Category: neuroscience

The Neural Correlates of Romantic Love

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ResearchBlogging.org

For the most part, fMRI studies attempt to localize cognitive processes to specific regions in the brain. Popular media often introduce these studies with headlines that tout the discovery of “the brain region” for memory, language, empathy, moral reasoning, loving weiner schnitzel and so on.

These headlines can be terribly misleading, as they’re often misinterpreted to suggest a specific brain region is dedicated to a single function, when, in fact, any given function maps on to a network of regions (forming a circuit), while any given region is part of multiple circuits subserving many functions. Similar faux pas can be found in descriptions of the functions associated with genes, e.g. “The gene for (fill in the blank).”

A few years back, the NY Times ran an infamous piece featuring the work of a neuromarketing company. In a horrible experiment fit for The Onion, participants lay in the scanner while looking at pictures of then presidential candidates. Subjects showed increased amygdala activation to pictures of Mitt Romney, which researchers interpreted as a sign of anxiety.

But after watching Romney speak on video, the amygdala activity died down, which researchers said showed that voters’ anxiety had decreased.

Meanwhile subjects’ anterior cingulates lit up to pictures of Hillary Clinton.

Here’s how researchers interpreted this neural activity:

Emotions about Hillary Clinton are mixed. Voters who rated Mrs. Clinton unfavorably on their questionnaire appeared not entirely comfortable with their assessment. When viewing images of her, these voters exhibited significant activity in the anterior cingulate cortex, an emotional center of the brain that is aroused when a person feels compelled to act in two different ways but must choose one. It looked as if they were battling unacknowledged impulses to like Mrs. Clinton.

The Times article about the “research” was quickly and roundly criticized by prominent neuroscientists, 17 of whom quickly responded with a signed letter to the editor, which the Times ran a couple of days later:

To the Editor:

“This Is Your Brain on Politics” (Op-Ed, Nov. 11) used the results of a brain imaging study to draw conclusions about the current state of the American electorate. The article claimed that it is possible to directly read the minds of potential voters by looking at their brain activity while they viewed presidential candidates.

For example, activity in the amygdala in response to viewing one candidate was argued to reflect “anxiety” about the candidate, whereas activity in other areas was argued to indicate “feeling connected.” While such reasoning appears compelling on its face, it is scientifically unfounded.

As cognitive neuroscientists who use the same brain imaging technology, we know that it is not possible to definitively determine whether a person is anxious or feeling connected simply by looking at activity in a particular brain region. This is so because brain regions are typically engaged by many mental states, and thus a one-to-one mapping between a brain region and a mental state is not possible.As cognitive neuroscientists, we are very excited about the potential use of brain imaging techniques to better understand the psychology of political decisions. But we are distressed by the publication of research in the press that has not undergone peer review, and that uses flawed reasoning to draw unfounded conclusions about topics as important as the presidential election.

Adam Aron, Ph.D., University of California, San Diego
David Badre, Ph.D., Brown University
Matthew Brett, M.D., University of Cambridge
John Cacioppo, Ph.D., University of Chicago
Chris Chambers, Ph.D., University College London
Roshan Cools, Ph.D., Radboud University, Netherlands
Steve Engel, Ph.D., University of Minnesota
Mark D’Esposito, M.D., University of California, Berkeley
Chris Frith, Ph.D., University College London
Eddie Harmon-Jones, Ph.D., Texas A&M University
John Jonides, Ph.D., University of Michigan
Brian Knutson, Ph.D., Stanford University
Liz Phelps, Ph.D., New York University
Russell Poldrack, Ph.D., University of California, Los Angeles
Tor Wager, Ph.D., Columbia University
Anthony Wagner, Ph.D., Stanford University
Piotr Winkielman, Ph.D., University of California, San Diego

Undoubtedly, fewer people saw that letter than saw the original article, which was much more prominently displayed.

