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Posts Tagged ‘Brain’

3rd Dalai Lama,
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Just a few excerpts from a lecture by the renown social psychologist Paul Ekman who is known for his work on the biology of human emotion.  Here he relates conceptual bridges between the writings of Charles Darwin and HH The Dalai Lama.  Ekman notes that both Darwin and HH The Dalai Lama intuit the existence of an organic natural source of compassion wherein humans are compelled to relieve the suffering of others so that the discomfort we feel when seeing others in pain can be relieved.  HH The Dalai Lama further suggests that these emotions are spontaneous, but compassion can be enhanced through PRACTICE!

Seems that science and ancient traditions can have a fascinating way of re-informing each other.

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The Karma Machine + Easy Photoshop Tattoo Tuto...
Image by vramak via Flickr

One of the themes that emerges in I.I atha yoganusasanam, and runs throughout the yoga sutras, is the notion that a yoga practice will bring one into a deeper awareness of the self.  To begin to explore the modern science notion of self-awareness, here’s a 2009 paper entitled, “The ‘prediction imperative’ as the basis for self-awareness” by Rodolfo R. Llinas and Sisir Roy [doi:10.1098/rstb.2008.0309].  The paper is part of a special theme issue from the Philosophical Transactions of the Royal Society B with the wonderfully karmic title: Predictions in the brain: using our past to prepare for the future.

Without unpacking the whole (open access) article, here are a few ideas that seem to connect loosely to themes in yoga.

The main issue addressed by the authors is how the brain manages to solve the computational problem of movement.  Here’s the problem: to just, for example,  reach into a refrigerator and grab a carton of milk (a far cry from, say, scorpion pose) they point out that,

“there are 50 or so key muscles in the hand, arm and shoulder that one uses to reach for the milk carton (leading to) over 1,000,000,000,000,000 combinations of muscle contractions (that) are possible.”

Yikes!  that is an overwhelming computational problem for the brain to solve – especially when there are 1,000-times FEWER neurons in the entire brain (only a mere 1,000,000,000,000 neurons).  To accomplish this computational feat, the authors suggest that brain has evolved 2 main strategies.

Firstly, the authors point out that the brain can lower the computational workload of controlling movement (motor output) by sending motor control signals in a non-continuous and pulsatile fashion.

“We see that the underlying nature of movement is not smooth and continuous as our voluntary movements overtly appear; rather, the execution of movement is a discontinuous series of muscle twitches, the periodicity of which is highly regular.”

This computational strategy has the added benefit of making it easier to bind and synchronize motor-movement signals with a constant flow of sensory input:

“a periodic control system may allow for input and output to be bound in time; in other words, this type of control system might enhance the ability of sensory inputs and descending motor command/controls to be integrated within the functioning motor apparatus as a whole.”

The idea of synchronizing sensory information with pulsing motor control signals brings to mind more poetic notions of rhythmicity and the way that yogis use their breath to enhance and unify  their outer and inner world experience.  Neat!  Also, I very much like the idea that our brains have enormously complex computational tasks to perform, so I’m keen to do what I can to help out my central nervous system.  Much gratitude to you brain!

Secondly, the authors then move ahead to describe the way in which neural circuits in the body and brain are inherently good at learning and storing information which makes them very good at predicting what to do with incoming sensory inputs.  This may just be another strategy the brain has evolved to simplify the enormous computational load associated with moving and coordinating the body.  Interestingly, the authors note,

“while prediction is localized in the CNS, it is a distributed function and does not have a single location within the brain. What is the repository of predictive function? The answer lies in what we call the self, i.e. the self is the centralization of the predictive imperative.  The self is not born out of the realm of consciousness—only the noticing of it is (i.e. self-awareness).”  Here’s a link to Llinas’ book on this topic.

The “self” is not just in the brain? but distributed throughout the entire CNS? Whoa!  Much to explore here.  Many thematic tie-ins with ancient Vedic notions of self and consciousness … will explore this in the future!

