Here’s a small insight into how this unfortunate developmental pathway might unfold … from a small-scale genetic study on variation in an intra-cytoplasmic loop of the Dopamine DRD4 receptor and its relationship to infidelity:

[DRD4] 7R+ individuals exhibit augmented anticipatory desire response to stimuli signaling dopaminergic incentives, such as food, alcohol, tobacco, gambling, and opiates. Although it is as yet speculative, these associations suggest that 7R+ individuals may allocate greater attention to appetitive rewards, contributing to the behavioral differences in promiscuity and infidelity observed here.

Neither the first, nor the last gene-twitter interaction to have gone badly for someone …

More on the DRD4 and social bonding genes

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Hands shake and wobble as the decades pass … moreso in some.

A recently evolved “T” allele (rs12720208) in the  3′ untranslated region (3′ UTR) of the FGF20 gene has been implicated in the risk of Parkinson’s Disease … namely by creating a wobbly G:U base-pair between microRNA-433 (miR-433) and the FGF20 transcript.  Since the normal function of microRNA-433 is to repress translation of proteins (such as FGF20), it is suspected that the PD risk “T” allele carriers make relatively more FGF20 … which, in turn … leads to the production of higher levels of alpha-synuclein (the main component of Lewy body fibrils, a pathological marker of diseases such as PD).  This newly evolved T-allele has also been associated with brain structural differences in healthy individuals.

My hands will shake and wobble as the decades pass … but not because I carry the G:U wobble pairing between miR-433:FGF20.  My 23andMe profile shows that I carry 2 C alleles and will produce the thermodynamically favorable G:C pairing.  Something to keep in mind as I lose my mind in the decades to come.

This paper explored this question using a shoulder exercise soreness assay and the COMT genotype and found that:

Participants that endorsed cognitions consistent with pain catastrophizing and had a genetic predisposition to low COMT enzyme activity had significantly higher pain intensity and pressure pain ratings when compared with groups with 1 or no risk factors.

“Pain catastrophizing” is a measure of how much a person ruminates (unable to suppress or divert attention away from pain-related thoughts) and/or focuses on and exaggerates the threat value of a painful stimuli and/or feels helpless and unable to cope with the adversity of painful stimuli.  It may be the most important aspect of coping with pain … an understanding that your perspective modulates your pain.

This may be worth noting given the  “dramatic increase in accidental deaths associated with the use of prescription opioids and also an increasing average daily morphine equivalent dose” despite the finding that “there is no clear evidence that long-term opiate therapy for chronic back pain is efficacious”.

Everyone has a birthday right. Its the day you (your infant self) popped into the world and started breathing, right?  But what about the day “you” were born – that is – “you” in the more philosophical, Jungian, spiritual, social, etc. kind of a way when you became aware of being in some ways apart from others and the world around you.  In her 1997 paper, “The Basal Ganglia and Cognitive Pattern Generators“, Professor Ann Graybiel writes,

The link between intent and action may also have a quite specific function during development. This set of circuits may provide part of the neural mechanism for building up cognitive patterns involving recognition of the self. It is well documented that, as voluntary motor behaviors develop and as feedback about the consequences of these behaviors occurs, the perceptuomotor world of the infant develops (Gibson 1969). These same correlations among intent, action, and consequence also offer a simple way for the young organism to acquire the distinction between actively initiated and passively received events. As a result, the infant can acquire the recognition of self as actor. The iterative nature of many basal ganglia connections and the apparent involvement of the basal ganglia in some forms of learning could provide a mechanism for this development of self-awareness.

As Professor Graybiel relates the “self” to function in the basal-ganglia and the so-called cortico-thalamic basal-ganglia loops – a set of parallel circuits that help to properly filter internal mental activity into specific actions and executable decisions – I got a kick out of a paper that describes how the development of the basal-ganglia can go awry for cells that are born at certain times.

Check out the paper, “Modular patterning of structure and function of the striatum by retinoid receptor signaling” by Liao et al.   It reveals that mice who lack a certain retinoic acid receptor gene (RARbeta) have a type of defective neurogenesis in late-born cells that make up a part of the basal ganglia (striatum) known as a striosome.  Normally, the authors say, retinoic acid helps to expand a population of late-born striosomal cells, but in the RARbeta mutant mice, the rostral striosomes remain under-developed.   When given dopaminergic stimulation, these mutant mice showed slightly less grooming and more sterotypic behaviors.

So when was “my self’s” birthday?  Was it when these late-born striosomal cells were, umm, born?  Who knows, but I’m glad my retinoic acid system was intact.

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!