(By the above study’s logic, looking at a picture of Donald Trump should elicit activity in the anterior insula, a region often associated with disgust responses)

It’s unfortunate that the study received such a prominent platform for distribution because people, especially non scientists, can be heavily influenced by articles with pictures of brains or technical sounding neuro language. One study, which I’ve written about on the blog, found that people were much more likely to believe a nonsensical article if it had meaningless neuroscience language in it than if it didn’t. As the average lay person doesn’t possess the technical skills to distinguish between valid and invalid fMRI studies, it’s up to the scientific community to police itself, which it does a pretty good job of through the peer review process.

This next study I’ll talk about demonstrates some of the challenges inherent to mapping localized neural activity onto unseen mental processes; in this case, the subjective experience of intense, romantic long-term love.

Aaron and colleagues previously published a study that presented neural correlates of intense romantic love (2005). In brief, the study reported that regions in the reward circuit of the brain were activated in response to pictures of a lover (versus a close friend). In the current study, they wanted to explore if these findings could be extended to long-term married couples (couples together for more than 20+ years who report still being madly in love).

Participants lay in the scanner and were repeatedly presented with pictures from four different categories: their partner, a close friend, and both a highly familiar and low-familiar neutral acquaintance. They were instructed to think about “experiences with each stimulus person (that were) nonsexual in nature.”

The fMRI data was analyzed via subtraction, a common fMRI analysis method in which one condition is compared to another to see if any differences fall out. The contrast of interest was between the partner and the close friend. In a cognitive process sense, the only difference thought to exist between perceiving these two individuals was thought to be the subject’s romantic love for one and not for the other. So if neural activity in the close friend condition is subtracted from activity in the partner condition, whatever is left over should represent the neural substrate of romantic love.

Researchers found activation in the ventral tegmental area, substantia nigra and nucleus accumbens (and the hippocampus, which corresponded with reported sex frequency, but the effect seems to be driven largely by two outliers, one of whom reported they have sex almost every day).

The activity does suggest a classic reward response and replicates previous findings. However, the big question isn’t whether there is a response, but rather what’s driving it?

A valid fMRI study doesn’t only rely on the integrity or analysis of the fMRI data, but, also, and perhaps more importantly, on the experimental design. In order to attribute increased activation in one condition versus the other to a specific cognitive function, one must be confident they have created conditions that have cleanly isolated the independent variable of interest (romantic love). The ventral tegmental area and other regions in the basal ganglia have been repeatedly shown to encode reward value – that is, they respond to things that give us hedonic pleasure, such as food, drugs, sex or receiving money. Past work has shown that intense romantic love is associated with activity in the those regions (Aaron 2005). In the current study, activity in some neural regions previously associated with maternal pair bonding was shown (substantia nigra, for one). The authors hypothesized that neural correlates for romantic long-term love should encompass those associated with both intense romantic love and maternal pair bonding.

But this analysis is dependent on long-term, romantic love being the only difference between conditions that would explain the differences in brain activity. And that may not entirely be the case.

Alternative Explanations
Just to refresh, the major dependent measure of interest was neural activity, especially of reward circuitry, while subjects looked at pictures of their long-term partner versus a close friend. One additional difference between these conditions (beyond romantic love) is that romantic partners are probably more familiar and closer to participants than close friends. This is a shortcoming acknowledged by the authors.

This difference suggests a causal chain of cognitive operations that could offer alternative explanations for some of the data seen in this study. First, It’s been shown that we prefer things that are familiar to us (the “mere exposure” effect, Zajonc, 1968). Second, we’re able to process familiar things (or people) much more fluently compared to the less familiar (Reber). Third, fluency processing has been associated with judgments of aesthetic appreciation such that the more fluently we can process something, the more beautiful or attractive we’re likely to rate it (Alter). Although the objective attractiveness of the photos was controlled for via a group of independent raters, the participants were likely much more subjective in their judgments and perhaps found their partners more attractive than an objective viewer might. Viewing attractive faces has been shown to elicit strong neural activity, particularly in the reward circuitry (NaCC and OFC).