One last passage I found of interest was written by Moshe Bar, the editor of the special issue, who suggested that neural solutions to these inherent computational challenges make the brain/mind a naturally restless place.  His words,

“As is evident from the collection of articles presented in this issue, the brain might be similarly flexible and ‘restless’ by default. This restlessness does not reflect random activity that is there merely for the sake of remaining active, but, instead, it reflects the ongoing generation of predictions, which relies on memory and enhances our interaction with and adjustment to the demanding environment.”

My yoga teachers often remind me that “monkey mind” is normal and with more practice, it will subside.  Very cool to see a tie-in with modern research.

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Pantanjali Statue In Patanjali Yog Peeth,Haridwar
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According to B.K.S. Iyengar, in his book, “Light on the Yoga Sutras of Patanjali“, the first chapter of Patanjali‘s yoga sutrassamadhi pada – deals with movements of consciousness, or citta vrtti.

Specifically, the very first chapter, first sutra: I.I atha yoganusasanam, “With prayers for divine blessings, now begins an exposition of the sacred art of yoga”.   Iyengar expands on this to suggest that Patanjali is inviting the reader to begin an exploration of that hidden part of man that is beyond the senses.

Beautifully said.  Indeed, as a new student, I’ve noticed my own awareness of my body, my emotions and my thought processes has increased.  I’m not sure if this is what Patanjali had in mind, but I’m finding that aspects of my physical and mental life that were hidden are now more apparent to me.  It feels good.

How does this work, and what might types of brain mechanisms are involved in gaining self awareness?  What is the self anyway?  What is self-awareness?  How far into one’s unconscious mental processes can one’s self-awareness reach?  Why does it feel good to have more self-awareness?  Lot’s to ponder in follow-ups to come.

Even though the sutras were written more than 2,000 years ago, a neural- and brain-based understanding of consciousness remains a topic of debate and intense research.  I’ll do my best to explore some of this research and ways in which it might reflect back to the poetic and admittedly broad notions of consciousness in the yoga sutras.

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Where's Waldo in Google Maps?
Image by Si1very via Flickr

In an earlier post on Williams Syndrome, we delved into the notion that sometimes a genetic variant can lead to enhanced function – such as certain social behaviors in the case of WS.  A mechanism that is thought to underlie this phenomenon has to do with the way in which information processing in the brain is widely distributed and that sometimes a gene variant can impact one processing pathway, while leaving another pathway intact, or even upregulated.  In the case of Williams Syndrome a relatively intact ventral stream (“what”) processing but disrupted dorsal stream (“where”) processing leads to weaker projections to the frontal cortex and amygdala which may facilitate gregarious and prosocial (a lack of fear and inhibition) behavior.  Other developmental disabilities may differentially disrupt these 2 visual information processing pathways.  For instance, developmental dyspraxia contrasts with WS as it differentially disrupts the ventral stream processing pathway.

A recent paper by Woodcock and colleagues in their article, “Dorsal and ventral stream mediated visual processing in genetic subtypes of Prader–Willi syndrome” [doi:10.1016/j.neuropsychologia.2008.09.019] ask how another developmental disability – Prader-Willi syndrome – might differentially influence the development of these information processing pathways.  PWS arises from the lack of expression (via deletion or uniparental disomy) of a cluster of paternally expressed genes in the 15q11-13 region (normally the gene on the maternally inherited chromosome is silent, or imprintedrelated post here).  By comparing PWS children to matched controls, the team reports evidence showing that PWS children who carry the deletion are slightly more impaired in a task that depends on the dorsal “where” pathway whilst some sparing or relative strength in the ventral “what” pathway.

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A sculpture of a Hindu yogi in the Birla Mandi...
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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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Crocus (cropped)
Image by noahg. via Flickr

If you’ve started to notice the arrival of spring blossoms, you may have wondered, “how do the blossoms know when its spring?”  Well, it turns out that its not the temperature, but rather, that plants sense the length of the day-light cycle in order to synchronize their  own life cycles with the seasons.  According to the photoperiodism entry for wikipedia, “Many flowering plants use a photoreceptor protein, such as phytochrome or cryptochrome, to sense seasonal changes in night length, or photoperiod, which they take as signals to flower.”

