A new technology developed at MIT enables scientists to label proteins across millions of individual cells in fully intact 3D tissues with unprecedented speed, uniformity, and versatility. Using the technology, a research team was able to richly label large tissue samples in a single day.

Look around, and you’ll see it everywhere: the way trees form branches, the way cities divide into neighborhoods, the way the brain organizes into regions. Nature loves modularity—a limited number of self-contained units that combine in different ways to perform many functions. But how does this organization arise? Does it follow a detailed genetic blueprint, or can these structures emerge on their own? 

A new study from Ila Fiete, a professor of brain and cognitive sciences and director of the K. Lisa Yang Integrative and Computational Neuroscience (ICoN) Center, suggests a surprising answer. In findings published in Nature, Fiete, also an associate investigator at the McGovern Institute for Brain Research, reports that a mathematical model called peak selection can explain how modules emerge without strict genetic instructions. Her team’s findings, which apply to brain systems and ecosystems, help explain how modularity occurs across nature, no matter the scale.

The roundworm C. elegans is a simple animal whose nervous system has exactly 302 neurons. Each of the connections between those neurons has been comprehensively mapped, allowing researchers to study how they work together to generate the animal’s different behaviors.

Steven Flavell, an MIT associate professor of brain and cognitive sciences and investigator with the Picower Institute for Learning and Memory at MIT and the Howard Hughes Medical Institute, uses the worm as a model to study motivated behaviors such as feeding and navigation, in hopes of shedding light on the fundamental mechanisms that may also determine how similar behaviors are controlled in other animals.