Posts Tagged ‘Functional magnetic resonance imaging’

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This past friday, I attended my first meditation session at my new yoga school.  I love this school and hope – someday – to make it through the full Ashtanga series and other sequences the instructors do.  In the meantime, I found myself sitting on my folded up blanket, letting my mind wander, listening to my breath and just trying to enjoy the moment.

What a wonderful experience it was … it felt great!  … I think I my have even given my brain a rest. A simple kindness to repay it for all it has done for me!

Although I did not know what I was supposed to be “doing” during meditation, the experience itself has me hooked and fascinated with a new research article, “Genetic control over the resting brain” [doi: 10.1073/pnas.0909969107]  by David Glahn and colleages.

Reading this paper, I learned that my brain “at rest” is really very active with neural activity in a series of interconnected circuits known as the default network.  Moreover, the research team finds that many of these interconnected circuits fire together in a way that is significantly influenced by genetic factors (overall heritability of about 0.42).  By analyzing the resting state (lay in the MRI and let your mind wander) patterns of activity in 333 folks from extended pedigrees, the team shows that certain interconnections (neural activity between 2 or more regions) within the default network are more highly correlated in people who are more related to each other.  For example, the left parahippocampal region was genetically correlated with many of the other brain areas in the default network.

Of course, these genetic effects on resting state connectivity are far from determinative, and the authors noted that some interconnections within the default network were more sensitive to environmental factors – such as functional connectivity between right temporal-parietal & posterior cingulate/precuneus & medial prefronal cortex.

Wow, so my resting state activity must – at some level – as a partial product of my genome – be rather unique and special.  It certainly felt that way as my mind wandered freely during meditation class. The authors point out that their heritability study lays more groundwork for follow-up gene hunting expeditions to isolate specific genetic variants.  This will be very exciting!

Some other items from their paper that I’ll be pondering in my next meditation class are the facts that these default neural networks are already present in the infant brain!  and in our non-human primate cousins (even when they are not conscious)!  Whoa!  These genetics & resting-state brain studies will really push our sense of what it means to be human, to be unique, to be interconnected by a common (genetic) thread from generation to generation over vast spatial and temporal distances (is this karma of sorts?).

I suppose yogis & other practitioners of meditation might be bemused at this recent avenue of “cutting edge” scientific inquiry – I mean – duh?!  of course, it makes sense that by remaining calm and sitting quietly that we would discover ourselves.

Related posts here, here, here

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According to wikipedia, “Jean Philippe Arthur Dubuffet (July 31, 1901 – May 12, 1985) was one of the most famous French painters and sculptors of the second half of the 20th century.”  “He coined the term Art Brut (meaning “raw art,” often times referred to as ‘outsider art’) for art produced by non-professionals working outside aesthetic norms, such as art by psychiatric patients, prisoners, and children.”  From this interest, he amassed the Collection de l’Art Brut, a sizable collection of artwork, of which more than half, was painted by artists with schizophrenia.  One such painting that typifies this style is shown here, entitled, General view of the island Neveranger (1911) by Adolf Wolfe, a psychiatric patient.

Obviously, Wolfe was a gifted artist, despite whatever psychiatric diagnosis was suggested at the time.  Nevertheless, clinical psychiatrists might be quick to point out that such work reflects the presence of an underlying thought disorder (loss of abstraction ability, tangentiality, loose associations, derailment, thought blocking, overinclusive thinking, etc., etc.) – despite the undeniable aesthetic beauty in the work.  As an ardent fan of such art,  it made me wonder just how “well ordered” my own thoughts might be.  Given to being rather forgetful and distractable, I suspect my thinking process is just sufficiently well ordered to perform the routine tasks of day-to-day living, but perhaps not a whole lot more so.  Is this bad or good?  Who knows.

However, Krug et al., in their recent paper, “The effect of Neuregulin 1 on neural correlates of episodic memory encoding and retrieval” [doi:10.1016/j.neuroimage.2009.12.062] do note that the brains of unaffected relatives of persons with mental illness show subtle differences in various patterns of activation.  It seems that when individuals are using their brains to encode information for memory storage, unaffected relatives show greater activation in areas of the frontal cortex compared to unrelated subjects.  This so-called encoding process during episodic memory is very important for a healthy memory system and its dysfunction is correlated with thought disorders and other aspects of cognitive dysfunction.  Krug et al., proceed to explore this encoding process further and ask if a well-known schizophrenia risk variant (rs35753505 C vs. T) in the neuregulin-1 gene might underlie this phenomenon.  To do this, they asked 34 TT, 32 TC and 28 CC individuals to perform a memory (of faces) game whilst laying in an MRI scanner.

The team reports that there were indeed differences in brain activity during both the encoding (storage) and retrieval (recall) portions of the task – that were both correlated with genotype – and also in which the CC risk genotype was correlated with more (hyper-) activation.  Some of the brain areas that were hyperactivated during encoding and associated with CC genotype were the left middle frontal gyrus (BA 9), the bilateral fusiform gyrus and the left middle occipital gyrus (BA 19).  The left middle occipital gyrus showed gene associated-hyperactivation during recall.  So it seems, that healthy individuals can carry risk for mental illness and that their brains may actually function slightly differently.

As an ardent fan of Art Brut, I confess I hoped I would carry the CC genotype, but alas, my 23andme profile shows a boring TT genotype.  No wonder my artwork sucks.  More on NRG1 here.

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The A-to-T SNP rs7794745 in the CNTNAP2 gene was found to be associated with increased risk of autism (see Arking et al., 2008).  Specifically, the TT genotype, found in about 15% of individuals, increases these folks’ risk by about 1.2-1.7-fold.  Sure enough, when I checked my 23andMe profile, I found that I’m one of these TT risk-bearing individuals.  Interesting, although not alarming since me and my kids are beyond the age where one typically worries about autism.  Still, one can wonder if such a risk factor might have exerted some influence on the development of my brain?

