  Noise is an inherent part of neuronal dynamics, and thus of the brain. It can
be observed in neuronal activity at different spatiotemporal scales, including
in neuronal membrane potentials, local field potentials,
electroencephalography, and magnetoencephalography. A central research topic in
contemporary neuroscience is to elucidate the functional role of noise in
neuronal information processing. Experimental studies have shown that a
suitable level of noise may enhance the detection of weak neuronal signals by
means of stochastic resonance. In response, theoretical research, based on the
theory of stochastic processes, nonlinear dynamics, and statistical physics,
has made great strides in elucidating the mechanism and the many benefits of
stochastic resonance in neuronal systems. In this perspective, we review recent
research dedicated to neuronal stochastic resonance in biophysical mathematical
models. We also explore the regulation of neuronal stochastic resonance, and we
outline important open questions and directions for future research. A deeper
understanding of neuronal stochastic resonance may afford us new insights into
the highly impressive information processing in the brain.