It turns out that humans are much the same. Say wha?!

Yep, as the long ago descendants of single cells who had to eek out a living during day (when the sun emits mutagenic UV radiation) and night cycles, our very own basic molecular machinery that regulates the transcription, translation, replication and a host of other cellular functions is remarkably sensitive – entrained – in a clock-like fashion to the rising and setting sun.  This is because, in our retinas, there are light-sensing cells that send signals to the suprachiasmatic nucleus (SCN) which then – via the pineal gland – secretes systemic hormones such as melatonin that help synchronize cells and organs in your brain and body.  When this process is disrupted, folks can feel downright lousy, as seen in seasonal affective disorder (SAD), delayed sleep phase syndrome (DSPS) and other circadian rhythm disorders.

If you’re skeptical, consider the effects of genetic variation in genes that regulate our circadian rhythms, often called “clock” genes – very ancient genes that keep our cellular clocks synchronized with each other and the outside environment.  Soria et al., have a great paper entitled, “Differential Association of Circadian Genes with Mood Disorders: CRY1 and NPAS2 are Associated with Unipolar Major Depression and CLOCK and VIP with Bipolar Disorder” [doi: 10.1038/npp.2009.230] wherein they reveal that normal variation in these clock genes is associated with mood regulation.

A few of the highlights reported are rs2287161 in the CRY1 gene,  rs11123857 in the NPAS2 gene, and rs885861 in the VIPR2 gene – where the C-allele, G-allele and C-allele, respectively, were associated with mood disorders.

I’m not sure how one would best interpret genetic variation of such circadian rhythm genes.  Perhaps they index how much a person’s mood could be influenced by changes or disruptions to the normal rhythm??  Not sure.  My 23andMe data shows the non-risk AA genotype for rs11123857 (the others are not covered by 23andMe).

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An historic find has occurred in the quest (gold-rush, if you will) to link genome variation with brain structure-function variation.  This is the publication of the very first genome-wide (GWAS) analysis of individual voxels (voxels are akin to pixels in a photograph, but are rather 3D cubes of brain-image-space about 1mm on each side) of brain structure – Voxelwise genome-wide association study (vGWAS) [doi: 10.1016/j.neuroimage.2010.02.032] by Jason Stein and colleagues under the leadership of Paul M. Thompson, a  leader in the area of neuroimaging and genetics – well-known for his work on brain structure in twin and psychiatric patient populations.

In an effort to discover genes that contribute to individual differences in brain structure, the authors took on the task of statistically analyzing the some 31,622 voxels (per brain) obtained from high-resolution structural brain scans; with 448,293 Illumina SNP genotypes (per person) with minor allele frequencies greater than 0.1 (common variants); in 740 unrelated healthy caucasian adults.  When performed on a voxel-by-voxel basis, this amounts to some 14 billion statistical tests.

Yikes!  A statistical nightmare with plenty of room for false positive results, not to mention the recent disillusionment with the common-variant GWAS approach?  Certainly.  The authors describe these pitfalls and other scenarios wherein false data is likely to arise and most of the paper addresses the pros and cons of different statistical analysis strategies – some which are prohibitive in their computational demands.  Undaunted, the authors describe several approaches for establishing appropriate thresholds and then utilize a ‘winner take all’ analysis strategy wherein a single ‘most-associated winning snp’ is identified for each voxel, which when clustered together in hot spots (at P = 2 x 10e-10), can point to specific brain areas of interest.

Using this analytical approach, the authors report that 8,212 snps were identified as ‘winning, most-associated’ snps across the 31,622 voxels.  They note that there was not as much symmetry with respect to winning snps in the left hemispere and corresponding areas in the right hemisphere, as one might have expected.  The 2 most significant snps across the entire brain and genome were rs2132683 and rs713155 which were associated with white matter near the left posterior lateral ventricle.  Other notable findings were rs2429582 in the synaptic (and possible autism risk factor) CADPS2 gene which was associated with temporal lobe structure and rs9990343 which sits in an intergenic region but is associated with frontal lobe structure.  These and several other notable snps are reported and brain maps are provided that show where in the brain each snp is associated.

