Posted in COMT, DARPP32, DRD2, Uncategorized, tagged Artificial Intelligence, Basal Ganglia, Brown University, Cognition, Cognitive science, Dopamine, economics, interviews, podcasts, Working memory on August 18, 2009 |
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If you’re interested in the neurobiology of learning and decision making, then you might be interested in this brief interview with Professor Michael Frank who runs the Laboratory of Neural Computation and Cognition at Brown University.
From his lab’s website: “Our research combines computational modeling and experimental work to understand the neural mechanisms underlying reinforcement learning, decision making and working memory. We develop biologically-based neural models that simulate systems-level interactions between multiple brain areas (primarily basal ganglia and frontal cortex and their modulation by dopamine). We test theoretical predictions of the models using various neuropsychological, pharmacological, genetic, and neuroimaging techniques.”
In this interview, Dr. Frank provides some overviews on how genetics fits into this research program and the genetic results in his recent research article “Prefrontal and striatal dopaminergic genes predict individual differences in exploration and exploitation”. Lastly, some lighthearted, informal thoughts on the wider implications and future uses of genetic information in decision making.
To my mind, there is no one else in the literature who so seamlessly and elegantly interrelates genetics with the modern tools of cognitive science and computational neurobiology. His work really allows one to cast genetic variation in terms of its influence on neural computation – which is the ultimate way of understanding how the brain works. It was a treat to host this interview!
Click here for the podcast and here, here, here for previous blog posts on Dr. Frank’s work.
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Posted in 5HTT, DARPP32, DLPFC, Dopamine, Frontal cortex, MAOA, tagged Biology, Brain, Eukaryotic, Functional magnetic resonance imaging, Gene, Genetic diversity, Genetics, MAOA on July 31, 2009 |
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Amidst a steady flow of upbeat research news in the behavioral-genetics literature, there are many inconvenient, uncomfortable, party-pooping sentiments that are more often left unspoken. I mean, its a big jump – from gene to behavior – and just too easy to spoil the mood by reminding your colleagues that, “well, everything is connected to everything” or “that gene association holds only for that particular task“. Such may have been the case often times in the past decade when the so-called imaging-genetics literature emerged to parse out a role for genetic variation in the structure and functional activation of the brain using various neuroimaging methods. Sure, the 5HTT-LPR was associated with amygdala activation during a face matching task, but what about other tasks (and imaging modalities) and other brain regions that express this gene. How could anyone (let alone NIMH) make sense out of all of those – not to mention the hundreds of other candidate genes poised for imaging-genetic research?
With this in mind, it is a pleasure to meet the spoiler-of-spoilers! Here is a research article that examines a few candidate genetic polymorphisms and compares their findings across multiple imaging modalities. In his article, “Neural Connectivity as an Intermediate Phenotype: Brain Networks Under Genetic Control” [doi: 10.1002/hbm.20639] Andreas Meyer-Lindenberg examines the DARPP32, 5HTT and MAOA genes and asks whether their associations with aspects of brain structure/function are in any way consistent across different neuroimaging modalities. Amazingly, the answer seems to be, yes.
For example, he finds that the DARPP32 associations are consistently associated with the striatum and prefrontal-striatal connectivity – even as the data were collected using voxel-based morphometry, fMRI in separate tasks, and an analysis of functional connectivity. Similarly, both the 5HTT and MAOA gene promoter repeats also showed consistent findings within a medial prefrontal and amygdala circuit across these various modalities.
This type of finding – if it holds up to the spoilers & party poopers – could radically simplify the understanding of how genes influence cognitive function and behavior. As suggested by Meyer-Lindenberg, “features of connectivity often better account for behavioral effects of genetic variation than regional parameters of activation or structure.” He suggests that dynamic causal modeling of resting state brain function may be a powerful approach to understand the role of a gene in a rather global, brain-wide sort of way. I hope so and will be following this cross-cutting “connectivity” approach in much more detail!
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Image via Wikipedia To go out tonight or stay home? Hillary or Barack? Curly fries or onion rings? How do I make these important choices and why will others decide differently? Although there are many reasons for not stressing-out and over-thinking one’s decisions (except for really important choices like curly fry vs. onion ring), it turns out that variation in your genome, in particular, 3 dopaminergic genes (DARPP-32, DRD2 and COMT: rs907094, rs1800496, rs4680) are influencing your tendency to ‘go for it’ or not to go for it. Frank and colleagues, in their paper, “Genetic triple dissociation reveals multiple roles for dopamine in reinforcement learning“, give an in-depth treatment of the neurobiology underlying decision making and reinforcement learning. After carefully reviewing the basic biology of dopaminergic synapses and selecting 3 candidate genetic variants, they find that each is associated with an independent aspect of decision making in a learning paradigm. The paper is an excellent example of how genetic variation can be linked to specific neural processes. Now bring on the curly fries – no wait – the onion rings.
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