The recent paper by Tan et al., “Normal variation in fronto-occipital circuitry and cerebellar structure with an autism-associated polymorphism of CNTNAP2” [doi:10.1016/j.neuroimage.2010.02.018 ] suggests there may be subtle, but still profound influences of the TT genotype on brain development in healthy individuals.  According to the authors, “homozygotes for the risk allele showed significant reductions in grey and white matter volume and fractional anisotropy in several regions that have already been implicated in ASD, including the cerebellum, fusiform gyrus, occipital and frontal cortices. Male homozygotes for the risk alleles showed greater reductions in grey matter in the right frontal pole and in FA in the right rostral fronto-occipital fasciculus compared to their female counterparts who showed greater reductions in FA of the anterior thalamic radiation.”

The FA (fractional anisotropy – a measurement of white-matter or myelination) results are consistent with a role of CNTNAP2 in the establishment of synaptic contacts and other cell-cell contacts especially at Nodes of Ranvier – which are critical for proper function of white-matter tracts that support rapid, long-range neural transmission.  Indeed, more severe mutations in CNTNAP2  have been associated with cortical dysplasia and focal epilepsy (Strauss et al., 2006).

Subtle changes perhaps influencing long-range information flow in my brain – wow!

More on CNTNAP2 … its evolutionary history and role in language development.

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In his undergraduate writings while a student at Harvard in the early 1900’s E. E. Cummings quipped that, “Japanese poetry is different from Western poetry in the same way as silence is different from a voice”.  Isabelle Alfandary explores this theme in Cummings’ poetry in her essay, “Voice and Silence in E. E. Cummings’ Poetry“,  giving some context to how the poet explored the meanings and consequences of voice and silence.  Take for example, his poem “silence”




ing;edge, of

(inquiry before snow

e.e. cummings

Lately, it seems that the brain imaging community is similarly beginning to explore the meanings and consequences of the brain when it speaks (activations whilst performing certain tasks) and when it rests quietly.  As Cummings beautifully intuits the profoundness of silence and rest,  I suppose he might have been intrigued by just how very much the human brain is doing when we are not speaking, reading, or engaged in a task. Indeed, a community of brain imagers seem to be finding that the brain at rest has quite a lot to say – moreso in people who carry certain forms of genetic variation (related posts here & here).

A paper by Perrson and colleagues “Altered deactivation in individuals with genetic risk for Alzheimer’s disease” [doi:10.1016/j.neuropsychologia.2008.01.026] asked individuals to do something rather ordinary – to pay attention to words – and later to then respond to the meaning of these words (a semantic categorization task). This simple endeavor, which, in many ways uses the very same thought processes as used when reading poetry, turns out to activate regions of the temporal lobe such as the hippocampus and other connected structures such as the posterior cingulate cortex.  These brain regions are known to lose function over the course of life in some individuals and underlie their age-related difficulties in remembering names and recalling words, etc.  Indeed, some have described Alzheimer’s disease as a tragic descent into a world of silence.

In their recordings of brain activity of subjects (60 healthy participants aged 49-79), the team noticed something extraordinary.  They found that there were differences not in how much the brain activates during the task – but rather in how much the brain de-activates – when participants simply stare into a blank screen at a small point of visual fixation.  The team reports that individuals who carry at least one copy of epsilon-4 alleles of the APOE gene showed less de-activation of their their brain (in at least 6 regions of the so-called default mode network) compared to individuals who do not carry genetic risk for Alzheimer’s disease.  Thus the ability of the brain to rest – or transition in and out of the so-called default mode network – seems impaired in individuals who carry higher genetic risk.

So, I shall embrace the poetic wisdom of E. E. Cummings and focus on the gaps, empty spaces, the vastness around me, the silences, and learn to bring my brain to rest.  And in so doing, perhaps avoid an elderly descent into silence.


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One of the complexities in beginning to understand how genetic variation relates to cognitive function and behavior is that – unfortunately – there is no gene for “personality”, “anxiety”, “memory” or any other type of “this” or “that” trait.  Most genes are expressed rather broadly across the entire brain’s cortical layers and subcortical systems.  So, just as there is no single brain region for “personality”, “anxiety”, “memory” or any other type of “this” or “that” trait, there can be no such gene.  In order for us to begin to understand how to interpret our genetic make-up, we must learn how to interpret genetic variation via its effects on cells and synapses – that go on to function in circuits and networks.  Easier said than done?  Yes, but perhaps not so intractable.

Here’s an example.  One of the most well studied circuits/networks/systems in the field of cognitive science are so-called basal-ganglia-thalamcortical loops.  These loops have been implicated in a great many forms of cognitive function involving the regulation of everything from movement, emotion and memory to reasoning ability.  Not surprisingly, neuroimaging studies on cognitive function almost always find activations in this circuitry.  In many cases, the data from neuroimaging and other methodologies suggests that one portion of this circuitry – the frontal cortex – plays a role in the representation of such aspects as task rules, relationships between task variables and associations between possible choices and outcomes.  This would be sort of like the “thinking” part of our mental life where we ruminate on all the possible choices we have and the ins and outs of what each choice has to offer.  Have you ever gone into a Burger King and – even though you’ve known for 20 years what’s on the menu – you freeze up and become lost in thought just as its your turn to place your order?  Your frontal cortex is at work!

The other aspect of this circuitry is the subcortical basla ganglia, which seems to play the downstream role of processing all that ruminating activity going on in the frontal cortex and filtering it down into a single action.  This is a simple fact of life – that we can be thinking about dozens of things at a time, but we can only DO 1 thing at a time.  Alas, we must choose something at Burger King and place our order.  Indeed, one of the hallmarks of mental illness seems to be that this circuitry functions poorly – which may be why individuals have difficulty in keeping their thoughts and actions straight – the thinking clearly and acting clearly aspect of healthy mental life.  Certainly, in neurological disorders such as Parkinson’s Disease and Huntington’s Disease, where this circuitry is damaged, the ability to think and move one’s body in a coordinated fashion is disrupted.

Thus, there are at least 2 main components to a complex system/circuits/networks that are involved in many aspects of learning and decision making in everyday life.  Therefore, if we wanted to understand how a gene – that is expressed in both portions of this circuitry – inflenced our mental life, we would have to interpret its function in relation to each specific portion of the circuitry.  In otherwords, the gene might effect the prefrontal (thinking) circuitry in one way and the basla-ganglia (action-selection) circuitry in a different way.  Since we’re all familiar with the experience of walking in to a Burger King and seeing folks perplexed and frozen as they stare at the menu, perhaps its not too difficult to imagine that a gene might differentially influence the ruminating process (hmm, what shall I have today?) and the action selection (I’ll take the #3 combo) aspect of this eveyday occurrance (for me, usually 2 times per week).