Furthermore, it has been posited that people incorporate close others into their psychological construct of self. Recent studies (deGreck 2008) showed that regions active in a reward task, such as the bilateral ventral striatum, and the ventral tegmental area (VTA), are also involved in differentiating between high and low personal relevance.It seems that we find thinking about ourselves pretty damn rewarding! (We’re all at least a little bit narcissistic). To the extent that someone has been incorporated into our self concept, thinking about that person, or looking at their picture as in this study, could be correlated with responses in reward regions of the brain in part because they activate thoughts of ourselves.

Both the familiarity –> processing fluency –> attractiveness model and self relevant thinking are plausible alternative explanations for at least some of the neural correlates found in this paper.

One other potential area of concern is that there is no way of knowing that participants weren’t thinking about sex with their partners, even though they were told not to. This might be especially difficult to achieve, especially for the two outliers who reported almost daily sex. Regions active during sexual arousal include R. amygdala, hypothalamus, hippocampus, midbrain, mOFC and nucleus accumbens, many of which were found to be active in this study.

The neural activity measured here may very well reflect some aspect of individuals’ love for their partners. But there seem to be other possible explanations for some of the data. I suppose that’s why people call the study of consciousness, of which subjective experiences such as romantic love are a subset, the “hard problem.”

References
Acevedo BP, Aron A, Fisher HE, & Brown LL (2011). Neural correlates of long-term intense romantic love. Social cognitive and affective neuroscience PMID: 21208991

Aron, A., Fisher, H., Mashek, D., Strong, G., Li, H., Brown, L. (2005). Reward, motivation and emotion systems associated with early-stage intense romantic love. Journal of Neurophysiology, 93, 327–37.

DEGRECK, M., ROTTE, M., PAUS, R., MORITZ, D., THIEMANN, R., PROESCH, U., BRUER, U., MOERTH, S., TEMPELMANN, C., & BOGERTS, B. (2008). Is our self based on reward? Self-relatedness recruits neural activity in the reward system NeuroImage, 39 (4), 2066-2075 DOI: 10.1016/j.neuroimage.2007.11.006

Alter, A., & Oppenheimer, D. (2008). Easy on the mind, easy on the wallet: The roles of familiarity and processing fluency in valuation judgments Psychonomic Bulletin & Review, 15 (5), 985-990 DOI: 10.3758/PBR.15.5.985

Peskin, M., & Newell, F. (2004). Familiarity breeds attraction: Effects of exposure on the attractiveness of typical and distinctive faces Perception, 33 (2), 147-157 DOI: 10.1068/p5028

Reber, R., Schwarz, N., & Winkielman, P. (2004). Processing Fluency and Aesthetic Pleasure: Is Beauty in the Perceiver’s Processing Experience? Personality and Social Psychology Review, 8 (4), 364-382 DOI: 10.1207/s15327957pspr0804_3

Smoking makes impulsive teen rats even more impulsive

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It’s one of the truisms of human life that teenagers often do silly, stupid and/or dangerous things. We certainly don’t need science to tell us that. One reason this seems to be the case is that, on average, teens have trouble optimally weighing risk vs. reward. I’m not excluding myself from this characterization. In fact, I sometimes marvel that I survived my teen years intact, if at all.

One stupid thing I and many of my friends did as teenagers was to try smoking.

There are no rational arguments in favor of smoking. Yet, according to one study, most adult smokers start before age 19 and 70% of all adolescents report trying a cigarette at least once. Messages directed to adolescents and teens against smoking often fall on deaf ears. In addition to subpar decision making skills, many teens hold the advice of their elders in low regard and are apt to pick up a cigarette as an act of defiance or as a show of their burgeoning adulthood. Hollywood films certainly contribute to the smoking mythology through their noble portrayals of troubled, rebellious or misunderstood teens reaching for smokes when the chips are down.