This year, my 5 year-old son and I have passed many afternoons sitting on the living room rug learning to read.  While he ever so gradually learns to decode words, eg. “C-A-T”  sound by sound, letter by letter – I can’t help but marvel at the human brain and wonder what is going on inside.  In case you have forgotten, learning to read is hard – damn hard.  The act of linking sounds with letters and grouping letters into words and then words into meanings requires a lot of effort from the child  (and the parent to keep discomfort-averse child in one place). Recently, I asked him if he could spell words in pairs such as “MOB & MOD”, “CAD & CAB”, “REB & RED” etc., and, as he slowly sounded out each sound/letter, he informed me that “they are the same daddy“.  Hence, I realized that he was having trouble – not with the sound to letter correspondence, or the grouping of the letters, or the meaning, or handwriting – but rather – just hearing and discriminating the -B vs. -D sounds at the end of the word pairs.  Wow, OK, this was a much more basic aspect of literacy – just being able to hear the sounds clearly.  So this is the case, apparently, for many bright and enthusiastic children, who experience difficulty in learning to read.  Without the basic perceptual tools to hear “ba” as different from “da” or “pa” or “ta” – the typical schoolday is for naught.

With this in mind, the recent article, “Genetic determinants of target and novelty-related event-related potentials in the auditory oddball response” [doi:10.1016/j.neuroimage.2009.02.045] caught my eye.  The research team of Jingyu Liu and colleagues asked healthy volunteers just to listen to a soundtrack of meaningless beeps, tones, whistles etc.  The participants typically would hear a long stretch of the same sound eg. “beep, beep, beep, beep” with a rare oddball “boop” interspersed at irregular intervals.  The subjects were instructed to simply press a button each time they heard an oddball stimulus.  Easy, right?  Click here to listen to an example of an “auditory oddball paradigm” (though not one from the Liu et al., paper).  Did you hear the oddball?  What was your brain doing? and what genes might contribute to the development of this perceptual ability?

The researchers sought to answer this question by screening 41 volunteers at 384 single nucleotide polymorphisms (SNPs) in 222 genes selected for their metabolic function in the brain.  The team used electroencephalogram recordings of brain activity to measure differences in activity for “boop” vs. “beep” type stimuli – specifically, at certain times before and after stimulus onset – described by the so-called N1, N2b, P3a, P3b component peaks in the event-related potentials waveforms.  Genotype data (coded as 1,0,-1 for aa, aA, AA) and EEG data were plugged into the team’s home-grown parallel independent components analysis (ICA) pipeline (generously provided freely here) and several positives were then evaluated for their relationships in biochemical signal transduction pathways (using the Ingenuity Pathway Analysis toolkit.  A very novel and sophisticated analytical method for certain!

The results showed that certain waveforms, localized to certain areas of the scalp were significantly associated with the perception of various oddball “boop”-like stimuli.  For example, the early and late P3 ERP components, located over the frontal midline and parieto-occipital areas, respectively, were associated with the perception of oddball stimuli.  Genetic analysis showed that several catecholaminergic SNPs such as rs1800545 and rs521674 (ADRA2A), rs6578993 and rs3842726 (TH) were associated with both the early and late P3 ERP component as well as other aspects of oddball detection.

Both of these genes are important in the synaptic function of noradrenergic and dopaminergic synapses. Tyrosine hydroxylase, in particular, is a rate-limiting enzyme in catecholamine synthesis.  Thus, the team has identified some very specific molecular processes that contribute to individual differences in perceptual ability.  In addition to the several other genes they identified, the team has provided a fantastic new method to begin to crack open the synaptic complexities of attention and learning.  See, I told you learning to read was hard!

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.

From his lab’s website: “Our research combines computational modeling and experimental work to understand the neural mechanisms underlying reinforcement learning, decision making and working memory. We develop biologically-based neural models that simulate systems-level interactions between multiple brain areas (primarily basal ganglia and frontal cortex and their modulation by dopamine). We test theoretical predictions of the models using various neuropsychological, pharmacological, genetic, and neuroimaging techniques.”

In this interview, Dr. Frank provides some overviews on how genetics fits into this research program and the genetic results in his recent research article “Prefrontal and striatal dopaminergic genes predict individual differences in exploration and exploitation”. Lastly, some lighthearted, informal thoughts on the wider implications and future uses of genetic information in decision making.

To my mind, there is no one else in the literature who so seamlessly and elegantly interrelates genetics with the modern tools of cognitive science and computational neurobiology.  His work really allows one to cast genetic variation in terms of its influence on neural computation – which is the ultimate way of understanding how the brain works.  It was a treat to host this interview!

Click here for the podcast and here, here, here for previous blog posts on Dr. Frank’s work.

Here’s a new addition to a rapidly growing list of findings for the valine-to-methionine substitution in the COMT gene (rs4680).  The paper, “Effects of the Val158Met catechol-O-methyltransferase polymorphism on cortical structure in children and adolescents” by Shaw and colleagues at the NIMH [doi:10.1038/mp.2008.121] finds that when genotype was used as a regressor for cortical thickness measures in children (8-14 years of age) significant associations were found in the right inferior frontal gyrus and the right superior/middle temporal gyrus (in both areas, the met/met group had thicker cortex).  The team notes that the findings in the frontal cortex were expected – as many others have found associations of COMT with this brain area using other imaging modalities.  However, the temporal lobe finds are something new.  No speculations on the mechanisms/implications are provided by the researchers on this new finding, but known interconnectivities of these two brain regions exist – perhaps supporting aspects of language, memory and/or other cognitive processes?