Nice idea you say, but does the idea flow from solid science?  Well, check out the recent paper from Cindy M. de Frias and colleagues “Influence of COMT Gene Polymorphism on fMRI-assessed Sustained and Transient Activity during a Working Memory Task.” [PMID: 19642882].  In this paper, the authors probed the function of a single genetic variant (rs4680 is the Methionine/Valine variant of the dopamine metabolizing COMT gene) on cognitive functions that preferentially rely on the prefronal cortex as well as mental operations that rely heavily on the basal-ganglia.  As an added bonus, the team also probed the function of the hippocampus – yet a different set of circuits/networks that are important for healthy mental function.  OK, so here is 1 gene who is functioning  within 3 separable (yet connected) neural networks!

The team focused on a well-studied Methionine/Valine variant of the dopamine metabolizing COMT gene which is broadly expessed across the pre-frontal (thinking) part of the circuitry and the basal-ganglia part of the circuitry (action-selection) as well as the hippocampus.  The team performed a neuroimaging study wherein participants (11 Met/Met and 11 Val/Val) subjects had to view a series of words presented one-at-a-time and respond if they recalled that a word was a match to the word presented 2-trials beforehand  (a so-called “n-back task“).  In this task, each of the 3 networks/circuits (frontal cortex, basal-ganglia and hippocampus) are doing somewhat different computations – and have different needs for dopamine (hence COMT may be doing different things in each network).  In the prefrontal cortex, according to a theory proposed by Robert Bilder and colleagues [doi:10.1038/sj.npp.1300542] the need is for long temporal windows of sustained neuronal firing – known as tonic firing (neuronal correlate with trying to “keep in mind” all the different words that you are seeing).  The authors predicted that under conditions of tonic activity in the frontal cortex, dopamine release promotes extended tonic firing and that Met/Met individuals should produce enhanced tonic activity.  Indeed, when the authors looked at their data and asked, “where in the brain do we see COMT gene associations with extended firing? they found such associations in the frontal cortex (frontal gyrus and cingulate cortex)!

Down below, in the subcortical networks, a differerent type of cognitive operation is taking place.  Here the cells/circuits are involved in the action selection (press a button) of whether the word is a match and in the working memory updating of each new word.  Instead of prolonged, sustained “tonic” neuronal firing, the cells rely on fast, transient “phasic” bursts of activity.  Here, the modulatory role of dopamine is expected to be different and the Bilder et al. theory predicts that COMT Val/Val individuals would be more efficient at modulating the fast, transient form of cell firing required here.   Similarly, when the research team explored their genotype and brain activity data and asked, “where in the brain do we see COMT gene associations with transient firing? they found such associations in the right hippocampus.

Thus, what can someone who carries the Met/Met genotype at rs4680 say to their fellow Val/Val lunch-mate next time they visit a Burger King?  “I have the gene for obesity? or impulsivity? or “this” or “that”?  Perhaps not.  The gene influences different parts of each person’s neural networks in different ways.  The Met/Met having the advantage in pondering (perhaps more prone to annoyingly gaze at the menu forever) whist the Val/Val has the advantage in the action selecting (perhaps ordering promptly but not getting the best burger and fries combo).

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DON’T tell the grant funding agencies, but, in at least one way, the effort to relate genetic variation to individual differences in cognitive function is a totally intractable waste of money.

Let’s say we ask a population of folks to perform a task – perhaps a word memory task – and then we use neuroimaging to identify the areas of the brain that (i) were associated with performance of the task, and (ii) were not only associated with performance, but were also associated with genetic variation in the population.  Indeed, there are already examples of just this type of “imaging-genetic” study in the literature.  Such studies form a crucial translational link in understanding how genes (whose biochemical functions are most often studied in animal models) relate to human brain function (usually studied with cognitive psychology). However, do these genes relate to just this task? What if subjects were recalling objects? or feelings?  What if subjects were recalling objects / experiences / feelings / etc. from their childhoods?  Of course, there are thousands of common cognitive operations one’s brain routinely performs, and, hence, thousands of experimental paradigms that could be used in such “imaging-genetic” gene association studies.  At more than $500/hour (some paradigms last up to 2 hours) in imaging costs, the translational genes-to-cognition endeavor could get expensive!

DO tell the grant funding agencies that this may not be a problem any longer.

The recent paper by Liu and colleagues “Prefrontal-Related Functional Connectivities within the Default Network Are Modulated by COMT val158met in Healthy Young Adults” [doi: 10.1523/jneurosci.3941-09.2010] suggests an approach that may simplify matters.  Their approach still involves genotyping (in this case for rs4680) and neuroimaging.  However, instead of performing a specific cognitive task, the team asks subjects to lay in the scanner – and do nothing.  That’s right – nothing – just lay still with eyes closed and just let the mind wander and not to think about anything in particular – for a mere 10 minutes.  Hunh?  What the heck can you learn from that?

It turns out that one can learn a lot.  This is because the neural pathways that the brain uses when you are actively doing something (a word recall task) are largely intact even when you are doing nothing.  Your brain does not “turn off” when you are laying still with your eyes closed and drifting in thought.  Rather, your brain slips into a kind of default pattern, described in studies of  “default networks” or “resting-state networks” where wide-ranging brain circuits remain dynamically coupled and actively exchange neural information.  One really great paper that describes these networks is a free-and-open article by Hagmann et al., “Mapping the Structural Core of Human Cerebral Cortex” [doi: 10.1371/journal.pbio.0060159] from which I’ve lifted their Figure 1 above.  The work by Hagmann et al., and others show that the brain has a sort of “connectome” where there are thousands of “connector hubs” or nodes that remain actively coupled (meaning that if one node fires, the other node will fire in a synchronized way) when the brain is at rest and when the brain is actively performing cognitive operations.  In a few studies, it seems that the strength of functional coupling in certain brain areas at rest is correlated (positively and negatively) with the activation of these areas when subjects are performing a specific task.