As in most genome-wide studies, one can imagine that the authors were initially bewildered by their unexpected findings.  None of the ‘usual suspects’ such as neurotransmitter receptors, transcription factors, etc. etc. that dominate the psychiatric genetics literature.  Bewildered, perhaps, but maybe thats part of the fun and excitement of discovery!  Very exciting stuff to come I’ll bet as this new era unfolds!

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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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wotd044
Image by theloushe via Flickr

** PODCAST accompanies this post**

I have a little boy who loves to run and jump and scream and shout – a lot.  And by this, I mean running – at full speed and smashing his head into my gut,  jumping – off the couch onto my head,  screaming – spontaneous curses and R-rated body parts and bodily functions.  I hope you get the idea.  Is this normal? or (as I oft imagine) will I soon be sitting across the desk from a school psychologist pitching me the merits of an ADHD diagnosis and medication?

Of course, when it comes to behavior, there is not a distinct line one can cross from normal to abnormal.  Human behavior is complex, multi-dimensional and greatly interpreted through the lens of culture.  Our present culture is highly saturated by mass-marketing, making it easy to distort a person’s sense of “what’s normal” and create demand for consumer products that folks don’t really need (eg. psychiatric diagnoses? medications?).   Anyhow, its tough to know what’s normal.  This is an important issue to consider for those (mass-marketing hucksters?) who might be inclined to promote genetic data as “hard evidence” for illness, disorder or abnormality of some sort.

With this in mind, I really enjoyed a recent paper by Stollstorff et al., “Neural response to working memory load varies by dopamine transporter genotype in children” [doi:10.1016/j.neuroimage.2009.12.104] who asked how the brains of healthy children functioned, even though they carry a genotype that has been widely associated with the risk of ADHD.  Healthy children who carry genetic risk for ADHD. Hmm, might this be my boy?

The researchers looked at a 9- vs. 10-repeat VNTR polymorphism in the 3′-UTR of the dopamine transporter gene (DAT1).  This gene – which encodes the very protein that is targeted by so many ADHD medications – influences the re-uptake of dopamine from the synaptic cleft.  In the case of 10/10 genotypes, it seems that DAT1 is more highly expressed, thus leading to more re-uptake and hence less dopamine in the synaptic cleft.  Generally, dopamine is needed to enhance the signal/noise of neurotransmission, so – at the end of the day – the 10/10 genotype is considered less optimal than the 9/9-repeat genotype.  As noted by the researchers, the ADHD literature shows that the 10-repeat allele, not the 9-repeat, is most often associated with ADHD.

The research team asked these healthy children (typically developing children between 7 and 12 years of age) to perform a so-called N-back task which requires that children remember words that are presented to them one-at-a-time.  Each time a new word is presented, the children had to decide whether that word was the same as the previous word (1-back) or the previous, previous word (2-back).  Its a maddening task and places an extreme demand on neural circuits involved in active maintenance of information (frontal cortex) as well as inhibition of irrelevant information that occurs during updating (basal ganglia circuits).

As the DAT1 protein is widely expressed in the basal ganglia, the research team asked where in the brain was variation in the DAT1 (9- vs. 10-repeat) associated with neural activity?  and where was there a further difference between 1-back and 2-back?  Indeed, the team finds that brain activity in many regions of the basal ganglia (caudate, putamen, substantia nigra & subthalamic nucleus) were associated with genetic variation in DAT1.  Neat!  the gene may be exerting an influence on brain function (and behavior) in healthy children, even though they do not carry a diagnosis.  Certainly, genes are not destiny, even though they do influence brain and behavior.

What was cooler to me though, is the way the investigators examined the role of genetic variation in the 1-back (easy or low load condition) vs. 2-back (harder, high-load condition) tasks.  Their data shows that there was less of an effect of genotype on brain activation in the easy tasks.  Rather, only when the task was hard, did it become clear that the basal ganglia in the 10/10 carriers was lacking the necessary brain activation needed to perform the more difficult task.  Thus, the investigators reveal that the genetic risk may not be immediately apparent under conditions where heavy “loads” or demands are not placed on the brain.  Cognitive load matters when interpreting genetic data!

