An ancient Eastern text describes two temporally distinct aspects of pain perception; the direct experience of the sensation and habitual, negative, mentation which follows. It was suggested that the so-called ‘second dart’ of pain could be removed via meditative training, obliterating the suffering associated with noxious stimulation.

It’s a subtle distinction … to just experience something in the moment  vs. to ruminate on it and its causes, consequences, duration, etc.  How many times have you heard the sage advice, just let it go?  Is this what the brain imaging shows … that the meditators are not ruminating (they have decreased activity in parts of the brain involved in ruminating) … they have experienced the pain and then let it go?  Experience and forget?

Reminded me of an interesting little protein named DREAM.  Interesting because it modulates pain (when DREAM is inactivated in experimental mice the animals feel no pain) and interesting also because the gene plays a role in the formation of memories (mice show poor contextual fear memory when the gene is inactivated).

Experience and forget.  A Zen teaching encoded in our DNA?

Also my father, who in space-time occupied a stark room of a rest home an hour distant, which he furnished with a vigorous and Protean suite of senility’s phantoms, was in a genetic dimension unfolding within me, as time advanced, and occupying my body like, as Colette had written to illustrate another phenomenon, a hand being forced into a tight glove.

The yoga sutras are a lot of fun to read – especially the super-natural ones.  I try not to take them too literally, as you never know what might have been warped in translation, or perhaps included merely to inspire yogis to go the extra mile in their practices.

Occasionally, I come across articles in the science literature that reveal how truly weird and wild the human brain can be – and it strikes me – that maybe the ancient yogis were more in tune with the human mind than we “modern science” folks give them credit for.  Here’s a weird and wild sutra:

III.55 -  tarakam sarvavisayam sarvathavisayam akramam ca iti vivekajam jnanam – The essential characteristic of the yogi’s exalted knowledge is that he grasps instantly, clearly and wholly, the aims of all objects without going into the sequence of time of change.

How can we know things instantly?  and without respect to time (ie. never having had prior experience)?

Admittedly, Patanjali may be referring to things that take place in emotional, subconscious or cosmic realms that I’m not familiar with, so I won’t quibble with the text.  Besides, it sounds like an AWESOME state of mind to attain, and well worth the effort – even if we concede it is knowingly unobtainable.  But is it unobtainable?

Might there be states of mind that make it seem obtainable?  Here’s a fascinating science article that appeared in Science Magazine this past week.  Paradoxical False Memory for Objects After Brain Damage [doi: 10.1126/science.1194780] describing the effects of damage in the perirhinal cortex (in rats) that led the animals to demonstrate a peculiar form of false memory – wherein the animals treated never-before seen objects as being familiar. Hmmm.  An altered form of brain activity where unfamiliar and novel things seem very familiar.  Sounds sort of  like “instantaneous knowing without respect to time” to me.

Given the tremendous similarity in brain circuits and memory systems across all mammals, I wonder if humans (perhaps in deep meditative states or with various forms of hallucinogenic or damaged states) could experience this? Sutra III.55 seems strange, but not, perhaps unobtainable.

You already know this, but when you are stressed out (chronic stress), your brain doesn’t work very well.  That’s right – just when you need it most – your brain has a way of letting you down!

Here are a few things that happen to the very cells (in the hippocampus) that you rely on:

- reorganization within mossy fiber terminals
- loss of excitatory glutamatergic synapses
- reduction in the surface area of postsynaptic densities
- marked retraction of thorny excrescences
- alterations in the lengths of the terminal dendritic segments of pyramidal cells
- reduction of the dorsal anterior CA1 area volume

Thanks brain!  Thanks neurons for abandoning me when I need you most!  According to this article, these cellular changes lead to, “impaired hippocampal involvement in episodic, declarative, contextual and spatial memory – likely to debilitate an individual’s ability to process information in new situations and to make decisions about how to deal with new challenges.” UGH!

Are our cells making these changes for a reason?  Might it be better for cells to remodel temporarily rather than suffer permanent, life-long damage?  Perhaps.  Perhaps there are molecular pathways that can lead the reversal of these allostatic stress adaptations?

Check out this recent paper: “A negative regulator of MAP kinase causes depressive behavior” [doi 10.1038/nm.2219]  the authors have identified a gene – MKP-1 – a phosphatase that normally dephosphorylates various MAP kinases involved in cellular growth, that, when inactivated in mice, produces animals that are resistant to chronic unpredictable stress.  Although its known that MKP-1 is needed to limit immune responses associated with multi-organ failure during bacterial infections, the authors suggest:

“pharmacological blockade of MKP-1 would produce a resilient of anti-depressant response to stress”

Hmmm … so Mother Nature is using the same gene to regulate the immune response (turn it off so that it doesn’t damage the rest of the body) and to regulate synaptic growth (turn it off – which is something we DON’T want to do when we’re trying to recover from chronic stress)?  Mother Nature gives us MKP-1 so I can survive an infection, but the same gene prevents us from recovering (finding happiness) from stress?

Of course, we do not need to rely only on pharmacological solutions.  Exercise & social integration are cited by these authors as the top 2 non-medication strategies.

Most cells in your adult body are “terminally differentiated” – meaning that they have developed from stem cells into the final liver, or heart, or muscle or endothelial cell that they were meant to be.  From that point onward, cells are able to “remember” to stay in this final state – in part – via stable patterns of DNA methylation that reinforce the regulation of “the end state” of gene expression for that cell.  As evidence for this role of DNA methylation, it has been observed that levels of DNA methyl transferase (DNMT) decline when cells are fully differentiated and thus, cannot modify or disrupt their patterns of methylation.

