Working group explores how living circuits work and evolve
Think of circuits, and you think of tiny resistors, transistors, and wires. But circuits are found in biology too: from genes to neurons to social interactions, living circuits crunch data to produce new outputs.
This week, a group of experts is meeting at SFI to explore not just how biological circuits work, but also how they evolve.
The “low bar” is to share methods among researchers who study various kinds of biological circuits, says SFI Professor Jessica Flack, who is co-organizing the event. “The high bar is the discovery of common principles of computation in biological systems and an understanding of how these principles influence the evolution of phenotypic traits and social structures,” she says.
To get a sense for what biological circuits look like, consider fights among monkeys, a model system of longstanding interest to Flack and her colleagues. Each monkey is a component of the circuit, and monkeys are connected by their strategies – for instance, whether Monkey A is more or less likely to join a fight if Monkey B is already in the mix.
So-called “gates” take all of that information and compute outcomes, such as the optimal fight size – if fights are too small, they accomplish nothing, but if they get too big, conflict can spin out of control and destabilize the society.
What’s more, circuits can be understood at different levels of abstraction, so that a gate’s outputs could serve as the inputs to a different, more macroscopic circuit, just like small circuits can be built into larger electronic devices such as stereos or computers.
The working group’s first aim is to share ideas and methods for studying biological circuits – especially gene regulatory networks, neural circuits in the brain, and social circuits (like the monkey example).
But the larger goal is to understand circuit evolution. To start with, the team will try to understand the time and spatial scales characteristic of different circuits, as well as which of a circuit’s features have the most impact on outcomes – those features, Flack says, “will give us a starting point for thinking about what properties of the circuits could be targets for natural selection to act on.”
In addition to biological perspectives, the working group will look to statistical physics and information theory to work it all out, Flack says. Once they make progress, the group’s members hope to produce a special issue of Philosophical Transactions of the Royal Society.