Although the health risks associated with smoking are widely known, a recent Nature Neuroscience study has provided even more reasons for teens to avoid smoking. Researchers from the Netherlands found that in adolescent rats, exposure to smoking led to increased and long lasting impulsiveness and impaired measures of attention in adulthood. In contrast, adult animals exposed to similar levels of nicotine did not show these long term effects. So, the impulsiveness that might lead a teen to try smoking could be increased by the very product of that impulsiveness, creating a vicious feedback cycle. Nasty business.

What’s the molecular mechanism? A proteomic analysis of 297 different mPFC proteins in adolescent rats who had exposure to smoking showed that levels of mGLuR2 was downregulated. mGluR2 is a metabotropic glutamatergic receptor that sits on the presynaptic side of synapses in the mPFC, a brain region important for cognitive control and attention. Adolescent nicotine exposure resulted in decreased mGLuR2 signaling and reduced plasticity in the mPFC. This was shown to be directly related to attentional deficits by a rescue experiment in which a glutamate agonist was injected into the mPFC in vivo. The agonist restored attentional performance to normal levels but didn’t affect impulsiveness.

In sum, the adolescent brain is more susceptible to the consequences of smoking via alteration of synaptic mGluR2 protein levels. It’s known that nicotine exerts its initial effects on the brain through nicotinic acetylcholine receptor activation and this study suggests that adolescents are uniquely vulnerable to increased activation of these receptors.

The researchers acknowledge that the sequence of molecular events is unknown, but speculate that “…mGluR2 levels following nicotine exposure at the end of adolescence compensate for nicotine’s actions and inhibit neurotransmitter release.” One caveat to keep in mind is that it’s unknown the extent to which this effect would be replicated in humans. Another important point is that in this experiment, nicotine was dissolved in solution and administered subcutaneously. Cigarettes contain many other carcinogens and toxins to which adolescents could be particularly vulnerable, so the long-term cognitive effects of cigarette smoking could extend far beyond those uncovered in this study, which looked just at nicotine.

The takeaway message is definitely clear: Parents, do everything you can to keep your kids from smoking!*

*I’m an advocate for making the sale of tobacco and tobacco related products illegal. Tobacco offers no clear benefits to society, with the exception of a few thousand jobs and the enrichment of a couple handfuls of business executives, while incurring great economic costs to the nation as a whole. Although nicotine has shown some cognitive benefits to individuals in certain disease states, all in all its mostly detrimental. (I’m a member of that most annoyingly vociferous group of anti-smoking activists: ex-smokers. Maybe we’re so adamant because we know how hard it is to quit!) That long-term cognitive deficits are now being shown to accrue in cigarette smoking teens is hopefully another nail in the coffin of the tobacco industry and smoking culture in general, which will perhaps be looked back upon as a sign of the special ignorance of our times.

References

Counotte DS, Goriounova NA, Li KW, Loos M, van der Schors RC, Schetters D, Schoffelmeer AN, Smit AB, Mansvelder HD, Pattij T, & Spijker S (2011). Lasting synaptic changes underlie attention deficits caused by nicotine exposure during adolescence. Nature neuroscience, 14 (4), 417-9 PMID: 21336271

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Regard thyself and put down the smoke stick

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As many a former smoker will probably attest, quitting cigarettes ranks high in the hard-to-kick category. I made several unsuccessful attempts before finally kicking the habit after a 10 year pack-a-day run. Ultimately what worked for me was to go cold turkey, but there were perhaps other alternatives which I might have tried. In a paper from Nature Neuroscience, researchers from University of Michigan provided participants with interventions involving individually tailored messages* designed to encourage quitting and found that participants’ brain activity while listening to the messages predicted how likely they would be to successfully quit smoking.

*Tailored messages are statements about an individuals’ issues and thoughts about quitting smoking, derived from pre-screen interviews with them. e.g., “You are worried that when angry or frustrated, you may light up”.

