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Schilling A, Gerum R, Metzner C, Maier A, Krauss P. Intrinsic Noise Improves Speech Recognition in a Computational Model of the Auditory Pathway. Front Neurosci 2022; 16:908330. [PMID: 35757533 PMCID: PMC9215117 DOI: 10.3389/fnins.2022.908330] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 05/09/2022] [Indexed: 01/05/2023] Open
Abstract
Noise is generally considered to harm information processing performance. 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. 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. Here we present a computational model of the auditory pathway based on a deep neural network, trained on speech recognition. We simulate different levels of hearing loss and investigate the effect of intrinsic noise. Remarkably, speech recognition after hearing loss actually improves with additional intrinsic noise. 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.
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Affiliation(s)
- Achim Schilling
- Laboratory of Sensory and Cognitive Neuroscience, Aix-Marseille University, Marseille, France
- Neuroscience Lab, University Hospital Erlangen, Erlangen, Germany
- Cognitive Computational Neuroscience Group, Friedrich-Alexander-University Erlangen-Nuremberg (FAU), Erlangen, Germany
| | - Richard Gerum
- Department of Physics and Center for Vision Research, York University, Toronto, ON, Canada
| | - Claus Metzner
- Neuroscience Lab, University Hospital Erlangen, Erlangen, Germany
- Friedrich-Alexander-University Erlangen-Nuremberg (FAU), Erlangen, Germany
| | - Andreas Maier
- Pattern Recognition Lab, Friedrich-Alexander-University Erlangen-Nuremberg (FAU), Erlangen, Germany
| | - Patrick Krauss
- Neuroscience Lab, University Hospital Erlangen, Erlangen, Germany
- Cognitive Computational Neuroscience Group, Friedrich-Alexander-University Erlangen-Nuremberg (FAU), Erlangen, Germany
- Pattern Recognition Lab, Friedrich-Alexander-University Erlangen-Nuremberg (FAU), Erlangen, Germany
- Linguistics Lab, Friedrich-Alexander-University Erlangen-Nuremberg (FAU), Erlangen, Germany
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Tziridis K, Brunner S, Schilling A, Krauss P, Schulze H. Spectrally Matched Near-Threshold Noise for Subjective Tinnitus Loudness Attenuation Based on Stochastic Resonance. Front Neurosci 2022; 16:831581. [PMID: 35431789 PMCID: PMC9005796 DOI: 10.3389/fnins.2022.831581] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Accepted: 02/23/2022] [Indexed: 12/29/2022] Open
Abstract
Recently, we proposed a model of tinnitus development based on a physiological mechanism of permanent optimization of information transfer from the auditory periphery to the central nervous system by means of neuronal stochastic resonance utilizing neuronal noise to be added to the cochlear input, thereby improving hearing thresholds. In this view, tinnitus is a byproduct of this added neuronal activity. Interestingly, in healthy subjects auditory thresholds can also be improved by adding external, near-threshold acoustic noise. Based on these two findings and a pilot study we hypostatized that tinnitus loudness (TL) might be reduced, if the internally generated neuronal noise is substituted by externally provided individually adapted acoustic noise. In the present study, we extended the data base of the first pilot and further optimized our approach using a more fine-grained adaptation of the presented noise to the patients' audiometric data. We presented different spectrally filtered near-threshold noises (-2 dB to +6 dB HL, 2 dB steps) for 40 s each to 24 patients with tonal tinnitus and a hearing deficit not exceeding 40 dB. After each presentation, the effect of the noise on the perceived TL was obtained by patient's response to a 5-scale question. In 21 out of 24 patients (13 women) TL was successfully subjectively attenuated during acoustic near-threshold stimulation using noise spectrally centered half an octave below the individual's tinnitus pitch (TP). Six patients reported complete subjective silencing of their tinnitus percept during stimulation. Acoustic noise is able to reduce TL, but the TP has to be taken into account. Based on our findings, we speculate about a possible future treatment of tinnitus by near-threshold bandpass filtered acoustic noise stimulation, which could be implemented in hearing aids with noise generators.
