If we as humans can understand how fireflies in swarms synchronize, we can understand their communication more deeply. Their on-off flickers of light are more similar to our binary computational logic than the tremulous variations of a frog croak or pitches of bugling elk calls.
Fireflies' elegant, distributed communication systems could eventually help us with our own telecommunications through new ideas about compressing information and distributed networks.
Assistant Professor of computer science Orit Peleg has just received $900,000 over the next five years to learn how fireflies in a swarm synchronize their lighting displays. The funding was provided by a National Science Foundation CAREER award, a highly prestigious early-career grant for junior faculty members.
Peleg, a member of the Biofrontiers Institute and Department of Computer Science, seeks to create testable theories about animal communication with her lab by merging tools from physics, biology, math and computer science.
Female fireflies judge the blinking displays of males to determine their mate. When there are swarms of small, blinking insects that can stretch over miles in the dark, any way to cut down on the visual clutter is important, and this is where synchronizing their flash patterns comes together.
"There are some really interesting questions about how really similar signals on the level of individual fireflies can result in a different collective signal," Peleg said.
Some groups of fireflies begin to flash in a burst together and stop the burst together, while others flash in a matching pattern but offset in time from one another so that the overall swarm always has some members flashing.
Currently our telecommunication networks and other manmade technology require synchronization to a central clock, which means that the network is really sensitive to failures of that clock.
"But that's not how biology does it. Biology achieves synchronization in a distributed way, which is more robust to failures of individual nodes," Peleg said
Changing the Working Model
We currently describe fireflies' brilliant displays of synchronizing bioluminescence through mathematical models that don't fully account for the possible agency of fireflies to change their lighting patterns in response to other fireflies.
The models are also tied to limited experimental data, giving Peleg and her lab rich ground for research and experimentation.
In the field, the lab sets up dark tents in the middle of the firefly swarms. They bring fireflies inside and use LED lights to mimic their signal patterns. They've already seen that, by changing the LED flashes, they can change the responses of living fireflies.
"They kind of treat it as if it were another firefly. It's really fun to watch how the firefly responds and communicates back to the artificial light," Peleg said.
They have also had success in training fireflies to create light patterns they have never been observed making in the wild in response to the LED light's patterns.
Outside of the carefully controlled environment in the tent, the lab will also use low-cost video equipment throughout the swarms to create robust 3-D video that can be analyzed and turned into 3D models that match the observed behavior of the fireflies.
By creating a model from field-data, Peleg can create more testable and verifiable theories around the ways that fireflies manage their synchronization.
The field data can be used to create simulations of firefly lighting patterns where the actions of real fireflies placed in the system impact the response of the program's lights, which involves advanced image processing and hardware.
In addition, Peleg is excited to use the data created from these field recordings to offer a class called "Physics, Artificial Intelligence, and Generative Art of Agent-Based Models," where undergraduate and graduate students will be able to craft their own visualizations of the data captured by the cameras in the field. By bringing experiential learning to the forefront, Peleg hopes to support their joy of learning.