The Technicolor Brain
Researchers at Harvard University have developed a new method for setting the brain aglow in a rainbow of colors. The technology will allow scientists to generate maps of one of the brain’s last frontiers: the complex tangle of neural circuits that collect, process, and archive information. Such maps could ultimately shed light on the early development of the human brain and on diseases such as autism and schizophrenia, which have been linked to connectivity problems.
“This will be an incredibly powerful tool,” says Elly Nedivi, a neuroscientist at MIT who is not involved in the research. “It will open up huge opportunities in terms of looking at neural connectivity.”
For years, scientists have used fluorescent proteins derived from jellyfish to mark specific cells in genetically engineered animals. But the limited number of available colors wasn’t enough to create a detailed picture of the millions of neurons in the brain. Jean Livet, Jeff Lichtman, and their collaborators at Harvard genetically engineered mice to carry numerous copies of genes that code for fluorescent proteins of three different colors–yellow, red, and cyan–as well as an enzyme that can randomly block any subset of these genes from producing their fluorescent tag.
When the mice are fed a compound that activates the enzyme, each cell undergoes a random molecular process in which subsets of the color-coding genes are knocked out. The remaining genes produce the three colored fluorescent compounds in different amounts, which combine to form a unique new hue. “We get a wide range of colors–about 100,” says Lichtman. The researchers call the animals “brainbow” mice because of the colorful images they capture of their brains. A new paper describing the process was published today in the journal Nature.
See the images produced by genetically engineered "brainbow" mice.
The ability to paint individual brain cells with such a broad palette will allow neuroscientists to explore neural circuits like never before. Most previous work has focused on larger-scale anatomy or on the function of individual cells, missing out on the detailed wiring in between these two scales. “There’s a whole class of disorders of the nervous system that people suspect are due to defects in the connections between nerve cells, but we don’t have real tools to trace the connections,” says Lichtman. “It would be very useful to look at wiring in animal models of autism spectrum disorder or psychiatric illness.”
When neighboring cells are labeled with the same color, as in previous methods, it’s difficult to discern each cell’s path in the brain. But in this case, neighboring cells are usually different colors, allowing scientists to follow their tangled projections as they branch and synapse throughout the brain. In a proof of principle experiment, the researchers traced all the connections in a small slice of cerebellar tissue, the part of the brain that controls balance and movement. “It will allow scientists to figure out not just what neurons do, but what they do in context of the intact circuit,” says Nedivi. “I’m sure the day the paper comes out, everyone and their mother will be calling them and asking for these mice.”
Lichtman and his collaborators plan to use the technique to study how the brain develops. “During development, wiring changes in a dramatic way,” says Lichtman. Young mammals actually have too many connections and must prune away the excess, but it’s unclear how that happens. “The choice of which connections are maintained and lost probably has a lot to do with how humans are shaped by their experience,” he says. “Understanding the rules of that trimming requires seeing [which connections] might stay, versus which might leave.”
Geoffrey Hinton tells us why he’s now scared of the tech he helped build
“I have suddenly switched my views on whether these things are going to be more intelligent than us.”
ChatGPT is going to change education, not destroy it
The narrative around cheating students doesn’t tell the whole story. Meet the teachers who think generative AI could actually make learning better.
Meet the people who use Notion to plan their whole lives
The workplace tool’s appeal extends far beyond organizing work projects. Many users find it’s just as useful for managing their free time.
Learning to code isn’t enough
Historically, learn-to-code efforts have provided opportunities for the few, but new efforts are aiming to be inclusive.
Get the latest updates from
MIT Technology Review
Discover special offers, top stories, upcoming events, and more.