In the genetic study reported by Liu and colleagues, they found that genotype (N=57) at the dopaminergic COMT gene correlated with differences in the functional connectivity (synchronization of firing) of nodes in the prefrontal cortex.  This result is eerily similar to results found for a number of specific tasks (N-back, Wisconsin Card Sorting, Gambling, etc.) where COMT genotype was correlated with the differential activation of the frontal cortex during the task.  So it seems that one imaging paradigm (lay still and rest for 10 minutes) provided comparable insights to several lengthy (and diverse) activation tasks.  Perhaps this is the case. If so, might it provide a more direct route to linking genetic variation with cognitive function?

Liu and colleagues do not comment on this proposition directly nor do they seem to be over-interpreting their results in they way I have editorialized things here.  They very thoughtfully point out the ways in which the networks they’ve identified and similar and different to the published findings of others.  Certainly, this study and the other one like it are the first in what might be a promising new direction!

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In his book, The Beak of the Finch, Jonathan Weiner describes the great diversity of finches on the Galapagos Islands – so much diversity – that Darwin himself initially thought the finch variants to be completely different birds (wrens, mockingbirds, blackbirds and “gross-bills”).  It turns out that one of the pivotal events in Charles Darwin‘s life was his work in 1837 with the great ornithologist John Gould who advised that the birds were actually closely related finches and also specific to separate islands!

Fast-forward to 2009, and we are well on our way to understanding how closely related species can, via natural selection of genetic variation, diverge across space and time. The BMP4 and CaM genes, for example, have been associated with beak morphology in what are now known as Darwin’s Finches.  Wonderful indeed, but now consider, for a moment, the variability – not of finch beaks – but of human cognition.

If you’ve ever been a part of a team or group project at work or school, you know that very few people THINK just like you.  Indeed, variability in human cognition can be the source of a lot of frustration.  Let’s face it, people have different experiences stored away (in a highly distributed fashion) in their memory banks, and each persons brain is extensively wired with trillions of synapses.  Of course! nobody thinks like you.  How could such a complex organ function exactly the same way in 2 separate individuals.

Perhaps then, if you were an alien visitor (as Darwin was to the Galapagos Islands) and you watched 5 separate individuals devise a plan to – oh lets just say, to improve healthcare accessibility and affordability – and you measured individuals based solely on their “thinking patterns” you might conclude (as Darwin did) that you were dealing with 5 separate “species”.  Just flip the TV between FOX, CNN, CNBC, CSPAN and MSNBC if you’re not convinced!

However, if you were to take a more in-depth approach and crack open a current issue of a neuroimaging journal – you might come to the exact opposite conclusion.  That’s right.  If you looked at patterns of brain activity and other indirect measures of neural network dynamics (what I casually meant by “thinking patterns” ) you would mostly see conclusions drawn from studies where many individuals are pooled into large groups and then probed for forms of brain activity that are common rather than different.  Most studies today show that humans use a common set of neural systems to perform mental operations (e.g., recalling events and information).  Brain structures including the hippocampus, frontal cortex, thalamus, parietal cortex are all known to be involved in deciding whether or not you have seen something before.  Thus, if you perform an fMRI brain scanning study on individuals and ask them to complete an episodic memory recall task (show them a list of words before scanning and then – when they are in the scanner – ask them to respond to words they remember seeing), you will likely observe that all or most individuals show some BOLD response activity in these structures.

OK great! But can you imagine where we would be if Charles Darwin returned home from his voyage and said, “Oh, just a bunch of birds out there … you know, the usual common stuff … beaks, wings, etc.”  I’d rather not imagine.

Enter Professor Michael Miller and colleagues and their recent paper, “Unique and persistent individual patterns of brain activity across different memory retrieval tasks” [doi:10.1016/j.neuroimage.2009.06.033].  This paper looks – not just at the common stuff – but the individual differences in BOLD responses among individuals who perform a number of different memory tasks.  The team reports that there are dramatic differences in the patterns of brain activity between individuals.  This can be seen very clearly in Figure 1 which shows left hemisphere activity associated with memory recall.  The group data (N=14) show nice clean frontal parietal activations – but when the data is broken down on an individual-by-individual basis, you might – without knowing that the all subjects were performing the same recall tasks – suspect that each person was doing or “thinking” something quite different.  The research team then re-scanned each subject several months later and asked whether the individual differences were consistent from person to person. Indeed, the team shows that the 2nd brain scan is much more similar to the first (correlations were about 0.5) and that the scan-rescan data for an individual was more similar than the correlation between any single person and the rest of the group (about 0.25).  Hence, as the authors state, “unique patterns of brain activity persist across different tasks”.

Vive la difference!  Yes, the variability is – if you’re interested in using genetics to understand human history and cognitive development – the really exciting part!  Of course, genetics is not the main reason for the stable individual-to-individual differences in brain activity.  There are likely to be many factors that could alter the neural dynamics of broadly distributed neural networks used for memory recall.  Environment, experience, gender are just a few factors that are known to influence the function of these networks.  The authors reveal that individuals may also differ in the strategies and criteria they use to make decisions about whether they can recall or detect a previously viewed item.  Some people will respond only when they are very certain (high criteria) and others will respond even if they feel only slightly sure they’ve seen an item before (low criteria).  The authors show in Figure 5 that the folks who showed similar decision criteria are more likely to have similar patterns of brain activity.

Perhaps then, the genetic differences that (partially) underlie individual differences in brain activity might relate to personality or other aspects of decision making?  I don’t have a clue, but I do know that this approach – of looking carefully at individual differences – is a step forward to doing what Darwin (and don’t forget John Gould!) is so well known for.  Understand where the variation comes from, and you will understand where you come from!

I will follow this literature more closely in the months to come.

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*** PODCAST accompanies this post ***

Nowadays, it seems that genomics is spreading beyond the rarefied realm of science and academia into the general, consumer-based popular culture.  Quelle surprise!?  Yes, the era of the personal genome is close at hand, even as present technology  provides – directly to the general consumer public – a  genome-wide sampling of many hundreds of thousands of single nucleotide variants.   As curious early adopters begin to surf their personal genomic information, one might wonder how they, and  homo sapiens in general, will ultimately utilize their genome information.  Interestingly, some have already adapted the personal genome to facilitate what homo sapiens loves to do most – that is, to interact with one another.  They are at the vanguard of a new and hip form of social interaction known as “personal genome sharing”.  People connecting in cyberspace – via  haplotype or sequence alignment – initiating new social contacts with distant cousins (of which there may be many tens of thousands at 5th cousins and beyond).  Sharing genes that regulate the social interaction of sharing genes, as it were.

