Tuesday, October 14, 2014

Mysterious Resting State Networks Might Be What Allow Different Brain Therapies to Work

From Pacific Standard, this is a brief review of new research around the efficacy of deep brain stimulation and transcranial magnetic stimulation for the treatment of various types of psychological distress (depression, bipolar, and so on). Their results suggest that brain networks might be used to understand why brain stimulation works and to improve this form of therapy by identifying the best places to stimulate the brain.

First up is the summary from PS, followed by the full abstract (article is paywalled).

Mysterious Resting State Networks Might Be What Allow Different Brain Therapies to Work


By Nathan Collins • October 01, 2014

FMRI scans from another study. (Photo: Public Domain)

Deep brain stimulation and similar treatments target the hubs of larger resting-state networks in the brain, researchers find.

More and more, doctors and patients dealing with severe depression, obsessive compulsive disorder, or even Parkinson’s disease turn to techniques such as deep brain stimulation and transcranial magnetic stimulation. While those treatments have proven effective in some cases, it has been unclear why the hodgepodge of stimulation sites and techniques all seem to work. A new study suggests one possibility: the different methods each activate parts of the brain common to one of its resting state networks.

For a few decades now, neuroscientists who specialize in functional magnetic resonance imaging, or fMRI, have focused on what our brains do when we do math problems, play games, choose between politicians, and much more. But as early as the mid-1990s, researchers realized they’d been missing something: What happens when we’re not doing anything at all? With that question, they began to explore what’s called the default mode network and other resting state networks (RSNs), collections of brain regions that are active and working together specifically as we let our minds and senses wander. But no one is quite sure what exactly these networks do.

Around the same time as some were exploring RSNs, others were pioneering the next generation of brain stimulation techniques, methods somewhat less crude than early forms of electroconvulsive therapy. Some new methods are invasive—deep brain stimulation, for example, requires an electrical implant in the brain—and some aren’t. Transcranial magnetic stimulation involves a targeted magnetic pulse originating outside the brain. They have one thing in common, though: Different techniques applied in different parts of the brain often achieve the same goals.

It works that way, Michael Fox and five others argue, because of resting state networks. To figure that out, the team reviewed clinical studies that had used deep brain stimulation (DBS), transcranial magnetic stimulation (TMS), and a third method, transcranial direct current stimulation, or tDCS, to treat 14 disorders, including anorexia, depression, and Tourette syndrome. Across all 14 diseases except for one, epilepsy, they found correlations between resting-state activity in sites where DBS was effective and in others where TMS and tDCS were effective, indicating that such sites were all part of the same resting-state network. Backing that conclusion up was the observation that there seemed to be little, if any, connection between DBS regions that worked and regions where other kinds of stimulation had failed.

“Sites effective for the same disease tend to fall within the same brain network [and] ineffective sites fall outside this network,” the authors write in Proceedings of the National Academy of Science. Researchers who study psychiatric disorders had already started thinking in network terms, and now they have an even better reason to.


Nathan Collins studied astrophysics and political science before realizing he wanted to learn about all of the science without worrying about tenure. In his second life as a freelance science writer, he’s written for Scientific American, New Scientist, and others.

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Resting-state networks link invasive and noninvasive brain stimulation across diverse psychiatric and neurological diseases


Michael D. Fox, Randy L. Buckner, Hesheng Liu, M. Mallar Chakravarty, Andres M. Lozano, and Alvaro Pascual-Leone

Edited by Michael S. Gazzaniga, University of California, Santa Barbara, CA, and approved August 28, 2014 (received for review March 17, 2014)

Significance

Brain stimulation is a powerful treatment for an increasing number of psychiatric and neurological diseases, but it is unclear why certain stimulation sites work or where in the brain is the best place to stimulate to treat a given patient or disease. We found that although different types of brain stimulation are applied in different locations, targets used to treat the same disease most often are nodes in the same brain network. These results suggest that brain networks might be used to understand why brain stimulation works and to improve therapy by identifying the best places to stimulate the brain.

Abstract

Brain stimulation, a therapy increasingly used for neurological and psychiatric disease, traditionally is divided into invasive approaches, such as deep brain stimulation (DBS), and noninvasive approaches, such as transcranial magnetic stimulation. The relationship between these approaches is unknown, therapeutic mechanisms remain unclear, and the ideal stimulation site for a given technique is often ambiguous, limiting optimization of the stimulation and its application in further disorders. In this article, we identify diseases treated with both types of stimulation, list the stimulation sites thought to be most effective in each disease, and test the hypothesis that these sites are different nodes within the same brain network as defined by resting-state functional-connectivity MRI. Sites where DBS was effective were functionally connected to sites where noninvasive brain stimulation was effective across diseases including depression, Parkinson's disease, obsessive-compulsive disorder, essential tremor, addiction, pain, minimally conscious states, and Alzheimer’s disease. A lack of functional connectivity identified sites where stimulation was ineffective, and the sign of the correlation related to whether excitatory or inhibitory noninvasive stimulation was found clinically effective. These results suggest that resting-state functional connectivity may be useful for translating therapy between stimulation modalities, optimizing treatment, and identifying new stimulation targets. More broadly, this work supports a network perspective toward understanding and treating neuropsychiatric disease, highlighting the therapeutic potential of targeted brain network modulation.
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