This [interesting blog](http://brainmagnets.blogspot.com/) by Dr. Topher Stephenson tracks the use of “neuromodulation” techniques, including electrical and magnetic stimulation of specific brain regions to produce desired changes in mood and behavior. This seemingly far-out technology is a major topic of applied research today, with new discoveries coming almost too fast to track.
In [this post ](http://brainmagnets.blogspot.com/2007/09/9v-battery-for-depression.html), for instance, Dr. Stephenson reports on a small, double blind [study](http://journals.cambridge.org/action/displayAbstract?fromPage=online&aid=1044804) of “transcranial direct current stimulation” of 40 depressed patients that showed significant results.
Among the most interesting things about these techniques is that they use weak electrical current. “All with a nine volt battery,” is Dr. Stephenson’s wry comment. “Maybe I should regress back to being a young kid and start licking batteries more often???????”
The possibility of altering brain states using weak electrical current raises the possibility of – eventually – self-modulation. This is not to say that the knowledge exists to drive our brains the way we pilot a little remote control car; only that the increased precision and decreased power demands of neuromodulation reduces risk tremendously, and makes it ever more likely that these tools will eventually leave the lab.
Among the many interesting links from the NueroMod Blog is one to [this piece](http://www.technologyreview.com/blog/boyden/) by [Ed Boyden](http://edboyden.org/) in MIT’s technology review. Boyden points out that even fairly precise stimulation of specific brain regions can produce a range of different effects, not all of which may be equally desirable. Boydon is among the researchers attempting to sort out these different effects, and identify what types of interventions can work under different circumstances. He is a thoughtful, interesting writer.
> Consider the question of how you might augment cognition and mood by stimulating selected neural circuits. You’d probably want maximum flexibility — the ability to tune mood, decision-making, judgment, and so on, independent of one another. Researchers have attempted to alter cognitive functions by noninvasive stimulation of cortical brain regions, each a few cubic centimeters in volume. It’s become clear, however, that these brain regions are not the most elementary of brain circuit elements. For example, manipulation of one specific brain region can change many cognitive and emotional functions, in parallel. Consider the concrete example of [transcranial magnetic stimulation](http://en.wikipedia.org/wiki/Transcranial_magnetic_stimulation) (TMS) of the right prefrontal cortex. In the last few years, studies have shown that TMS of this brain region with a standard protocol (one pulse per second for 10 to 30 minutes) can [alter decision-making in the face of unfairness](http://www.sciencemag.org/cgi/content/abstract/1129156), [improve the symptoms of depression](http://archpsyc.ama-assn.org/cgi/content/abstract/56/4/315), and [increase risk-taking behavior.](http://www.jneurosci.org/cgi/content/full/26/24/6469) Thus, it may be difficult to induce a specific, desired brain state, without inducing other (perhaps undesired) brain states, when the primitives under consideration are all “brain regions.” Clearly, this convenient abstraction layer, which has been prominent across centuries of neuroscience, will need to be refined in order to develop a fully flexible architecture for cognitive augmentation.
> In our lab, we have begun to assemble a toolbox of methods for precisely controlling specific neural-circuit primitives. We are now using these tools to learn how to control behavioral outputs, with great precision and power. Hopefully, in this way we will learn what the neurobiological primitives are for engineering the brain and develop design rules for the optimal control of neural-circuit output, especially in disease states. We’re at an early stage. The synthetic biologists started off with the strong hypothesis that genes were the right abstraction layer. After all, the genome is fundamental, and DNA is easy to generate, manipulate, and read. But for neural computation, we don’t know what the DNA equivalent is. Are the primitives dendritic elements? Single neurons? Synaptic connections? Cell types? Small networks? Large networks? And at what nervous-system scales should we be reading? Writing?