This result made me think that genes in the brain might be a lot like genes in muscles.  Individual differences in muscle strength are not associated with genotype when kids are lifting feathers.  Only when kids are actually training and using their muscles, might one start to see that some genetically advantaged kids have muscles that strengthen faster than others.  Does this mean there is a “weak muscle gene” – yes, perhaps.  But with the proper training regimen, children carrying such a “weak muscle gene” would be able to gain plenty of strength.

I guess its off to the mental and physical gyms for me and my son.

** PODCAST accompanies this post** also, here’s a link to the Vaidya lab!

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Recreated :File:Neuron-no labels2.png in Inksc...
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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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If you’re a coffee drinker, you may have noticed the new super-sized portions available at Starbucks.  On this note, it may be worth noting that caffeine is a potent psychoactive substance of which – too much – can turn your buzz into a full-blown panic disorder.  The Diagnostic and Statistical Manual for psychiatry outlines a number of caffeine-related conditions mostly involving anxieties that can arise when the natural alertness-promoting effects are pushed to extremes.  Some researchers have begun to explore the way the genome interacts with caffeine and it is likely that many genetic markers will surface to explain some of the individual differences in caffeine tolerance.

Here’s a great paper, “Association between ADORA2A and DRD2 Polymorphisms and Caffeine-Induced Anxiety” [doi: 10.1038/npp.2008.17] wherein polymorphisms in the adenosine A2A receptor (ADORA2A encodes the protein that caffeine binds to and antagonizes) – as well as the dopamine D2 receptor (DRD2 encodes a protein whose downstream signals are normally counteracted by A2A receptors) — show associations with anxiety after the consumption of 150mg of caffeine (about an average cup of coffee – much less than the super-size, super-rich cups that Starbucks sells).  The variants, rs5751876 (T-allele), rs2298383 (T-allele) and rs4822492 (G-allele) from the ADORA2A gene as well as rs1110976 (-/G genotype) from the DRD2 gene showed significant increases in anxiety in a test population of 102 otherwise-healthy light-moderate regular coffee drinkers.

My own 23andMe data only provides a drop of information suggesting I’m protected from the anxiety-promoting effects.  Nevertheless, I’ll avoid the super-sizes.
rs5751876 (T-allele)  C/C – less anxiety
rs2298383 (T-allele) – not covered
rs4822492 (G-allele) – not covered
rs1110976 (-/G genotype) – not covered

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Walter Dean Myers, an author of The Young Landlords and many other classic coming of age novels once remarked, “The special place of the young adult novel should be in its ability to address the needs of the reader to understand his or her relationships with the world, with each other, and with adults.”  Indeed, the wonderful elaborations of psychosocial development that occur during the teenage years makes for a vivid and tumultuous time – worthy of many a book – especially those like Myers’ that so help adolescents to cope.  During this time, a child’s brain and body is supplanted by adult systems, which, from a physiological point of view, place the adolescent’s mind and body at the mercy of thousands of shifting biochemical processes.  Such a notion of the shifting sands of adolescence were brought to mind while reading a research article focused on one – just one single example – of biochemical change.

The paper entitled, “Cortico-striatal synaptic defects and OCD-like behaviors in SAPAP3 mutant mice” [doi: 10.1038/nature06104] points out that mice who lack the function of the post-synaptic density scaffolding protein encoded by the SAPAP3 gene display excessive grooming and other behaviors reminiscent of obsessive compulsive disorder – a condition that frequently emerges during adolescence.  One of the main findings of the paper is that a normal developmental shift of NR2B –> NR2A subunits of the NMDA receptor does NOT seem to occur – rendering the SAPAP3 mutant mice with an immature form of NMDA receptor.  The authors suggest that this may be the underlying reason for the aberrant behavior, and were able to normalize the mutant mice by re-introducing SAPAP3 protein via a lentiviral-mediated expression vector placed in the striatum.

