Brandeis Magazine

Picture this: A photo of a scruffy bearded dude wearing a plaid shirt, part of an MIT Technology Review story about “the hipster effect,” an abstruse mathematical concept that explains why, paradoxically, anti-conformists often look alike.

A reader recognizes himself in the photo and threatens to sue MIT for using his image without his permission. As it happens, the photo is a stock image of a model, not a photo of that reader. The contretemps offered a confirmation most mathematicians, who struggle to describe their work in layperson’s terms, could only dream of: The irate anti-conformist resembled the photographed anti-conformist so much, he actually thought he was him.

The hipster effect is a mathematical concept that appears in statistical physics, neuroscience, finance and other areas. It deals with populations — of atoms, neurons, people or systems, for instance — composed of conformists, who follow the majority, and anti-conformists, who go in the opposite direction. The paradox is that the anti-conformists end up making similar choices, thus conforming within their group. Then they oppose the trend they created and oscillate in unison among other choices. What remains true throughout this process is that anti-conformists tend to look the same and make the same choices.

Jonathan Touboul, associate professor of mathematics, wrote an article titled “The Hipster Effect: When Anti-Conformists All Look the Same,” which will appear in a forthcoming journal of the American Institute of Mathematical Sciences. Of course, he isn’t studying hipsters per se, though he finds the culture fascinating. An applied mathematician (who’s helping to develop Brandeis’ new applied mathematics major), Touboul is interested in how mathematics describes the real world as well as how metaphors can be used to describe mathematical phenomena.

The hipster effect has implications for decoding scientific, economic and financial phenomena, he says — for example, when individuals take positions in opposition to a majority, such as selling stocks when most people are buying.

In particular, Touboul wants to use mathematics to understand biological systems, especially the interplay of neuron structure and function. “If you look at large networks of neurons in the brain,” he says, “each neuron has a level of randomness, but they manage to finely synchronize, generating brain rhythms associated with physiological functions such as memory or attention.”

Disruptions in synchrony are seen in such conditions as epilepsy, Alzheimer’s and Parkinson’s disease. Touboul is currently collaborating with biologists and neurosurgeons to model neuronal networks that synchronize abnormally in Parkinson’s to better understand a treatment called deep brain stimulation.

Understanding when neurons synchronize may help physicians fine-tune the timing and frequency at which they stimulate the brain. In turn, this knowledge might help researchers develop new therapies that don’t rely on invasive deep-brain electrodes.

— Laura Gardner