Perhaps the findings provide a clue to an important role that genes may play in the development of cognitive function.

In 1802, in a letter to then Secretary of the Treasury, Albert Gallatin, Thomas Jefferson warned that, “If the American people ever allow private banks to control the issue of their money, first by inflation and then by deflation, the banks and corporations that will grow up around them (around the banks), will deprive the people of their property until their children will wake up homeless on the continent their fathers conquered.” (source)  Although the US now does have a central government bank, Jefferson’s warning still chillingly echoes through our current crisis as we teeter on this very brink.

The reasons why the US financial system lies stricken now (not to mention many times before) are complex for sure, but for a neuroscience & genetics buff like myself, its fun to consider the underlying mechanisms of human biology and behavior within a macroeconomic framework.  What role for the brain and human nature? How does our understanding of human social and emotional behavior reconcile with the premise of so-called “rational” behavior of investors and consumers in a marketplace? Can we regulate and design a debacle-proof economic system that accounts for human social and emotional influences on otherwise rational behavior? Luckily, if you are interested in these questions, you need only to pick up a copy of “Animal Spirits: How Human Psychology Drives the Economy, and Why It Matters for Global Capitalism” by George Akerlof and Robert Shiller, who cover this very topic in great detail and provide a broad framework for neuropsychological research to inform macroeconomic policy.  A lofty and distant goal indeed, but perhaps the only way forward from such spectacular wreckage of the current system.

One such aspect of so-called “animal  spirits” could be, for example – fear – which has been blamed many times for financial panics and is covered in great measure by Akerlof and Shiller.  During the depths of the great depression, FDR famously tried to shake people loose from their animal spirits by suggesting “Only Thing We Have to Fear Is Fear Itself” (listen to the audio).   As another example, consider the chart at the top of the post – a 5yr trace of the VIX an index of volatility in the price of stock options over time.  In a bull or a bear market, when there are clear economic signals that stock prices should rise or fall, the VIX is rather low – since people feel relatively certain about the overall direction of the market.  Note however, what happened in the fall of 2008, when the heady days of the housing boom ended and our current crisis began – the VIX rockets toward 100% volatility – indicating rather dramatic swings in future earnings estimates and hence, tremendous uncertainty about the future direction of the market.  Indeed, for high flying investors (who may reside in tall buildings with windows that open) the VIX is sometimes referred to as the fear index.

What – in terms of brain mechanisms – might underlie such fear – which seems to stem from the uncertainty of whether things will get better or worse?  What do we know about how humans react to uncertainty and how humans process uncertainty?  What brain systems and mechanisms are at play here? One recent report that uses genetic variation as a tool to peer into such brain mechanisms suggests that dopamine signaling modulates different brain areas and our propensity to respond in conditions of low and high uncertainty.

In their article, “Prefrontal and striatal dopaminergic genes predict individual differences in exploration and exploitation“, [doi:10.1038/nn.2342] Michael Frank and colleagues examine individual differences in a so-called exploration/exploitation dilemma.  In their ‘‘temporal utility integration task’’, individuals could maximize their rewards by pressing “stop” on a rotating dial which can offer greater rewards when individuals press faster, or when individuals learn to withold and wait longer, and, in a third condition when rewards are uncertain.  The authors liken the paradigm to a common life dilemma when there are clear rewards to exploiting something you know well (like the restaurant around the corner), but, however, there may be more rewards obtained by exploring the unknown (restaurants on the other side of town).  In the case of the VIX and its massive rise on the eve of our nations financial calamity, investors were forced to switch from an exploitation strategy (buy housing-related securities!!!) to an exploration strategy (oh shit, what to do?!!).

The neurobiological model hypothesized by Frank and colleagues predicts that the striatum will be important for exploitation strategies and find supporting data in gene associations with the striatally-enriched DARPP-32 gene (a marker for dopamine D1-dependent signalling) and DRD2 for the propensity to respond faster and slower, respectively, in the exploitative conditions (rs907094 & rs1800496).  For the exploratory conditions, the team found an association with the COMT gene which is well-known to modulate neural function in the prefrontal cortex (rs4680). Thus, in my (admittedly loose) analogy, I can imagine investors relying on their striata during the housing boom years and then having to rely more on their prefrontal cortices suddenly in the fall of 2008 when it was no longer clear how to maximize investment rewards.  Egregious bailouts were not yet an option!

Click here and here to read more breakthrough neuroeconomics & genetic research from Michael Frank and colleagues.  Here and here for more on Shiller and Keynes.