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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