NOT the case in the brain! Even though neurons in the adult brain are fully differentiated, levels of methyl transferases – DO NOT decline.  Why not? Afterall, we wouldn’t want our neurons to turn into liver cells, or big toe cells, would we?

One hypothesis, suggested by David Sweatt and colleagues is that neurons have more important things to “remember”.   They suggest in their fee and open research article, “Evidence That DNA (Cytosine-5) Methyltransferase Regulates Synaptic Plasticity in the Hippocampus” [doi: 10.1074/jbc.M511767200] that:

DNA methylation could have lasting effects on neuronal gene expression and overall functional state. We hypothesize that direct modification of DNA, in the form of DNA (cytosine-5) methylation, is another epigenetic mechanism for long term information storage in the nervous system.

By measuring methylated vs. unmethylated DNA in the promoter of the reelin and BDNF genes and relating this to electrophysiological measures of synaptic plasticity, the research team finds correlations between methylation status and synaptic plasticity.  More specifically, they find that zebularine (an inhibitor of DNMT) CAN block long-term potentiation (LTP), but NOT block baseline synaptic transmission nor the ability of synapses to fire in a theta-burst pattern (needed to induce LTP).

This suggests that the epigenetic machinery used for DNA methylation may have a role in the formation of cellular memory – but not in the same sense as in other cells in the body – where cells remember to remain in a terminally differentiated state.

In the brain, this epigenetic machinery may help cells remember stuff that’s more germane to brain function … you know … our memories and stuff.

Here’s the problem. In order to USE the BRAIN (to learn and remember stuff) we have to also USE the GENOME (to encode the proteins that synapses use in the process of memory formation).  When we’re thinking, we have to take our precious DNA out of its protective supercoiled, proteinaceous shell and allow the double helix to melt into single strands and expose their naked A’s, G’s, T’s and C’s to the chemical milieu (to the start the transcription process).  This is risky business damage to DNA can lead to cell death!

One might imaging that its best to carry out this precarious act quickly and in proximity to DNA repair enzymes (I’d think).  A very important job that includes: uncoiling chromatin superstructures, transcribing DNA (that encodes proteinaceous building blocks that synapses use to strengthen and weaken themselves) – and then – making sure there was no damage incurred along the way.  A BIG job that MUST get done each and every time my cells engage in learning.  Wow!  I didn’t realize that learning new stuff means I’m exposing my DNA to damage?  Hmm … I wonder if that PhD was worth it?

To perform this important job, it seems there is an amazing handyman of a molecule named poly(ADP-ribose) polymerase-1 (PARP-1).  Amazing, because it – itself – can function in many of the steps involved in uncoiling chromatin structures, transcription initiation and DNA repair.  The protein that can “do it all” … get the job done quickly and even fix any errors made along the way! It is known to function in the so-called base excision repair (BER) pathway and is also known have a role in transcription through remodeling of chromatin by ADP-ribosylating histones and relaxing chromatin structure, thus allowing transcription to occur (click here for a great open review of PARP-1).  Nice!

According to OMIM, earlier studies by Cohen-Armon et al. (2004) found that poly(ADP-ribose) polymerase-1 is activated in neurons that mediate several forms of long-term memory in Aplysia. Because poly(ADP-ribosyl)ation of nuclear proteins is a response to DNA damage in virtually all eukaryotic cells (indeed, PARP-1 knock-out mice are more sensitive to DNA damage), it was surprising that activation of the polymerase occurred during learning and was required for long-term memory. Cohen-Armon et al. (2004) suggested that the fast and transient decondensation of chromatin structure by poly(ADP-ribosyl)ation enables the transcription needed to form long-term memory without strand breaks in DNA.

A recent article in Journal of Neuroscience seems to confirm this function -  now in the mouse brain.  Histone H1 Poly[ADP]-Ribosylation Regulates the Chromatin Alterations Required for Learning Consolidation [doi:10.1523/JNEUROSCI.3010-10.2010] by Fontán-Lozano et al., examined cells in the hippocampus at different times during the learning of an object recognition paradigm.  They confirm (using a PARP-1 antagonist) that PARP-1 is needed to establish object memory and also that PARP-1 seems to contribute during the paradigm and up to 2 hours after the training session.  They suggest that the poly(ADP-ribosyl)ation of histone H1 influences whether H1 is bound or unbound and thus helps regulate the opening and closing of the chromatin so that transcription can take place. 

Nice to know that PARP-1 is on the job!  Still am wondering if the PhD was worth all the learning.  Are there trade-offs at play here?  MORE learning vs. LESS something?   Perhaps. Check out the paper by Grube and Bürkle (1992) - Poly(ADP-ribose) polymerase activity in mononuclear leukocytes of 13 mammalian species correlates with species-specific life span. This gene may influence life span!

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.

DON’T tell the grant funding agencies

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!

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.

pointer to: Computational Models of Basal Ganglia Function where Kenji Doya provides computational explanations for neuromodulators and their role in reinforcement learning. In his words, “Dopamine encodes the temporal difference error — the reward learning signal. Acetylcholine affects learning rate through memory updates of actions and rewards. Noradrenaline controls width or randomness of exploration. Serotonin is implicated in “temporal discounting,” evaluating if a given action is worth the expected reward.”

This type of amazing research provides a pathway to better understand how genes contribute to how the brain “works” as a 3-dimensional biochemical computational machine.