A broader view of social genes, within the context of our neo-Darwinian synthesis, however, shows that the relationship between the genome and social behavior can be rather complex.  When genes contribute directly to the fitness of an organism (eg. sharper tooth and claw), it is relatively straightforward to explain how novel fitness-conferring genetic variants increase in frequency from generation to generation.  Even when genetic variants are selfish, that is, when they subvert the recombination or gamete production machinery, in some cases to the detriment of their individual host, they can still readily spread through populations.  However, when a new genetic variant confers a fitness benefit to unrelated individuals by enhancing a cooperative or reciprocally-altruistic form of social interaction, it becomes more difficult to explain how such a novel genetic variant can take hold and spread in a large, randomly mating population.  Debates on the feasibility natural selection acting “above the level of the individual” seem settled against this proposition.  However, even in the face of such difficult population genetic conundrums, research on the psychology, biology and evolutionary genetics of social interactions continues unabated.  Like our primate and other mammalian cousins, with whom homo sapiens shares some 90-99% genetic identity, we are an intensely social species as our literature, poetry, music, cinema, not to mention the more recent twittering, myspacing, facebooking and genome-sharing demonstrate.

Indeed, many of the most compelling examples of genetic research on social interactions are those that reveal the devastating impacts on psychological development and function when social interaction is restricted.  In cases of maternal and/or peer-group social separation stress, the effects on gene expression in the brain are dramatic and lead to long-lasting consequences on human emotional function.  Studies on loneliness by John Cacioppo and colleagues reveal that even the perception of loneliness is aversive enough to raise arousal levels which, may, have adaptive value.  A number of specific genes have been shown to interact with a history of neglect or maltreatment in childhood and, subsequently, increase the risk of depression or emotional lability in adulthood.  Clearly then, despite the difficulties in explaining how new “social genes” arise and take hold in populations, the human genome been shaped over evolutionary time to function optimally within the context of a social group.

From this perspective, a new paper, “Oxytocin receptor genetic variation relates to empathy and stress reactivity in humans” by Sarina Rodrigues and colleagues [doi.org/10.1073/pnas.0909579106] may be of broad interest as a recent addition to a long-standing, but now very rapidly growing, flow of genetic research on genes and social interactions.  The research team explored just a single genetic variant in the gene encoding the receptor for a small neuropeptide known as oxytocin, a protein with well-studied effects on human social interactions.  Intra-nasal administration of oxytocin, for example, has been reported to enhance eye-gaze, trust, generosity and the ability to infer the emotional state of others.  In the Rodrigues et al., study, a silent G to A change (rs53576) within exon 3 of the oxytocin receptor (OXTR) gene is used to subgroup an ethnically diverse population of 192 healthy college students who participated in assessments for pro-social traits such as the “Reading the Mind in the Eyes” (RMET) test of empathetic accuracy as well as measures of dispositional empathy.  Although an appraisal of emotionality in others is not a cooperative behavior per se, it has been demonstrated to be essential for healthy social function.  The Rodrigues et al., team find that the subgroup of students who carried the GG genotype were more accurate and able to discern the emotional state of others than students who carried the A-allele.  Such molecular genetic results are an important branching point to further examine neural and cognitive mechanisms of empathy as well as long-standing population genetic concerns of how new genetic variants like the A-allele of rs53576 arose and managed to take-hold in human populations.

Regarding the latter, there are many avenues for inquiry, but oxytocin’s role in the regulation of the reproductive cycle and social behavior stands out as an ideal target for natural selection.  Reproductive and behavioral-genetic factors that influence the ritualized interactions between males and females have been demonstrated to be targets of natural selection during the process of speciation.  New variants can reduce the cross-mating of closely related species who might otherwise mate and produce sterile or inviable hybrid offspring.  So-called pre-mating speciation mechanisms are an efficient means, therefore, to ensure that reproduction leads to fit and fertile offspring.  In connection with this idea, reports of an eye-gaze assessment similar to the RMET test used by Rodrigues et al., revealed that women’s pupils dilate more widely to photos of men they were sexually attracted to during their period of the menstrual cycle of greatest fertility, thus demonstrating a viable link between social preference and reproductive biology.  However, in the Rodrigues et al., study, it was the G-allele that was associated with superior social appraisal and this allele is not the novel allele, but rather the ancestral allele that is carried by chimpanzees, macaques and orangutans.  Therefore, it does not seem that the novel A-allele would have been targeted by natural selection in this type of pre-mating social-interaction scenrio.  Might other aspects of OXTR function provide more insight then?  Rodrigues et al.,  explore the role of the gene beyond the social interaction dimension and note that OXTR is widely expressed in limbic circuitry and also plays a broader modulatory role in many emotional reactivity.  For this reason, they sought to assess the stress responsivity of the participants via changes in heart-rate that are elicited by the unpredictable onset of an acoustic startle.  The results show that the A-allele carriers showed greater stress reactivity and also greater scores on a 12-point scale of affective reactivity.  Might greater emotional vigilance in the face of adversity confer a fitness advantage for A-allele carriers? Perhaps this could be further explored.

