Synopsis: A rosy outlook on pink noise

The reasons why complex systems like neuronal networks process some signals better than others might be buried in the noise.
Synopsis figure
Illustration:Carin Cain

Frequency filters on radio receivers are engineered to block noise and deliver a clear and crisp sounding tune. Similarly, humans and animals may have adapted their sensory hardware so as to optimally process signals, such as loudness or changes in brightness, with certain noise characteristics.

In a paper appearing in Physical Review Letters, Gerardo Aquino at Dresden’s Max-Planck Institute for the Physics of Complex Systems, in collaboration with scientists at the University of North Texas and Duke University, US, outline an idea that explains why complex systems, like neuronal networks, seem to most efficiently process information that carries 1/f noise. Unlike “white” noise, which is equally powerful at all frequencies, the intensity of 1/f, or “pink” noise, drops in half when the frequency is doubled.

A simplifying assumption when dealing with out-of-equilibrium systems is that they obey linear-response theory: the response of the system depends linearly on the input (at least when the input and response are broken down into frequencies). But some complex systems don’t appear to follow linear response theory. Aquino et al. connect this observation with the idea that a complex system responds best to a complex input. Within this framework, complex systems transfer information characterized by 1/f noise more optimally than other signals.

While primarily a mathematical work, Aquino et al. suggest their hypothesis could be tested in experiments that probe fluctuations in the structure of liquid crystals. – Jessica Thomas


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