Here’s the premise: Anti-smoking messages custom made for an individual can be more effective than generic ones, but only if said individual processes those messages in a self directed manner. Past research has shown a specific set of neural regions – primarily the mPFC and precuneus/posterior cingulate – to be associated with self referential thinking. Therefore, researchers hypothesized, activity in these brain regions while processing tailored anti-smoking messages might predict the likelihood of quitting.

The Study
The experiment was carried out over three days with a follow-up visit four months later.

Day 1: 91 participants completed a health assessment, demographic questionnaire and a psychosocial characteristics scale related to quitting smoking. Responses were then used to create smoking cessation messages tailored to each individual.
Day 2: Participants went into scanner and performed 2 fMRI tasks: The first task had participants listen to anti-smoking messages of three different types: personally tailored anti-smoking, non-tailored anti-smoking and neutral.

Here are some examples of what they heard:

Tailored messages
A concern you have is being tempted to smoke when around other smokers.
Something else that you feel will tempt you after you quit is because of a craving.
You are worried that when angry or frustrated, you may light up.
Untailored messages
Some people are tempted to smoke to control their weight or hunger.
Smokers also light up when they need to concentrate.
Certain moods or feelings, places, and things you do can make you want to smoke.
Neutral messages
Oil was formed from the remains of animals and plants that lived millions of years ago.
Sighted in the Pacific Ocean, the world’s tallest sea wave was 112 feet.
Wind is simple air in motion. It is caused by the uneven heating of the earth’s surface by the sun.

Then, participants completed a self appraisal task to identify brain regions active during self relevant thought processes. In this task, participants saw adjectives appear on the screen and had to either rate how much the adjective described them or whether the adjective was positive or negative.

Day 3: Participants completed a web-based smoking cessation program and were instructed to quit smoking. (They were given a supply of nicotine patches to get themselves started)

Results
Behavioral
Experimenters checked in with subjects four months later to see if they were abstaining from smoking. Out of 87 who participated in the smoking cessation program, 45 were not smoking, while 42 were still (or had quit briefly and restarted) smoking.

Subjects were given a surprise memory test for the anti-smoking messages they’d received four months prior and remembered self relevant, tailored messages most well. However, their memory performance was not related to whether they successfully quit smoking.

fMRI
As for the fMRI data, experimenters used a mask of tailored vs. untailored message conditions AND self-appraisal to identify the region common to both processes. This seems like a mild case of double dipping, no? That is, finding a brain region that responds to the condition of interest (in this case, voxels more active in tailored vs. untailored conditions) and then using the same data to test the hypothesis. Ideally, the ROI would be obtained independently of the main task.

A blow by blow on the different contrasts of interest:

1. Researchers looked at brain regions more active during tailored vs. untailored messages and found differential activation in the regions below.

There are, I think, some problems here; mainly, that the task differences for processing tailored vs non-tailored statements may extend beyond self relevant thinking to (1) memory processes employed in processing either category of stimuli; that is, episodic (tailored) vs. semantic (non-tailored), (2) cognitive effort, (3) elicitation of visual vs. non-visual memory, (4) processing fluency and (5) affect or reward responses. Thus, the difference in brain activation found in this task might reflect something other than just self referential processing.

2. The localizer task (used to isolate neural areas involved in self appraisal) had participants process adjectives either by relating them to self or by judging their affective value. This suggests an alternative explanation for the categorical contrast in that it isn’t specific to self per se, but really more specific to people vs. non-people. A more widely used version of this task has participants process adjectives with regards to self or an other. As a further control, a third condition is often included in which participants identify whether words are in upper case or lower case. The contrast applied is (self – control) – (other – control). It’s not clear why the researchers chose the task they did, which seems significantly noisier.

Here’s the contrast from the present study:

And here’s a contrast from another study (Jenkins 2010) that looked at three different types of self-referential processing.

Although roughly similar, the current study shows cortical midline activation seems to be much more dorsal than that found in Jenkins (2010). Using an ROI derived from this localizer task to correlate neural activity in tailored vs. untailored statements with quitting led to a non-significant result (from supplementary materials). This could explain why the researchers used the composite mask to define the ROI.