Regarding the neural and cognitive mechanisms of empathy and other pro-social traits, the Rodrigues et al., strategy demonstrates that when human psychological research includes genetic information it can more readily be informed by a wealth of non-human animal models.  Comparisons of genotype-phenotype correlations at the behavioral, physiological, anatomical and cellular levels across different model systems is one general strategy for generating hypotheses about how a gene like OXTR mediates and moderates cognitive function and also why it (and human behavior) evolved.  For example, mice that lack the OXTR gene show higher levels of aggression and deficits in social recognition memory.  In humans, genetic associations of the A-allele with autism, and social loneliness form possible translational bridges.  In other areas of human psychology such as in the areas of attention and inhibition, several genetic variants correlate with specific  mental operations and areas of brain activation.  The psychological construct of inhibition, once debated purely from a behavioral psychological perspective, is now better understood to be carried out by a collection of neural networks that function in the lateral frontal cortex as well as basal ganglia and frontal midline.  Individual differences in the activation of these brain regions have been shown to relate to genetic differences in a number of dopaminergic genes, whose function in animal models is readily linked to the physiologic function of specific neural circuits and types of synapses.  In the area of social psychology, where such types of neuroimaging-genetic studies are just getting underway, the use of “hyper-scanning”, a method that involves the simultaneous neuroimaging of two or more individuals playing a social game (prisoners dilemma) reveals a co-activation of dopamine-rich brain areas when players are able to make sound predictions of other participant’s choices.  These types of social games can model specific aspects of reciprocal social interactions such as trust, punishment, policing, sanctions etc. that have been postulated to support the evolution of social behavior via reciprocal altruism.  Similar imaging work showed that intra-nasal administration of oxytocin potently reduced amygdala activation and decreased amygdala coupling to brainstem regions implicated in autonomic and behavioural manifestations of fear.  Such recent examples affirm the presence of a core neural circuitry involved in social interaction whose anatomical and physiological properties can be probed using genetic methods in human and non-human populations.

Although there will remain complexities in explaining how new “social genes” can arise and move through evolutionary space and time (let alone cyberspace!) the inter-flows of genetic data and social psychological function in homo sapiens will likely increase.  The rising tide should inevitably force both psychologists and evolutionary biologists to break out of long-standing academic silos and work together to construct coherent models that are consistent with cognitive-genetic findings as well as population- genetic and phylogenetic data.  Such efforts will heavily depend on a foundation of psychological research into “social genes” in a manner illustrated by Rodrigues et al.

*** PODCAST accompanies this post *** Thanks agian Dr. Rodrigues!!!

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Surgeon holding scalpel.
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Whether you are a carpenter, plumber, mechanic, electrician, surgeon or chef, your livelihood depends on a set of sturdy, reliable, well-honed, precision tools.  Similarly, neuroscientists depend on their electrodes, brain scanners, microscopes and more recently their genome sequencers.  This is because they are not just trying to dissect the brain – the physical organ – but also the psychological one.  As the billions of neurons connected by trillions of synapses process electrical impulses – a kind of neural information – it is the great endeavor of cognitive-molecular-neuro-psychology (or whatever you wish to call the art) to figure out how all of those neurons and connections come into being and how they process information in ways that lead to your personality, self-image, hopes, dreams, memories and the other wonderful aspects of your mental life.  How and why does information flow through the brain in the way it does? and how and why does it do so in different ways for different people? Some, for instance, have informally related Sigmund Freud‘s models of mental structure to a kind of plumbing wherein psychic energy was routed (or misrouted) through different structural aspects of the mind (pipes as it were).  Perhaps such a model was fitting for the great industrial era in which he lived – but perhaps not in today’s highly information-based, inter-connected and network-oriented era.  If our understanding of mental life is a product of our tools, then perhaps we should be sure that our modern tools are up to the job.

One recent paper reminded me of how important it is to double check the accuracy and precision of one’s tools was the research article, “Quantifying the heritability of task-related brain activation and performance during the N-back working memory task: A twin fMRI study” [doi:10.1016/j.biopsycho.2008.03.006] by Blokland et al..  In this report, the team summarizes the results of measurments of the brain activity – not structure – but rather activity as measured by their chosen tool, the MRI scanner.  This research team, based in UCLA and known as one of the best in the field, asks whether the so-called BOLD response (an indirect measure of neural activity) shows greater concordance in identical (monozygotic) vs. fraternal (dizygotic) twins.  To generate brain activity, the research team asked the subjects to perform a task called an N-back  workng memory task, which entails having to remember something that happend “N” times ago (click here for further explanation of N-back task or play it on your iphone).  If you’ve done this, you’ll know that its hard – maddeningly so – and it requires a lot of concentration, which, the researchers were counting on to generate activity in the prefrontal cortex.

After looking at the brain activity patterns of some 29 MZ pairs and 31 DZ pairs, the team asked if the patterns of brain activity in the lateral frontal cortex were more similar in the MZ pairs vs. the DZ pairs.  If so, then it would suggest that the scanning technology (measurement of the BOLD response) is sufficiently reliable and precise enough to detect the fraction of individual differences in brain activty that arise from additive genetic variation.  If one actually had such super-precise tool, then one could begin to dissect and tease apart aspects of human cognition that are regulated by individual genetic variation – a very super-precise and amazing tool – that might allow us to understand mental life in biologically-based terms (and not Freud’s plumbingesque analogies).  If only such a tool existed! Somewhat amazingly, the scanning tools did seem to be able to detect differences between the BOLD response correlations of MZ pairs vs. DZ pairs.  The BOLD response correlations were greater for MZ vs. DZ in the middle frontal gyrus, angular gyrus, supramarginal gyrus when activity for the 2-back task was compared to the 0-back task.  The team were cautious to extend these findings too far, since the standard deviations are large and the estimates of heritability for the BOLD response are rather low (11-36%), but, overall, the team suggests that the ability to use the fMRI methods in conjunction with genetic markers shows future promise.

Meanwhile, the literature of so-called “imaging-genetic” findings begins to grow in the literature.  I hope the tools are reliable and trustworthy enough to justify conclusions and lessons about human genetic variation and its role in mental life.  Will certainly keep this cautionary report in mind as I report on the cognitive genetics literature in the future.

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Pointer to: NeuroImage establishes a YouTube Channel with the aim of collaborating with the community with a free-to-view platform for posting and viewing videos related to all areas of neuroimaging.

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labyrinthine circuit board lines
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Amidst a steady flow of upbeat research news in the behavioral-genetics literature, there are many inconvenient, uncomfortable, party-pooping sentiments that are more often left unspoken.  I mean, its a big jump – from gene to behavior – and just too easy to spoil the mood by reminding your colleagues that, “well, everything is connected to everything” or “that gene association holds only for that particular task“.  Such may have been the case often times in the past decade when the so-called imaging-genetics literature emerged to parse out a role for genetic variation in the structure and functional activation of the brain using various neuroimaging methods.  Sure, the 5HTT-LPR was associated with amygdala activation during a face matching task, but what about other tasks (and imaging modalities) and other brain regions that express this gene.  How could anyone (let alone NIMH) make sense out of all of those – not to mention the hundreds of other candidate genes poised for imaging-genetic research?