Gosh.  This NR2B –> NR2A shift is just one example – one grain – in the shifting biochemical sands of development.  Just one of thousands.  How did my brain ever make it through?

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OM, computer generated image - Png file, Atten...
Image by MAMJODH via Flickr

Oxygen is the key to life.  This is because it loves electrons.  In the mitochondria of every cell in your body, oxygen (in is atmospheric O2 state) serves as the ultimate electron acceptor and provides the chemical energy that drives the formation of ATP (a form of chemical energy storage that our body uses for all its cellular functions).

Oxygen is the key to death.  This is because it loves electrons.  When so-called reactive oxygen species (small molecules that contain oxygen in an ionized form) are permitted to roam free in cell and the body, they can indiscriminately pull electrons from other molecules (oxidation) and cause undesirable protein damage and premature cell death.

There is no escaping this chemical reality.  The very substance that giveth life, doth take it away and our longevity teeters on the quantum mechanical balance of electrons whizzing around the nucleus of the oxygen atom.  (I’ll think about this and the chemical symbol for oxygen (O), next time I chant “Om” in yoga class).

So it is with this humbling knowledge that many search for ways to optimize this balance (several populations have already figured out how to routinely live to 100+ years!) or at least improve the quality of our naturally limited life-span.  Light exercise, vegetables, friends and not too much alcohol.

Consider the recent paper, by Srivastava et al., “Association of SOD2, a Mitochondrial Antioxidant Enzyme, with Gray Matter Volume Shrinkage in Alcoholics” [doi: 10.1038/npp.2009.217].  The authors report that shrinkage of the neocortex (gray matter) of the brain is associated  chronic high levels of alcohol consumption.  That’s right, too much alcohol shrinks your brain.  Yikes!  How does alcohol exert its effect on brain shrinkage?  Well,  the authors measured many aspects of liver function (various enzyme levels), but these did not correlate with gray matter shrinkage.  Rather, the authors traced the effect to an enzyme that normally keeps harmful reactive oxygen species at bay – the so-called superoxide dismutase (SOD) enzyme.  We all have this enzyme, but in some of us, those who carry the rs4880 “G” allele of our SOD2 gene produce an enzyme that has an alanine at position 16 (Ala16) and is less active than the rs4880 “A” allele which encodes a more active enzyme with a Valine at position 16 (Val16).  The authors report that the rs10370 “TT”, rs4880 “GG” diplo-genotype (diplotype) was associated with more gray matter shrinkage in 76 individuals who report chronic high levels of alcohol consumption.  Here, the less active form of SOD2 is seemingly less able to metabolize all the harmful superoxide radicals that are generated during chronic exposure to alcohol.  Apparently their neurons are in retreat.

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Summer, Brody and Audric Hug
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If you have a minute, check out this “Autism Sensory Overload Simulation” video to get a feel for the perceptual difficulties experienced by people with autism spectrum disorders.  A recent article, “Critical Period Plasticity Is Disrupted in the Barrel Cortex of Fmr1 Knockout Mice” [doi: 10.1016/j.neuron.2010.01.024] provides some clues to the cellular mechanisms that are involved in this phenomenon.  The authors examined the developing somatosensory cortex in lab mice who carry a mutation in a gene called FMR1.  The normal function of this gene is to help synapses mature and optimize their strength through a process known as activity-dependent plasticity.  This a kind of “use-it-or-lose-it” neural activity that is important when you are practicing and practicing to learn something new – say, like riding a bike, or learning a new language.  Improvements in performance that come from “using” the circuits in the brain are correlated with optimized synaptic connections – via a complex set of biochemical reactions (eg. AMPA receptor trafficking).

When FMR1 is not functioning, neuronal connections (in this case, synapses that connect the thalamus to the somatosensory cortex) cannot mature and develop properly.  This wreaks havoc in the developing brain where maturation can occur in successive critical periods – where the maturation of one circuit is needed to ensure the subsequent development of another.  Hence, the authors suggest, the type of sensory overload reported in the autism spectrum disorders may be related to a similar type of developmental anomaly in the somatosensory cortex.

