used. SPM uses a technique called statistical parametric mapping (hence the name) based on the assumption of normality. FSL and BrainVoyager do too. XBAM, on the other hand, differs from more orthodox software in a number of other ways; the most basic difference is that it uses non-parametric statistics but this document lists no less than five major innovations -"not to assume normality but to use permutation testing to construct the null distribution used to make inference about the probability of an "activation" under the null hypothesis.""recognizing the existence of correlation in the residuals after fitting a statistical model to the data."using "a mixed effects analysis of group level fMRI data by taking into account both intra and inter subject variances."using "3D cluster level statistics based on cluster mass (the sum of all the statistical values in the cluster) rather than cluster area (number of voxels)."using "a wavelet-based time series permutation approach that permitted the handling of complex noise processes in fMRI data rather than simple stationary autocorrelation."Phew. Which combination of these are responsible for the difference is impossible to say.The biggest question, though, is: should we all be using XBAM? Is it "better" than SPM? This is where things get tricky. The truth is that there's no right way to statistically analyze any data, let alone fMRI data. There are lots of wrong ways, but even if you avoid making any mistakes, there are still various options as to which statistical methods to use, and which method you use depends on which assumptions you're making. XBAM rests of different assumptions from SPM.Whether XBAM's assumptions are more appropriate than those of SPM is a difficult question. The people who wrote XBAM think so, and they're very smart people. But so are the people who wrote SPM. The point is, it's a very complex issue, the mathematical details of which go far beyond the understanding of most fMRI users (myself included).My worry about this paper is that the average Joe Neuroscientist will decide that, because XBAM produces more activation than SPM, it must be "better". The authors are careful not to say this, but for fMRI researchers working in the publish-or-perish world of modern science, and whose greatest fear is that they'll run an analysis and end up with no blobs at all, the temptation to think "the more blobs the merrier" is a powerful one.Fusar-Poli, P., Bhattacharyya, S., Allen, P., Crippa, J., Borgwardt, S., Martin-Santos, R., Seal, M., O’Carroll, C., Atakan, Z., & Zuardi, A. (2010). Effect of image analysis software on neurofunctional activation during processing of emotional human faces Journal of Clinical Neuroscience DOI: 10.1016/j.jocn.2009.06.027... Read more »
Fusar-Poli, P., Bhattacharyya, S., Allen, P., Crippa, J., Borgwardt, S., Martin-Santos, R., Seal, M., O’Carroll, C., Atakan, Z., & Zuardi, A. (2010) Effect of image analysis software on neurofunctional activation during processing of emotional human faces. Journal of Clinical Neuroscience. DOI: 10.1016/j.jocn.2009.06.027
Capitalists beware. No less a journal than Nature has just published a paper proving conclusively that the human brain is a Communist, and that it's plotting the overthrow of the bourgeois order and its replacement by the revolutionary Dictatorship of the Proletariat even as we speak.Kind of. The article, Neural evidence for inequality-averse social preferences, doesn't mention the C word, but it does claim to have found evidence that people's brains display more egalitarianism than people themselves admit to.Tricomi et al took 20 pairs of men. At the start of the study, both men got a $30 payment, but one member of each pair was then randomly chosen to get a $50 bonus. Thus, one guy was "rich", while the other was "poor". Both men then had fMRI scans, during which they were offered various sums of money and saw their partner being offered money too. They rated how "appealing" these money transfers were on a 10 point scale.What happened? Unsurprisingly both "rich" and "poor" said that they were pleased at the prospect of getting more cash for themselves, the poor somewhat more so, but people also had opinions about payments to the other guy:the low-pay group disliked falling farther behind the high-pay group (‘disadvantageous inequality aversion’), because they rated positive transfers to the high-pay participants negatively, even though these transfers had no effect on their own earnings. Conversely, the high-pay group seemed to value transfers [to the poor person] that closed the gap between their earnings and those of the low-pay group (‘advantageous inequality aversion’)What about the brain? When people received money for themselves, activity in the ventromedial prefrontal cortex (vmPFC) and the ventral striatum correlated with the size of their gain.However, when presented with a payment to the other person, these areas seemed to be rather egalitarian. Activity rose in rich people when their poor colleagues got money. In fact, it was greater in that case than when they got money themselves, which means the "rich" people's neural activity was more egalitarian than their subjective ratings were. Whereas in "poor" people, the vmPFC and the ventral striatum only responded to getting money, not to seeing the rich getting even richer.The authors conclude that thisindicates that basic reward structures in the brain may reflect even stronger equity considerations than is necessarily expressed or acted on at the behavioural level... Our results provide direct neurobiological evidence in support of the existence of inequality-averse social preferences in the human brain.Notice that this is essentially a claim about psychology, not neuroscience, even though the authors used neuroimaging in this study. They started out by assuming some neuroscience - in this case, that activity in the vmPFC and the ventral striatum indicates reward i.e. pleasure or liking - and then used this to investigate psychology, in this case, the idea that people value equality per se, as opposed to the alternative idea, that "dislike for unequal outcomes could also be explained by concerns for social image or reciprocity, which do not require a direct aversion towards inequality."This is known as reverse inference, i.e. inference from data about the brain to theories about the mind. It's very common in neuroimaging papers - we've all done it - but it is problematic. In this case, the problem is that the argument relies on the idea that activity in the vmPFC and ventral striatum is evidence for liking.But while there's certainly plenty of evidence that these areas are activated by reward, and the authors confirmed that activity here correlated with monetary gain, that doesn't mean that they only respond to reward. They could also respond to other things. For example, there's evidence that the vmPFC is also activated by looking at angry and sad faces.Or to put it another way: seeing someone you find attractive makes your pupils dilate. If you were to be confronted by a lion, your pupils would dilate. Fortunately, that doesn't mean you find lions attractive - because fear also causes pupil dilation.So while Tricomi et al argue that people, or brains, like equality, on the basis of these results, I remain to be fully convinced. As Russell Poldrack noted in 2006caution should be exercised in the use of reverse inference... In my opinion, reverse inference should be viewed as another tool (albeit an imperfect one) with which to advance our understanding of the mind and brain. In particular, reverse inferences can suggest novel hypotheses that can then be tested in subsequent experiments.Tricomi E, Rangel A, Camerer CF, & O'Doherty JP (2010). Neural evidence for inequality-averse social preferences. Nature, 463 (7284), 1089-91 PMID: 20182511... Read more »
Tricomi E, Rangel A, Camerer CF, & O'Doherty JP. (2010) Neural evidence for inequality-averse social preferences. Nature, 463(7284), 1089-91. PMID: 20182511
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