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Posts Tagged ‘Electroencephalography’

lie_robot

Let’s be honest.  We are all great liars … to ourselves, and others.  The big blatant lies (I swear I never had sex with Monica Lewinsky) and the little well-meaning lies (No honey, that dress does not make your butt look big) and especially the lies that contain just enough truth as to seem believable on a global scale (Lowering taxes on the rich will spur economic growth) … are what make our lives, and daytime TV, so interesting.

Pity the poor human brain … for some people think that IT cannot tell a lie. Scientists in collaboration with law enforcement have been measuring the  P300 brain wave  as a sort of lie detector (here, here, here) more specifically  “an accurate, and countermeasure (CM)-resistant P300-based Guilty Knowledge Test.”

Interestingly, the properties of the P300 neural biomarker are highly heritable and associated with a variety of genetic polymorphisms – including rs521674 located in the noradrenergic receptor ADRA2A gene (functions in the alerting and stress response elicited when lying/trying not to lie).

I’m an AT heterozygote at rs521674 and proud of my pro-deceitful suppressed P300 … because sometimes all you have to cling to are the lies you tell yourself.

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[picapp src=”e/7/8/1/Children_Attend_Classes_9572.jpg?adImageId=4955179&imageId=1529412″ width=”380″ height=”253″ /]

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

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

The researchers sought to answer this question by screening 41 volunteers at 384 single nucleotide polymorphisms (SNPs) in 222 genes selected for their metabolic function in the brain.  The team used electroencephalogram recordings of brain activity to measure differences in activity for “boop” vs. “beep” type stimuli – specifically, at certain times before and after stimulus onset – described by the so-called N1, N2b, P3a, P3b component peaks in the event-related potentials waveforms.  800px-Erp1Genotype data (coded as 1,0,-1 for aa, aA, AA) and EEG data were plugged into the team’s home-grown parallel independent components analysis (ICA) pipeline (generously provided freely here) and several positives were then evaluated for their relationships in biochemical signal transduction pathways (using the Ingenuity Pathway Analysis toolkit.  A very novel and sophisticated analytical method for certain!

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

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

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Animation of an MRI brain scan, starting at th...Image via Wikipedia OK, the title of this post is fanciful – even for the blogosphere – but the recent open access paper, “Using fMRI Brain Activation to Identify Cognitive States Associated with Perception of Tools and Dwellings” by Shinkareva and team (DOI) is pretty darn amazing. The authors ask subjects to view pictures of and think about a set of objects: drill, hammer, screwdriver, pliers, saw, apartment, castle, house, hut, and igloo (tools vs. dwellings) while laying in an MRI scanner. The patterns of brain activity associated with each category were then used to train a pattern recognition learning program in order to discriminate between these two categories. Subsequent testing of the pattern recognizer showed that it could accurately predict what category of object a subject was viewing based on the pattern of brain activity. Interestingly, there were striking commonalities across subjects in the locations and activation amplitudes of regions for each category suggesting that the brains of different people are using similar neural pathways to represent semantic information. It is easy to imagine that genetic factors regulating human brain development may contribute to this invariance. I’m not sure if I’ll be surprised when this question is answered – perhaps my brain/genome scan will tell me whether I was or not.

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