The benefits of noise in neural systems: bridging theory and experiment

By Mark D. McDonnell, Lawrence M. Ward. Nature Reviews Neuroscience, 2011

742 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Molecular Biology, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/ea56342c53d4cb8f5be57a90471f7edce5fda30b

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cognitive Neuroscience

1. Bahram Zonooz
2. Elahe Arani
3. Fahad Sarfraz
4. Wolfgang Maass
5. Nienke E. R. van Bueren
6. S. V. D. van der Ven
7. Roi Cohen Kadosh
8. J. Urgen Schmidhuber

In Molecular Biology

1. Wolfgang Maass

In Statistical and Nonlinear Physics

1. Wolfgang Maass
2. Bahram Zonooz
3. Elahe Arani

Citations in the corpus

• Noise as a Resource for Computation and Learning in Networks of Spiking Neurons (2014, background): “It has already been proposed a while ago that noise is beneficial for the detection of weak signals by neurons (‘‘stochastic resonance’’; see the review in [10]).”
• Noise as a Resource for Learning in Knowledge Distillation (2020, background): “Recently, though, there has been a shift in neuroscience and a number of studies argue for the beneficial role of noise [13, 35, 37].”
• Human neuronal excitation/inhibition balance explains and predicts neurostimulation induced learning benefits (2023, background): “However, we should note that the mechanism of stochastic resonance is difficult, if not impossible, to prove in the human brain due to the complexity of biological processes (McDonnell & Abbott, 2009; Mcdonnell & Ward, 2011).”