With this in mind, it is a pleasure to meet the spoiler-of-spoilers! Here is a research article that examines a few candidate genetic polymorphisms and compares their findings across multiple imaging modalities.  In his article, “Neural Connectivity as an Intermediate Phenotype: Brain Networks Under Genetic Control” [doi: 10.1002/hbm.20639] Andreas Meyer-Lindenberg examines the DARPP32, 5HTT and MAOA genes and asks whether their associations with aspects of brain structure/function are in any way consistent across different neuroimaging modalities.  Amazingly, the answer seems to be, yes.

For example, he finds that the DARPP32 associations are consistently associated with the striatum and prefrontal-striatal connectivity – even as the data were collected using voxel-based morphometry, fMRI in separate tasks, and an analysis of functional connectivity.  Similarly, both the 5HTT and MAOA gene promoter repeats also showed consistent findings within a medial prefrontal and amygdala circuit across these various modalities.

This type of finding – if it holds up to the spoilers & party poopers – could radically simplify the understanding of how genes influence cognitive function and behavior.  As suggested by Meyer-Lindenberg, “features of connectivity often better account for behavioral effects of genetic variation than regional parameters of activation or structure.”  He suggests that dynamic causal modeling of resting state brain function may be a powerful approach to understand the role of a gene in a rather global, brain-wide sort of way.  I hope so and will be following this cross-cutting “connectivity” approach in much more detail!

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Horatio, Hamlet, and the Ghost (Artist: Henry ...
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Amidst the steady stream of basic imaging and genetic science that pours forth into the literature each day (or in response to Eric Kandel‘s latest update on the state of brain science and mental health), how could anyone remain glum?  In Hamlet, the King asks, “How is it that the clouds still hang on you?” to which Hamlet replies, “Not so, my lord, I am too much in the sun“.  So it seems the case with John M. Grohol, whose recent article, “Chasing the Genetic Ghosts of Mental Illness” which rightly maintains an evenly skeptical long-term perspective on the (as-yet-unrealized-over) promise of genetic and brain imaging research. Certainly, patients may be encouraged by new findings, but as Grohol points out, there is a notorious 1-step forward, 2-steps back dynamic to basic research that can undermine the time-line of promise delivery.  Indeed, from a patient’s perspective, basic research that characterizes empirical therapeutic effects may only deliver marginal benefits at best.  Thus, there may be some need to better communicate on the fruits of basic research now – abundant or sparse as they may be.  I will keep Grohol’s perspective in mind.

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One of the difficulties in understanding mental illness is that so many aspects of mental life can go awry – and its a challenge to understand what abnormalities are directly linked to causes and what abnormalities might be consequences or later ripples in a chain reaction of neural breakdown.  Ideally, one would prefer to treat the fundamental cause, rather than only offer palliative measures for symptoms that arise from tertiary neural inefficiencies. In their research article entitled, “Evidence That Altered Amygdala Activity in Schizophrenia Is Related to Clinical State and Not Genetic Risk“, [doi: 10.1176/appi.ajp.2008.08020261] (audio link) Rasetti and colleagues explore this issue.

Specifically, they focus on the function of the amygdala and its role in responding to, and processing, social and emotional information.  In schizophrenia, it has been found that this brain region can be somewhat unresponsive when viewing faces displaying fearful expressions – and so, the authors ask whether the response of the amygdala to fearful faces is, itself, an aspect of the disorder that can be linked to underlying genetic risk (a type of core, fundamental cause).

To do this, the research team assembled 3 groups of participants: 34 patients, 29 of their unaffected siblings and 20 demographically and ethnically matched control subjects.  The rationale was that if a trait – such as amygdala response – was similar for the patient/sibling comparison and dissimilar for the patient/control comparison, then one can conclude that the similarity is underlain by the similarity or shared genetic background of the patients and their siblings.  When the research team colected brain activity data in response to a facial expression matching task performed in an MRI scanner, they found that the patient/sibling comparison was not-similar, but rather the siblings were more similar to healthy controls instead of their siblings.  This suggests that the trait (amygdala response) is not likely to be directly related to core genetic risk factor(s) of schizophrenia, but rather related to apsects of the disorder that are consequences, or the state, of having the disorder.

A follow-up study using a different trait (prefrontal cortex activity during a working memory task) showed that this trait was similar for the patient/sibling contrast, but dissimilar for the patient/control contrast – suggesting that prefrontal cortex function IS somewhat linked to core genetic risk.  Congratulations to the authors on this very informative study!

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One of the mental functions many of us take for granted is memory – that is – until we’re at the grocery store.  If you’re like me, you dart out of the house confident that you don’t need a list since you’re just going to “pick up a few things” – only to return home and discover (hours later when you’re comfortably ensconced on the couch) that you forgot the ice cream.  Damn, why can’t I have a more efficient working memory system ?  What’s the matter with my lateral frontal cortex ?  Can I (should I) blame it on my genes ? What genes specifically ?

One group recently reported the use of the so-called BOLD-response (blood oxygen level dependent) as a means to sift through the human genome and identify genes that mediate the level of brain activity in the lateral frontal cortex that occur during a working memory task – somewhat akin to remembering a list of groceries.  Steven Potkin and associates in their paper, “Gene discovery through imaging-genetics: identification of two novel genes associated with schizophrenia” [doi: 10.1038/mp.2008.127] examine the level of brain activity in 28 patients with schizophrenia (a disorder where mental function in the lateral frontal cortex is disrupted) and correlate this brain activity (difference between short and long list) with genetic differences at 100,000 snps spread across the autosomes.

They identify 2 genes (that pass an additional series of statistical hurdles designed to weed-out false positive results) RSRC1 and ARHGAP18, heretofore, never having been connected to mental function.  Although neither protein is neuron or brain-specific in its expression, ARHGAP18 is a member of the Rho/Rac/Cdc42-like GTPase activating (RhoGAP) gene family which are well known regulators of the actin cytoskeleton (perhaps  a role in synaptic plasticity ?) and RSRC1 is reported to bind to actin homologs. Also, RSRC1 may play a role in forebrain development since it is expressed in cdc34+ stem cells that migrate under the control of TGF-alpha (As an aside, yours truly co-published a paper showing that TGF-alpha is regulated by early maternal care – possible connection ? Hmm).  A last possibility is a role in RNA splicing which many SR-proteins like RSRC1 function in – which also could be important for synaptic function as many mRNA’s are stored in synaptic terminals.

