Posts Tagged ‘default network’


We all have social networks.  Your friends and family are a network of relationships.  The neural networks in your brain that carry out computations involved in social interactions are another type of “social network”.  These two networks are obviously related – in so far as your ability to self-reference and understand your own internal thoughts and feelings predicts how well you can understand and predict the internal thoughts and feelings of others – and thus how extensive your network of friends and family is likely to be.  The structure of your brain networks may even be related to how many friends you have on facebook.

According to Lencz and colleagues, there is a genetic association between the T-allele of rs1344706 and the structure and connectivity of the neural networks that carry out self-referential processing in the brain … in the so-called “default mode network” that is associated with “stimulus independent” mental activity and with social cognition such as when you are attributing mental states to others.

Interestingly, the T-allele of this SNP – residing in the zinc finger protein 804A gene – has been previously associated with schizophrenia (SZ).

From Lencz and colleagues:

“To our knowledge, this is also the first study to identify a genetic correlate of multiple brain regional GM volumes comprising the default mode network.”

The default mode network comprises regions that show synchronized activity at ‘resting’ baseline, in the absence of specific stimulation (Raichle et al, 2001). Ongoing work has implicated this network in the development of self-referential thought (Spreng and Grady, 2010), which has been specifically implicated in the developmental psychopathology of SZ (Nelson et al, 2009).

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




ing;edge, of

(inquiry before snow

e.e. cummings

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

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

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

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


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

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

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

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

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

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

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

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