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Church Steeple
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Humans are spiritual creatures – there’s no denyin’.  How & why we got this way is one of THE BIG questions of all time.  Since our genome shapes the development of our brain and its interaction with our culture, its not a surprise to see that, from time to time, folks will look for and find genetic links to various forms of spiritual and religious behavior.  Here’s a recent paper from Kenneth Kendler’s research team at the Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University School of Medicine entitled, “A Developmental Twin Study of Church Attendance and Alcohol and Nicotine Consumption: A Model for Analyzing the Changing Impact of Genes and Environment” [link to abstract].  An analysis of more than 700 pairs of twins found that the correlation between alcohol and nicotine consumption and church attendance (more church predicts less smokin’ and drinkin’) is more than 50% influenced by genetic factors – in adults.  In children and teens, the genetic contribution to the correlation is much less and the strength of the correlation stems more from shared environmental factors (parents, school etc.).  Is there a gene for going to church? Nope.  Are there genes that shape a person’s inclination toward novelty or conscientiousness? More likely so.  Are they distributed across all races and cultures? Yep.  Lots to ponder next Sunday morning.

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Novelty candles may be used.
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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.

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Diagram to illustrate Minute Structure of the ...
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For a great many reasons, research on mental illness is focused on the frontal cortex.  Its just a small part of the brain, and certainly, many things can go wrong in other places during brain/cognitive development, but, it remains a robust finding, that when the frontal cortex is not working well, individuals have difficulties in regulating thoughts and emotions.  Life is difficult enough to manage, let alone without a well functioning frontal cortex.  So its no surprise that many laboratories look very closely at how this region develops prenatally and during childhood.

One of the more powerful genetic methods is the analysis of gene expression via microarrays (here is a link to a tutorial on this technology).  When this technology is coupled with extremely careful histological analysis and dissection of cortical circuits in the frontal cortex, it begins to become possible to begin to link changes in gene expression with the physiological properties of specific cells and local circuits in the frontal cortex. The reason this is an exciting pursuit is because the mammalian neocortex is organized in a type of layered fashion wherein 6 major layers have different types of connectivity and functionality.  The developmental origins of this functional specificity are thought to lie in a process known as radial migration (here is a video of a neuron as it migrates radially and finds its place in the cortical hierarchy).  As cells are queued out of the ventricular zone, and begin their migration to the cortical surface, they are exposed to all sorts of growth factors and morphogens that help them differentiate and form the proper connectivities.  Thus, the genes that regulate this process are of keen interest to understanding normal and abnormal cognitive development.

Here’s an amazing example of this – 2 papers entitled, “Infragranular gene expression disturbances in the prefrontal cortex in schizophrenia: Signature of altered neural development?” [doi:10.1016/j.nbd.2009.12.013] and “Molecular markers distinguishing supragranular and infragranular layers in the human prefrontal cortex [doi:10.1111/j.1460-9568.2007.05396.x] both by Dominique Arion and colleagues.  In both papers, the authors ask, “what genes are differentially expressed in different layers of the cortex?”.  This is a powerful line of inquiry since the different layers of cortex are functionally different in terms of their connectivity.  For example, layers II-III (the so-called supragranular layers) are known to connect mainly to other cortical neurons – which is different functionally than layers V-VI (the so-called infragranular layers) that connect mainly to the striatum (layer V) and thalamus (layer VI).  Thus, if there are genes whose expression is unique to a layer, then one has a clue as to how that gene might contribute to normal/abnormal information processing.

The authors hail from a laboratory that is well-known for work over many years on fine-scaled histological analysis of the frontal cortex at the University of Pittsburgh and used a method called, laser capture microdissection, where post-mortem sections of human frontal cortex (area 46) were cut to separate the infragraular layer from the supragranular layer.  The mRNA from these tissue sections was then used for DNA microarray hybridization.  Various controls, replicate startegies and in-situ tissue hybridizations were then employed to validate the initial microarray results.