The authors’ method is completely novel and they seem to have discovered 2 new points from which to further explore the genetic basis of mental disability.  It will be of great interest to see where the research leads next.

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Day 184 - Halfway!
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I’ve heard of mind reading – yes, some folks have actually figured out (here, here, here) how to decode the fMRI signal to literally know what you’re thinking – but am now beginning to wonder where it all ends. In their new paper, “Transcription MRI: A New View of the Living Brain”, by Liu and colleagues [doi: 10.1177/1073858407309746], they describe the use of short oligonucleotides that can hybridize to mRNA transcripts and, due to the presence of a paramagnetic linker on the oligo, also be visualized in the MR scanner.  This is a new technique and the paper runs it alongside more traditional reporter-gene methods (requiring post-mortem tissue however) to validate the specificity and precision of the approach.  Presently, the method is not safe for humans, so only mice need worry about who is looking at their deepest gene expressions.

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female reading emotionsImage by -kÇ- via Flickr Session 4 of our discussion group, “When Basic Neuroscience Meets Psych Rehab” will meet on Sept 25. This session will cover the topic of ‘affect labeling’ which is one strategy for managing one’s emotions. Did you know there are 3,000+ words you can choose from to describe your feelings ? How many can you name right off the bat ? The discussion seeks to flesh out the way in which basic brain mechanisms of emotional regulation work and how brain-based (and genetic) biomarkers might be used in a clinical therapy/rehabilitation setting. Slides and discussion highlights will be posted to the website.

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An image illustrating the density of astrocyte...Image via Wikipedia James Schummers, Hongbo Yu and Mriganka Sur present their measurements of Ca++ dynamics in response to visual stimuli in the awake ferret and reveal highly refined patterns of astrocyte activity in their paper, “Tuned Responses of Astrocytes and Their Influence on Hemodynamic Signals in the Visual Cortex” (DOI: 10.1126/science.1156120). The genetic regulation of neurovascular coupling is key to understanding the way in which genetic variation may regulate brain function (or at least function as measured by the BOLD response). A closer look at BOLD response and genetic pathways that mediate astrocyte function would be music to my ears – or at least my auditory cortex astocytes.Related articles by Zemanta

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Animation of an MRI brain scan, starting at th...Image via Wikipedia OK, the title of this post is fanciful – even for the blogosphere – but the recent open access paper, “Using fMRI Brain Activation to Identify Cognitive States Associated with Perception of Tools and Dwellings” by Shinkareva and team (DOI) is pretty darn amazing. The authors ask subjects to view pictures of and think about a set of objects: drill, hammer, screwdriver, pliers, saw, apartment, castle, house, hut, and igloo (tools vs. dwellings) while laying in an MRI scanner. The patterns of brain activity associated with each category were then used to train a pattern recognition learning program in order to discriminate between these two categories. Subsequent testing of the pattern recognizer showed that it could accurately predict what category of object a subject was viewing based on the pattern of brain activity. Interestingly, there were striking commonalities across subjects in the locations and activation amplitudes of regions for each category suggesting that the brains of different people are using similar neural pathways to represent semantic information. It is easy to imagine that genetic factors regulating human brain development may contribute to this invariance. I’m not sure if I’ll be surprised when this question is answered – perhaps my brain/genome scan will tell me whether I was or not.

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Comparison of zygote development in monozygoti...Image via Wikipedia Twin studies are oft used to gauge the role of the genome in behavioral science. A recent report, “Nature versus Nurture in Ventral Visual Cortex: A Functional Magnetic Resonance Imaging Study of Twins” by Polk et al., (DOI) shows that brain activity during early stages of visual processing is more similar in twins vs. unrelated subjects across several object categories such as faces, houses, pseudowords and a control category consisting of -ok- chairs? When the brain activity of identical vs. fraternal twins was examined, the activity associated with faces showed the greatest difference in similarity of activity compared to other categories. Its always fun to speculate about why the genome might weigh-in more heavily when it comes to face processing – certainly an important skill for our primate order.

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Red = oxygenated  Blue = d...Image via Wikipedia Brain images with red and yellow splotches of activity are now ubiquitous in the psychology literature and well on their way, via neuromarketing, to bamboozling consumers everywhere (eg. this splotch shows that 2/3 people really do prefer Pepsi !). When inappropriately used, fMRI methods can devolve quickly into a high-tech form of phrenology with concomitant hucksters (not unlike recent reports of consumer fraud in genetic testing) and, despite its ubiquity and potentcy as a research tool, the molecular basis for the fMRI signal has remained somewhat mysterious. Generally, when neurons fire, local blood-flow increases and the paramagnetic form of deoxyhemoglobin can be distinguished from the nonmagnetic oxygenated form using the electromagnetic scannner. Hence, splotches that indicate more blood flow (or Brain Oxygen Level Dependent – BOLD reponse) can be a proxy for neural activity. The connection between neuronal firing and blood flow, however, is not necessarily simple nor easily ignored. Amazingly, a recent report from Takano and colleagues, “Astrocyte-mediated control of cerebral blood flow(DOI) shows that a single master regulatory gene, cyclooxygenase-1 (COX-1) is sufficient to regulate blood flow in response to neural activity. Takano and a team led by Maiken Nedergaard show that astrocytes have their hands wrapped around neural synsapses and their feet wrapped around capillaries. When the astrocytes sense synaptic firing (glutamate spillover) they signal to the capillaries and contractile pericyte cells to relax and vasodilate. Using a series of pharmacologic blockers, the team tested a number of candidate regulatory pathways and found that only COX-1 blockade affected vasodilation in response to neural activity. The work of this research team greatly improves the understanding of the fMRI method and provides a well constrained framework through which to understand fMRI data and, moreover, the interplay between brain imaging and genetic data. Hopefully the basic research will stay one step ahead of the hucksters.

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