The term noise usually describes undesirable disturbances or fluctuations, and is considered to be the “fundamental enemy” ( McDonnell and Abbott, 2009) for communication and error-free information transmission and processing in engineering. This surprising result indicates that intrinsic noise might not only play a crucial role in human auditory processing, but might even be beneficial for contemporary machine learning approaches. Remarkably, speech recognition after hearing loss actually improves with additional intrinsic noise. We simulate different levels of hearing loss and investigate the effect of intrinsic noise. Here we present a computational model of the auditory pathway based on a deep neural network, trained on speech recognition. Especially within the auditory system, recent studies suggest that intrinsic noise plays a key role in signal processing and might even correspond to increased spontaneous neuronal firing rates observed in early processing stages of the auditory brain stem and cortex after hearing loss. However, in the context of stochastic resonance, noise has been shown to improve signal detection of weak sub- threshold signals, and it has been proposed that the brain might actively exploit this phenomenon. Noise is generally considered to harm information processing performance. 7Linguistics Lab, Friedrich-Alexander-University Erlangen-Nuremberg (FAU), Erlangen, Germany.6Pattern Recognition Lab, Friedrich-Alexander-University Erlangen-Nuremberg (FAU), Erlangen, Germany.5Friedrich-Alexander-University Erlangen-Nuremberg (FAU), Erlangen, Germany.4Department of Physics and Center for Vision Research, York University, Toronto, ON, Canada.3Cognitive Computational Neuroscience Group, Friedrich-Alexander-University Erlangen-Nuremberg (FAU), Erlangen, Germany.2Neuroscience Lab, University Hospital Erlangen, Erlangen, Germany.1Laboratory of Sensory and Cognitive Neuroscience, Aix-Marseille University, Marseille, France. ![]() Achim Schilling 1,2,3*, Richard Gerum 4, Claus Metzner 2,5, Andreas Maier 6 and Patrick Krauss 2,3,6,7
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