3. Again, the primary ROI was defined as a composite of overlapping regions between the self reference task AND the tailored vs. untailored statements task, which was used to compare neural activity with quitting behavior. They found that activity in these regions – which included dmPFC, precuneus and angular gyrus – during tailored smoking cessation messages predicted the likelihood of successfully abstaining from smoking. dmPFC and precuneus activation also individually predicted smoking cessation success, although angular gyrus did not.

This study provides clear evidence that participants processed tailored vs. non-tailored messages about smoking differently, and that this difference corresponded to their ability to stop smoking. However,
(1) neither task effectively isolates self referential processing,
(2) the region of activation was much more dorsal than that usually found in this literature (Northoff & Bermpohl, 2004; Schneider et al.,2008; Uddin, Iacoboni, Lange, & Keenan, 2007; Gillihan & Farah, 2005),
(3) an independently obtained ROI yielded insignificant results and
(4) mPFC and precuneus subserve an untold number of cognitive processes beyond self reflection.

Therefore, it seems a bit of a stretch to claim the neural activation found in this study is indicative of self referential processing.

References
Chua HF, Ho SS, Jasinska AJ, Polk TA, Welsh RC, Liberzon I, & Strecher VJ (2011). Self-related neural response to tailored smoking-cessation messages predicts quitting. Nature neuroscience, 14 (4), 426-7 PMID: 21358641

Jenkins AC, & Mitchell JP (2010). Medial prefrontal cortex subserves diverse forms of self-reflection. Social neuroscience, 1-8 PMID: 20711940

Northoff, G. (2005). Emotional-cognitive integration, the self, and cortical midline structures Behavioral and Brain Sciences, 28 (02) DOI: 10.1017/S0140525X05400047

Gillihan, S., & Farah, M. (2005). Is Self Special? A Critical Review of Evidence From Experimental Psychology and Cognitive Neuroscience. Psychological Bulletin, 131 (1), 76-97 DOI: 10.1037/0033-2909.131.1.76

SCHNEIDER, F., BERMPOHL, F., HEINZEL, A., ROTTE, M., WALTER, M., TEMPELMANN, C., WIEBKING, C., DOBROWOLNY, H., HEINZE, H., & NORTHOFF, G. (2008). The resting brain and our self: Self-relatedness modulates resting state neural activity in cortical midline structures Neuroscience, 157 (1), 120-131 DOI: 10.1016/j.neuroscience.2008.08.014

UDDIN, L., IACOBONI, M., LANGE, C., & KEENAN, J. (2007). The self and social cognition: the role of cortical midline structures and mirror neurons Trends in Cognitive Sciences, 11 (4), 153-157 DOI: 10.1016/j.tics.2007.01.001

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Mirror Neurons and Mentalizing

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Perhaps few findings in the cognitive sciences have received more press in recent years than the discovery by Rizolatti and colleagues in macque monkeys of mirror neurons; that is, neurons that preferentially activate both when a monkey performs some action and when observing someone else perform the same action. There is evidence that these neurons exist in humans, although it’s indirect (however, see Keysers 2010). They’ve quite captivated the publics’ attention, these crafty little neurons.

The mirror neuron system is thought to help primates, non-human and human, understand what others are doing by simulating the motor plan of an observed action and also allowing for prediction of the most likely outcome of an observed action. In other words, mirror neurons are sensitive both to actions and outcomes, and to some extent, inferring the why behind the what. Many have suggested that they play a significant role in comprehending mental states and empathic processes. But it’s in regards to these latter claims where the evidence is not as clear.

