July 12, 2013. About 2,300 neuroscientists from all over the world gathered in downtown Seattle June 16-20 for the annual meeting of the Organization of Human Brain Mapping (OHBM). Presentations ranged from imaging the brain in sickness and in health; resting-state versus task-based strategies; analytical tools to make sense of all the voxels streaming in; and the latest brain stimulation techniques. Schizophrenia figured prominently in one morning workshop devoted to exploring different measures of brain organization in mental illness. Toward the end of the meeting, Thomas Insel, the director of the National Institute for Mental Health (NIMH), dropped by for a town hall-styled conversation about the new BRAIN (Brain Research for Advancing Innovative Neurotechnologies) initiative announced in April by the Obama administration (Insel et al., 2013).
Brain organization in schizophrenia
Vince Calhoun of the University of New Mexico in Albuquerque organized the workshop, held Tuesday, June 18, which featured talks about ways to capture the brain’s connectivity and how these networks might differ in schizophrenia. All speakers used functional magnetic resonance imaging (fMRI) to monitor co-activated regions of the brain, which was then taken as a measure of their connectivity.
Ed Bullmore of the University of Cambridge, United Kingdom, reviewed his graph theoretical approach, which focuses on hub regions of the brain that are highly connected to other parts of the brain. At rest, the brain in schizophrenia seems to have fewer of these hubs (Lynall et al., 2010), and modeling work from Bullmore’s group suggests this could stem from too many long-range connections (see SRF related news story). Bullmore proposed that these hub regions represent the most valuable components of the brain’s network and that brain disorders, including mental illnesses, are “hubopathies.” To back this up, he showed new computer simulations in which targeted removal of hub regions steeply decreased global efficiency—a measure of how well information flows through the brain—compared to random removal of brain regions.
In his talk, Vince Calhoun emphasized the dynamic nature of the brain’s connectivity patterns, even at rest. Last year his group reported that, at rest, the healthy brain cycles through distinct states, with some regions tightly co-activated some of the time, then less well correlated or even anti-correlated at other times (Allen et al., 2012). He showed data indicating differences in these states in schizophrenia and bipolar disorder, and a poster by Barnaly Rashid of his lab delved into the details. Of five distinct states identified during rest, people with schizophrenia and bipolar disorder transitioned into three of these states less often than controls did, and both spent less time in state 2, which is noted for decreased correlations within sensorimotor regions, but high correlations within cognitive control regions, visual regions, and default-mode regions. State 5 also looked slightly different in schizophrenia and bipolar: Bipolar disorder was marked by reduced connectivity between visual areas and frontal cortex, whereas the version of state 5 in schizophrenia included several regions that were over- or underconnected compared to controls.
In her talk, Talma Hendler of Tel Aviv University, Israel, described the dynamics of brain connectivity as emotions evolved while people with schizophrenia watched movie clips. This approach has allowed her to dissect two different networks involved in empathy in a previous study: an insula-anterior cingulate circuit tied to “embodied simulation,” which represents a bottom-up process by which a person viscerally feels another’s emotions, and a medial prefrontal cortex-temporal-parietal circuit tied to “Theory of Mind,” which reflects a more cognitive rumination on someone else’s emotions (Raz et al., 2013). Synchrony within these regions tracks with emotion intensity, and Hendler presented new data from people with schizophrenia showing that, despite reporting similar fear intensities as controls while watching the movies, their brain synchrony differed, overemphasizing the Theory of Mind network. Healthy siblings of people with schizophrenia showed intermediate levels of synchrony, suggesting that some of the pattern of emotion-related brain changes reflect vulnerability to the disorder and its associated difficulties in reading emotions.
In the last talk, Tianzi Jiang of the Chinese Academy of Sciences, Beijing, China, described the brainnetome (as in Brain-net-ome), a Chinese project to study the brain at multiple levels, taking its networks as the basic unit of research (Jiang, 2013). Part of this initiative involves scanning, with both structural and functional imaging methods, 1,000 schizophrenia patients, and the researchers have already scanned half that number. This integrative view will not only provide a fuller picture of the brain in the disorder, but the researchers also hope to develop a way to diagnose it through imaging.
Jiang described recent results of this effort: A single-nucleotide polymorphism in the disrupted in schizophrenia 1 (DISC1) gene was associated with disrupted connectivity in healthy controls. Specifically, for the risk variant Ser704Cys, Cys allele carriers showed decreased global efficiency relative to Ser homozygotes (Li et al., 2013). New data presented by Bing Liu in a poster from the group also reported decreased white matter integrity in the tracts connecting the thalamus to the medial prefrontal cortex for Cys allele carriers, implicating DISC1 function in brain connections.
NIH BRAIN initiative: the next big thing?
This "big science" approach to solving the brain’s mysteries seems to be catching on, with other projects underway in Europe, Israel, and now the United States. Touted as the “next great American project,” on the order of the moonshot or the Human Genome Project, the NIH’s BRAIN initiative plans to pull together different fields to develop the tools most needed to decode the language of the brain. On Wednesday afternoon, June 19, Thomas Insel was on hand to explain and receive feedback on the new initiative. He acknowledged that the complexity of the brain made the ultimate goals of this project harder to identify than, say, the Human Genome Project’s clear endpoint. An advisory group is now developing priorities for research, and their recommendations are expected by August. Insel tried to calm anxieties about the project taking away money from the already strapped NIH budget, saying that its budget for 2014 was less than 1 percent of the $5.5 billion planned for neuroscience research.
Though it is unclear whether the project will involve brain imaging, or even human studies, plenty of comments followed. One person suggested that understanding brain development was a worthy target, as finding ways to treat what are now lifelong developmental disorders would be a good return on research investment. Another audience member suggested that, in parallel with developing tools, there is a need for developing analysis techniques that can deal with the massive amounts of data to come (and that are already swamping researchers). Yet another attendee countered that there were already ways for dealing with high-dimensional datasets in the fields of computer science, statistics, and physics. “There are people out there already who can do this,” he said, to applause from the audience. Finally, someone suggested that focusing on brain disorders could break open brain operation better than studying healthy brains. Insel said that, as director of the NIMH, he had no quibbles with that idea, but as far as he knew, the BRAIN initiative was “agnostic” about disorders.—Michele Solis.