There is rarely time to write about every cool science story that comes our way. So this year we’ve got another special series of Twelve Days of Christmas posts, highlighting a science story that fell through the cracks in 2020, every day from December 25th through January 5th. Today: Experiments in synchronization in a network of violin players showed that people can drown out distractions and miscommunication, in order to stay in sync.
An unusual experiment in which 16 violinists tried to synchronize their playing while wearing noise-cancelling headphones yielded some intriguing results, according to an August 2020 paper published in Nature Communications. The study concluded that human networks are fundamentally different from other networks in terms of synchronized behavior because of our ability to make decisions. This could lead to better models for complex human behaviour, with applications in fields as diverse as economics, epidemiology, politics, traffic management and the dissemination of misinformation.
There have been previous studies on synchronization in human behavior, particularly with regard to bridge dynamics. For example, as we reported before, people walking on a bridge that begins to shift will instinctively adjust their stride to accommodate the swinging motion of the bridge as it swings sideways. This will be familiar to anyone who has tried to walk on a fast-moving train and had to find a foothold as the train wobbled back and forth. But a bridge exacerbates the problem, giving rise to extra small lateral oscillations that amplify the sway. The result is a positive feedback loop (the technical term is “synchronous lateral excitation”).
Provide a large enough crowd to adjust their stride to the movement of the bridge, and the swaying can become dangerously violent, as happened with the Millennium Bridge when it first opened in June 2000. About 90,000 people crossed the bridge on the opening day, with about 2,000 people at any one time, and the crowd’s movement triggered significant shaking and swaying.
Over time, the pedestrians unintentionally became involved, causing the bridge to wobble even more. The spontaneous synchrony of the crowd was similar to what happens with the highly synchronized flashes of fireflies or the firing of neurons in the brain. Londoners nicknamed it ‘Wobbly Bridge’. Officials sealed it off after just two days, and the bridge remained closed for the next two years until the necessary adjustments could be made to stop the swinging.
The phenomenon has also been observed among stock brokers, according to a 2011 study that found that traders’ daily instant messaging patterns are closely related to their level of synchronous trading. Conclusion: “The higher the traders’ synchronous trading, the less likely they are to lose money at the end of the day,” the authors wrote. Cornell University applied mathematician Steven Strogatz has performed synchronization experiments with crickets in soundproof boxes.
Moti Fridman – a physicist at Bar-Ilan University in Israel and a co-author of the paper on violin players – has also long been interested in synchronization, having published studies on synchronized large laser networks and, on a smaller scale, the unusual coupling which explains why rubbing the rim of one wine glass produces a tone and causes vibrations in other wine glasses. For the violin studies, he worked with Elad Shniderman, a music graduate student at Stony Brook University in New York, as well as colleagues from Bar-Ilan and the Weizman Institute of Science.
Previous studies have largely dealt with simple networks where each person (or node) is connected to every other person. In a more complex network, the number of connections between each person can vary, and there can also be delayed messages between them that can prevent the transition to a synchronized state. as Fridman et al† wrote in their paper, “Research on network links or linkage has mainly focused on all-to-do linking, while current social networking and human interactions often rely on complex linkage configurations.”
The participating violinists put on noise-cancelling headphones and began to play the same musical phrase repeatedly, without looking at or listening to the other players. They could only rely on what they heard through the headphones, which were connected to a computer system. The researchers then introduced intermittent delays in signals between paired violinists, varying the delays and combinations of violinists. It’s called a “frustrated situation” and most network models assume that in such a frustrated condition, each node will try to find a middle ground between all the different inputs.
Instead, Fridman et al† found that the players responded by adjusting their playing, speeding up or slowing down their tempo to better synchronize with their fellow violinists. “Human networks behave differently than any other network we’ve ever measured,” Fridman told The Jerusalem Post. “In a state of frustration, they don’t look for a ‘middle’, but ignore one of the inputs. This is a critical phenomenon that changes the dynamics of the network. Human networks are able to change their inner structure in order to a better solution than is possible in existing models.”
It’s similar to a phenomenon known as the ‘cocktail party effect’: people’s ability to discern one conversation thread amid a cacophony of chatter in a crowded room. But the effect has so far not been included in studies of network synchronization. The next step is to conduct the experiment online, trying to synchronize hundreds and thousands of violinists over the internet.
Building better models of complex human behavior would have implications for a wide range of areas, such as better controlling epidemics – something of particular concern today given the ongoing coronavirus pandemic – and preventing the spread of false information. through social media (“fake news”) . “Our results are also related to any network where every node in the network has decision-making power, such as autonomous cars, or introducing AI into our highly connected world,” Fridman told Inside Science. “Our model can predict the dynamics of such systems with high accuracy, more than was previously possible.”
DOI: Nature Communications, 2020. 10.1038/s41467-020-17540-7 (About DOIs).
List image by Chen Damari