So, how does the brain intuit others’ inherently unobservable mental states in the absence of biological action? Much of the research evidence points to the mentalizing system, also known as the theory-of-mind network, as the neural network tasked to the job (see meta-analysis by Van Overwalle and Baetens, 2009). Anatomically speaking, these networks are distinct, with the mirror neurons located primarily in the ifraparietal sulcus, superior temporal sulcus and the prefrontal cortex, while the mentalizing system constitutes a distinct set of brain regions that lie along the cortical midline and in the temporal lobes, including the mPFC, TPJ, temporal poles, PCC and posterior STS.

One of the big challenges in this area of research is in designing tasks that are able to effectively disentangle processing of motor action from mentalizing. This is quite a challenge because it’s difficult to know what kind of mental process participants are applying to any given set of social stimuli. Do participants engage in higher-order abstract mentalizing automatically, and even when the stimuli might not necessarily demand it? How can we know what mental process subjects are engaging in? In other words, how might one capture the distinction between perceiving what others are doing vs. obtaining a more abstract representation of why they might be doing it?

UCLA’s Bob Spunt and colleagues (2011) designed a study that would attempt to do just that. They had participants observe short video clips of a human performing an action and directed the participants, in the scanner, to covertly describe each video clip in terms of (1) what an actor was doing, (2) why he was doing it, (3) how we was doing it or (4) to just passively view the video. They were to start the process of covert description once the video started playing, begin their description with the word “he” (e.g. he is reading) and to press a button once they were done.

(Thanks to the researchers for providing the video)

For example, in the above example, participants might have covertly described that the man is reading (WHAT), that he wants to learn or is bored (WHY), or that he is flipping pages or gripping the book (HOW).

This had the effect of creating three levels of mentalizing “depth” while holding the action component constant. If the mirror neuron network was involved in the mentalizing process, then one would expect to see neural activation increases in the mirror neuron network covarying with the increase in participants presumed mentalizing about the actor. And if the mirror neuron network was involved in mentalizing, then one would expect to see increased activations in neural regions which have been previously suggested to contain mirror neurons.

Results
In support of the theory that mirror neurons don’t play a significant role in mentalizing, the researchers found no increase in the mirror neuron network in response to increases in mentalizing. But they did find increased activation in brain regions associated with mentalizing, including dorsal and ventral medial pFC, posterior cingulate cortex, and the temporal poles.

Conclusion
The study does provide another piece of support to the position that although the mirror neuron system might be necessary in understanding actions of the body, it’s not sufficient to explain the cognitive processes required to infer unobservable mental states.

References
Spunt, R., Satpute, A., & Lieberman, M. (2011). Identifying the What, Why, and How of an Observed Action: An fMRI Study of Mentalizing and Mechanizing during Action Observation Journal of Cognitive Neuroscience, 23 (1), 63-74 DOI: 10.1162/jocn.2010.21446

Keysers, C., & Gazzola, V. (2010). Social Neuroscience: Mirror Neurons Recorded in Humans Current Biology, 20 (8) DOI: 10.1016/j.cub.2010.03.013

Van Overwalle F, & Baetens K (2009). Understanding others’ actions and goals by mirror and mentalizing systems: a meta-analysis. NeuroImage, 48 (3), 564-84 PMID: 19524046

ResearchBlogging.org

worthy links: Rama, acupuncture, disgust and politics (redux), mouse sex

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V.S. Ramachandran gives a stimulating TED lecture and a short interview, mostly about mirror neurons, over at Neurophilosophy.

NeuroLogica’s Steven Novella recaps a recent study showing that acupuncture doesn’t work — and points out the clever way in which the failure was spun by the study’s authors.

Just the other day, I summarized a recent study looking at the relationship between disgust/purity and political ideology. In this short video, a brief discourse by Yale’s Paul Bloom on the topic.

Over at Not Exactly Rocket Science, Ed Wong talks about work out of Bejing that showed male mice with reduced serotonin levels became less choosy about the sex of their sexual partners. And as should be expected, the sensationalistic headlines from mass media organizations shortly followed. From the BBC: “Sexual preference chemical found” And from CBS News, a NY Post-worthy headline: “Serotonin sex bomb: How to make a mouse bisexual or just really horny”