Observe around you, and you’ll notice it everywhere: the manner in which trees develop branches, how cities segment into neighborhoods, and the way the brain arranges itself into regions. Nature favors modularity — a finite amount of self-sufficient units that assemble in various configurations to carry out numerous functions. But how does this arrangement come into existence? Does it adhere to a precise genetic outline, or can these formations arise autonomously?
A recent investigation by MIT Professor Ila Fiete indicates an unexpected response.
In results published on Feb. 18 in Nature, Fiete, an associate researcher at the McGovern Institute for Brain Research and the head of the K. Lisa Yang Integrative Computational Neuroscience (ICoN) Center at MIT, reveals that a mathematical model referred to as peak selection can elucidate how modules develop without stringent genetic guidelines. The findings from her team, applicable to both brain systems and ecosystems, provide insight into how modularity manifests throughout nature, irrespective of the scale.
Integrating two major concepts
“Researchers have pondered how modular structures come into being. One theory proposes that various genes are activated at different sites to initiate or conclude a structure. This illustrates how insect embryos form body segments, with genes activating or deactivating at specific concentrations of a smooth chemical gradient within the insect egg,” explains Fiete, the lead author of the paper. Mikail Khona PhD ’25, a previous graduate student and K. Lisa Yang ICoN Center graduate fellow, along with postdoc Sarthak Chandra, also contributed to the study.
Another concept, inspired by mathematician Alan Turing, posits that a structure can arise from competition — small-scale interactions might generate repeating patterns, similar to the spots on a cheetah or the ripples found in sand dunes.
Both hypotheses are effective in certain contexts but prove inadequate in others. The latest research indicates that nature may not need to choose one method over another. The authors suggest a straightforward mathematical concept known as peak selection, illustrating that when a smooth gradient is combined with local interactions that are competitive, modular structures can spontaneously develop. “Thus, biological systems can arrange themselves into distinct modules without detailed direction from above,” states Chandra.
Modular structures within the brain
The researchers explored their thesis on grid cells, which play an essential role in spatial navigation as well as the encoding of episodic memories. Grid cells activate in a repetitive triangular pattern as animals navigate space, yet they do not all function at the same scale — they are arranged into unique modules, each responsible for mapping space at slightly varied resolutions.
The formation of these modules remains a mystery, but Fiete’s model indicates that gradual shifts in cellular characteristics along one dimension of the brain, in conjunction with local neural interactions, could account for the complete structure. The grid cells naturally categorize themselves into distinct groups with clear separations, without external guides or genetic programs dictating their positioning. “Our research elucidates how grid cell modules may arise. The explanation leans toward the possibility of self-organization. It predicts that there might not exist a gene or intrinsic cellular property that triggers a shift when the grid cell scale transitions to another module,” observes Khona.
Modular structures in nature
The very same principle extends beyond neuroscience. Envision a terrain where temperatures and rainfall fluctuate gradually throughout an area. You might expect species to be distributed, and to vary, smoothly across this expanse. However, in reality, ecosystems frequently form species clusters with sharp borders — distinct ecological “neighborhoods” that do not overlap.
Fiete’s research hints at the reason: local competition, cooperation, and predation among species interact with global environmental gradients to generate natural separations, even when the underlying conditions shift gradually. This phenomenon can be accounted for using peak selection — implying that the same principle that shapes brain circuits may also influence forests and oceans.
A self-organizing environment
One of the researchers’ most remarkable discoveries is that modularity in these systems is notably resilient. Alter the system’s size, and the number of modules remains constant — they merely scale up or down. This implies that a mouse brain and a human brain could utilize the same fundamental principles to develop their navigation circuits, albeit at different sizes.
The model also generates testable predictions. If accurate, grid cell modules should adhere to straightforward spacing ratios. In ecosystems, the distribution of species ought to form distinct clusters even in the absence of abrupt environmental changes.
Fiete highlights that their findings contribute an additional conceptual framework to biology. “Peak selection can guide future investigations, not only in grid cell studies but throughout developmental biology.”