Around the turn of the 20th century, a Spanish neuroscientist named Santiago Ramón y Cajal created intricate images of intertwined neurons that changed brain science forever. His exquisite illustrations helped scientists understand some fundamental facts about the brain, namely that long-armed neurons—communicating over gaps called synapses—are the basic unit of our nervous system.
Now, a team of scientists has created a new system for imaging and analyzing neurons on a much finer scale, one they hope will produce insights into everything from developing brains to devastating mental disorders.
Details of the system, as well as their analysis of a sliver of mouse cortex, were published in the journal Cell.
“The complexity of the brain is much more than what we had ever imagined,” says study first author Narayanan “Bobby” Kasthuri, a Boston University School of Medicine assistant professor of anatomy and neurobiology, who coauthored the Cell paper with Jeff Lichtman of Harvard University. “We had this clean idea of how there’s a really nice order to how neurons connect with each other, but if you actually look at the material it’s not like that.”
The work overturns a longstanding assumption, known as “Peter’s Rule,” that if two neurons are close to each other, they are likely to form synapses that allow them to communicate. It seems logical, but, Kasthuri learned, it turns out to be false, at least in this particular part of mouse brain, a piece of cortex that receives sensory information from whiskers.
“Just because two neurons spend a lot of time together doesn’t mean they make a connection,” says Kasthuri. “Now, that’s the rule for this part of the brain in an adult mammal. It could be that in different parts of the brain, or in a baby’s brain, every neuron is connecting to its neighbors. That’s why we want to do this imaging in other brains and in a baby’s brain—that’s how we’ll figure this out.”
How the system works
The imaging system contains both hardware, which slices and photographs brain samples, and software that analyzes the data. The patented hardware, developed by Kasthuri and scientists at Harvard, is called ATUM, for automated tape collecting ultra-microtome.
It uses a diamond knife to cut stained, plasticized samples of brain tissue into 30-nanomenter slices, then collects and photographs the samples with an electron microscope and stores the data.
The scientists used a program called VAST, developed by co-author Daniel Berger of Harvard and the Massachusetts Institute of Technology, to analyze the data, creating vivid color images of neurons at the level of individual synapses.
‘We think it will pay off’
The cost and data storage demands for this research are still high, but the researchers expect expenses to drop over time, just as it has for genome sequencing. To facilitate data sharing, the scientists are partnering with Argonne National Laboratory and hoping to create a national brain laboratory that neuroscientists worldwide can access within the next few years. Kasthuri likens the idea to the Human Genome Project, an undertaking that spawned new insights and technology, but also criticism.
“Some scientists have a fundamental problem with this type of work because it’s not hypothesis-driven,” says Kasthuri. “We want to collect a huge data set and then look for patterns. And we think it will pay off.”
“As long as data is showing you things that are unexpected, then you’re definitely doing the right thing,” says senior study author Lichtman. “And we are certainly far from being out of the surprise element. There’s never a time when we look at this data that we don’t see something that we’ve never seen before.”
Source: Boston University