Posts Tagged ‘Neural network’

03.23.09 [#082] Yogurt Reach
Image by Jeezny via Flickr

Pity the poor brain.  What a job it has!  Did you know that just to reach into a refrigerator and grab a glass of milk, involves at least 50 or so key muscles in the hand, arm and shoulder which can, in principle, lead to over 1,000,000,000,000,000 possible combinations of muscle contractions?  Just so you know, this is 1,000 times MORE contraction possibilities than there are neurons in the brain (only a mere 1,000,000,000,000 neurons).  I’m sorry brain, I’ll keep my hands out of the fridge, I promise!

To accomplish this computational feat, Rodolfo R. Llinas and Sisir Roy in their paper entitled, “The ‘prediction imperative’ as the basis for self-awareness” [doi:10.1098/rstb.2008.0309] suggest that brain has evolved a number of strategies.

For starters, the authors point out that the brain can lower the computational workload of controlling 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.“

Another strategy is the use of memory for the purposes of prediction (actually, their paper is part of a special theme issue from the Philosophical Transactions of the Royal Society B entitled, Predictions in the brain: using our past to prepare for the future).  The authors 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 using that information for making predictions and pre-prepared plans for what to do with expected incoming sensory inputs.  These neural mechanisms may also help reduce computational loads 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 where the “self” resides.

Lastly, the authors suggest that the genome might encode certain structural and functional aspects of neural development that create a bias for certain types of computation and prime neural networks with a Bayesian type of prior knowledge.  Their idea is akin to an organism being “experience expectant” rather than a pure blank slate that has to learn every stimulus-response contingency by trial-and-error.  To support their notion of the role of the genome, the authors cite a 2003 study from the Yonas Lab on the development of depth perception.  Another related study is covered here.

Methinks that genetic variants might someday be understood in terms of how they bias computational processes.  Something to shoot for in the decades to come!

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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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** 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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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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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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SfNneuroblogbadgeIn 13th century India,  the story was originally told of a group of blind men (or men in the dark) who touch an elephant to learn what it is like.  Each one touches a different part, but only one part, such as the side or the tusk.  They then compare notes on what they felt, and learn they are in complete disagreement.

With this ancient story in mind,  I’d like to introduce you to the annual conference of the Society for Neuroscience, or SfN, where brain enthusiasts across the globe gather for 5 days to compare notes – not on an elephant – but on something more massive – the brain and mind.  The vast complexities of neural development and communication will be shared amongst some 31,000+ participants in an effort to integrate findings from molecular to neural physiology to systems dynamics to behavior and find some  agreement on one of the all-time great biological mysteries.

As but a single humble molecular/cognitive/neuro/blogger, I will do my best to focus specifically on stories and highlights that address the dilemma of the bind men and the elephant and look for stories that  interlink different levels of analysis and help integrate data and models across different levels of analysis. I am fascinated by the way in which data from molecular levels of analysis can be interlinked with synaptic and systems levels of analysis and so hope to relate some of these interconnections with my readers.

You can readily follow the action at this years gathering using the fantastic organizational, informatic tools on the SfN meeting planner.  There are a number of resources to support neuro-bloggers and theme-specific neuro-tweeters.  Also, DrugMonkey has a growing list of other SfN tweeters/bloggers.  The real-time flow on Twitter #sfn09 as well as #sfnthemea & (b,c,d,e, and the notorious h) is already amazing !!

Please join the fray and share your thoughts with the SfN community! See you in Chicago.

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In previous posts, we have explored some of the basic molecular (de-repression of chromatin structure) and cellular (excess synaptogenesis) consequences of mutations in the MeCP2 gene – a.k.a the gene whose loss of function gives rise to Rett syndrome.  One of the more difficult aspects of understanding how a mutation in a lowly gene can give rise to changes in cognitive function is bridging a conceptual gap between biochemical functions of a gene product — to its effects on neural network structure and dynamics.  Sure, we can readily acknowledge that neural computations underlie our mental life and that these neurons are simply cells that link-up in special ways – but just what is it about the “connecting up part” that goes wrong during developmental disorders?

In a recent paper entitled, “Intact Long-Term Potentiation but Reduced Connectivity between Neocortical Layer 5 Pyramidal Neurons in a Mouse Model of Rett Syndrome” [doi: 10.1523/jneurosci.1019-09.2009] Vardhan Dani and Sacha Nelson explore this question in great detail.  They address the question by directly measuring the strength of neural connections between pyramidal cells in the somatosensory cortex of healthy and MeCP2 mutant mice.  In earlier reports, MeCP2 neurons showed weaker neurotransmission and weaker plasticity (an ability to change the strength of interconnection – often estimated by a property known as “long term potentiation” (LTP – see video)).   In this paper, the authors examined the connectivity of cortical cells using an electrophysiological method known as patch clamp recording and found that early in development, the LTP induction was comparable in healthy and MeCP2 mutant animals, and even so once the animals were old enough to show cognitive symptoms.  During these early stages of development, there were also no differences between baseline neurotransmission between cortical cells in normal and MeCP2 mice.  Hmmm – no differences? Yes, during the early stages of development, there were no differences between genetic groups – however – once the team examined later stages of development (4 weeks of age) it was apparent that the MeCP2 animals had weaker amplitudes of cortical-cortical excitatory neurotransmission.  Closer comparisons of when the baseline and LTP deficits occurred, suggested that the LTP deficits are secondary to baseline strength of neurotransmission and connectivity in the developing cortex in MeCP2 animals.

So it seems that MeCP2 can alter the excitatory connection strength of cortical cells.  In the discussion of the paper, the authors point out the importance of a proper balance of inhibition and excitation (yin and yang, if you will) in the construction or “connecting up part” of neural networks.  Just as Rett syndrome may arise due to such a problem in the proper linking-up of cells – who use their excitatory and inhibitory connections to establish balanced feedback loops – so too may other developmental disorders such as autism, Down’s syndrome, fragile X-linked mental retardation arise from an improper balance of inhibition and excitation.

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