A new system for functional analysis of neural networks

 FINDINGS:  By using a combination of genetic tools the Dymecki lab has developed a method for silencing specific neural networks in vivo.
RELEVANCE:  By silencing networks based on their specific gene expression history, researchers will be able to investigate the in vivo function of discrete, precise, and functionally related neuronal networks.  
 
Boston, Mass. (Sept. 28, 2009) - It is one of the most fundamental approaches to understanding how a system works. If you do not know the function of a specific component within a system, remove it, and see what happens.  From determining which of the morass of cables behind an entertainment system controls the DVD player, to micro-dissection of developmental signaling centers to targeted genetic disruptions, the basic concept is the same. Function is inferred by the effects of disruption. 
This works fine for a system with easily separable components.  But what about the central nervous system, the functional components of which are intertwined networks of cellular fibers?
Classical neurologists relied on chance.  Randomly developed brain lesions have been one of the best ways to determine the function of a region of the brain for over 100 years. Among other insights, lesion analysis has contributed to the understanding which general regions of the brain control memory, language, spatial skills, object recognition and processing of emotional reactions. But the lesions are random, rare, and rather crude often affecting multiple regions of the brain. 
fMRI has recently allowed investigators to dynamically visualize neurological activity in subjects while they perform specific tasks, allowing them to infer function based on which neural component lights up when a specific task is performed.  But it does not tell you what happens when you lose function, and it can not tell you precisely which cells are involved within  the area of activity.
So just how does one isolate a sub-section of a neural network, and silence its function? Susan Dymecki and Jun Chul Kim, a post-doctoral researcher in her lab, have developed an elegant method for doing just that.  By incorporating tetanus toxin into their dual recombinase reporter system they are able to disrupt synaptic communication in any targeted network. Thus, by incorporating the silencing system into various combinations of Flp and Cre expressing mice, they can very precisely target networks that are defined by the intersection of two distinct gene expression patterns.  In their introduction of this strategy, Dymecki and Kim have targeted subsets of serotonergic neurons.  Using this precise targeting method they were able to map distinct behaviors (such as anxiety-related behaviors versus associative learning or startle reflex behaviors) on to different serotonergic sub-networks.  Given the huge variety of gene expression patterns along the dorsal-ventral and anterior-posterior axis of the developing neural tube, there will not be a shortage of informative combinations anytime soon.
The results of their work were published in the August 13th issue of Neuron.