In first paper, the where the authors compare infra vs. supragranular layers, they report that 40 genes were more highly expressed in the supragranular layers (HOP, CUTL2 and MPPE1 were among the most enriched) and 29 genes were highly expressed in the infragranular layers (ZNF312, CHN2, HS3ST2 were among the most enriched).  Other differentially expressed genes included several that have previously been implicated in cortical layer formation such as RLN, TLX-NR2E1, SEMA3E, PCP4, SERPINE2, NR2F2/ARP1, PCDH8, WIF1, JAG1, MBP.  Amazing!! A handful of genes that seem to label subpopulations of projection neurons in the frontal cortex.  Polymorphic markers for these genes would surely be powerful tools for imaging-genetic studies on cognitive development.

In the second paper, the authors compare infra vs. supragranular gene expression in post-mortem brains from patients with schizophrenia and healthy matched controls. Using the same methods, the team reports both supra- and infragranular gene expression changes in schizophrenia (400 & 1200 differences respectively) – more than 70% of the differences appearing to be reductions in gene expression in schizophrenia. Interestingly, the team reports that the genes that were differentially expressed in the infragranular layers provided sufficient information to discriminate between cases and controls, whilst the gene expression differences in the supragranular layers did not.  More to the point, the team finds that 51 genes that were differentially expressed in infra- vs. supragranular expression were also differentially expressed in cases vs. controls  (many of these are also found to be associated in population genetic association studies of schiz vs. control as well!).  Thus, the team has identified layer (function) -specific genes that are associated with schizophrenia.  These genes, the ones enriched in the infragranular layers especially, seem to be at the crux of a poorly functioning frontal cortex.

The authors point to 3 such genes (SEMA3E, SEMA6D, SEMA3C) who happen to members of the same gene family – the semaphorin gene family.  This gene family is very important for the neuronal guidance (during radial migration), morphology, pruning and other processes where cell shape and position are regulated.  The authors propose that the semaphorins might act as “integrators” of various forms of wiring during development and in adulthood.  More broadly, the authors provide a framework to understand how the development of connectivity on the frontal cortex is regulated by genetic factors – indeed, many suspected genetic risk factors play a role in the developmental pathways the authors have focused on.

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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”

silence

.is
a
looking

bird:the

turn
ing;edge, of
life

(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.

***PODCAST ACCOMPANIES THIS POST***

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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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Just a pointer to onetime University of Edinburgh Professor C.H. Waddington’s 1972 Gifford Lecture on framing the genes vs. environment debate of human behavior.  Although Waddington is famous for his work on population genetics and evolutionary change over time, several of his concepts are experiencing some resurgence in the neuroimaging and psychological development literatures these days.

One term, CHREOD, combines the Greek word for “determined” or “necessary” and the word for “pathway.” It describes a system that returns to a steady trajectory in contrast to homeostasis which describes a system which returns to a steady state.  Recent reviews on the development of brain structure have suggested that the “trajectory” (the actual term “chreod” hasn’t survived) as opposed to any specific time point is the essential phenotype to use for understanding how genes relate to psychological development.  Another term, CANALIZATION, refers to the ability of a population to produce the same phenotype regardless of variability in its environment or genotype.  A recent neonatal twin study found that the heritability of grey matter in neonatal humans was rather low.  However it seems to then rise until young adulthood – as genetic programs presumably kick-in – and then decline again.  Articles by neurobiologist Jay N. Giedd and colleagues have suggested that this may reflect Waddington’s idea of canalization.  The relative influence of genes vs. environment may change over time in ways that perhaps buffer against mutations and/or environmental insults to ensure the stability and robustness of functions and processes that are both appropriate for survival and necessary for future development.  Another Waddington term, EPIGENETIC LANDSCAPE, refers to the limitations on how much influence genes and environment can have on the development of a given cell or structure.  Certainly the environment can alter the differentiation, migration, connectivity, etc. of neurons by only so much.  Likewise, most genetic mutations have effects that are constrained or compensated for by the larger system as well.

Its amazing to me how well these evolutionary genetic concepts capture the issues at the nexus of of genetics and cognitive development.  From his lecture, it is clear that Waddington was not unaware of this.  Amazing to see a conceptual roadmap laid out so long ago.  Digging the book cover art as well!

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