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Affiliation(s)
| | | | | | | | - Holger Schulze
- Experimental Otolaryngology, University of Erlangen-Nuremberg, Erlangen, Germany
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Schilling A, Tziridis K, Schulze H, Krauss P. The stochastic resonance model of auditory perception: A unified explanation of tinnitus development, Zwicker tone illusion, and residual inhibition. PROGRESS IN BRAIN RESEARCH 2021; 262:139-157. [PMID: 33931176 DOI: 10.1016/bs.pbr.2021.01.025] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Stochastic resonance (SR) has been proposed to play a major role in auditory perception, and to maintain optimal information transmission from the cochlea to the auditory system. By this, the auditory system could adapt to changes of the auditory input at second or even sub-second timescales. In case of reduced auditory input, somatosensory projections to the dorsal cochlear nucleus would be disinhibited in order to improve hearing thresholds by means of SR. As a side effect, the increased somatosensory input corresponding to the observed tinnitus-associated neuronal hyperactivity is then perceived as tinnitus. In addition, the model can also explain transient phantom tone perceptions occurring after ear plugging, or the Zwicker tone illusion. Vice versa, the model predicts that via stimulation with acoustic noise, SR would not be needed to optimize information transmission, and hence somatosensory noise would be tuned down, resulting in a transient vanishing of tinnitus, an effect referred to as residual inhibition.
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Affiliation(s)
- Achim Schilling
- Neuroscience Lab, Experimental Otolaryngology, University Hospital Erlangen, Erlangen, Germany; Cognitive Computational Neuroscience Group at the Chair of English Philology and Linguistics, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Konstantin Tziridis
- Neuroscience Lab, Experimental Otolaryngology, University Hospital Erlangen, Erlangen, Germany
| | - Holger Schulze
- Neuroscience Lab, Experimental Otolaryngology, University Hospital Erlangen, Erlangen, Germany
| | - Patrick Krauss
- Neuroscience Lab, Experimental Otolaryngology, University Hospital Erlangen, Erlangen, Germany; Cognitive Computational Neuroscience Group at the Chair of English Philology and Linguistics, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Erlangen, Germany; FAU Linguistics Lab, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Erlangen, Germany; Department of Otorhinolaryngology/Head and Neck Surgery, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
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Abstract
Power spectra of spike trains reveal important properties of neuronal behavior. They exhibit several peaks, whose shape and position depend on applied stimuli and intrinsic biophysical properties, such as input current density and channel noise. The position of the spectral peaks in the frequency domain is not straightforwardly predictable from statistical averages of the interspike intervals, especially when stochastic behavior prevails. In this work, we provide a model for the neuronal power spectrum, obtained from Discrete Fourier Transform and expressed as a series of expected value of sinusoidal terms. The first term of the series allows us to estimate the frequencies of the spectral peaks to a maximum error of a few Hz, and to interpret why they are not harmonics of the first peak frequency. Thus, the simple expression of the proposed power spectral density (PSD) model makes it a powerful interpretative tool of PSD shape, and also useful for neurophysiological studies aimed at extracting information on neuronal behavior from spike train spectra.
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Krauss P, Tziridis K, Schilling A, Schulze H. Cross-Modal Stochastic Resonance as a Universal Principle to Enhance Sensory Processing. Front Neurosci 2018; 12:578. [PMID: 30186104 PMCID: PMC6110899 DOI: 10.3389/fnins.2018.00578] [Citation(s) in RCA: 39] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2018] [Accepted: 07/30/2018] [Indexed: 11/13/2022] Open
Affiliation(s)
- Patrick Krauss
- Department of Otorhinolaryngology, Head and Neck Surgery, Experimental Otolaryngology, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany
| | - Konstantin Tziridis
- Department of Otorhinolaryngology, Head and Neck Surgery, Experimental Otolaryngology, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany
| | - Achim Schilling
- Department of Otorhinolaryngology, Head and Neck Surgery, Experimental Otolaryngology, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany
| | - Holger Schulze
- Department of Otorhinolaryngology, Head and Neck Surgery, Experimental Otolaryngology, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany
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Krauss P, Metzner C, Schilling A, Schütz C, Tziridis K, Fabry B, Schulze H. Adaptive stochastic resonance for unknown and variable input signals. Sci Rep 2017; 7:2450. [PMID: 28550314 PMCID: PMC5446399 DOI: 10.1038/s41598-017-02644-w] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2017] [Accepted: 04/19/2017] [Indexed: 11/09/2022] Open
Abstract
All sensors have a threshold, defined by the smallest signal amplitude that can be detected. The detection of sub-threshold signals, however, is possible by using the principle of stochastic resonance, where noise is added to the input signal so that it randomly exceeds the sensor threshold. The choice of an optimal noise level that maximizes the mutual information between sensor input and output, however, requires knowledge of the input signal, which is not available in most practical applications. Here we demonstrate that the autocorrelation of the sensor output alone is sufficient to find this optimal noise level. Furthermore, we demonstrate numerically and analytically the equivalence of the traditional mutual information approach and our autocorrelation approach for a range of model systems. We furthermore show how the level of added noise can be continuously adapted even to highly variable, unknown input signals via a feedback loop. Finally, we present evidence that adaptive stochastic resonance based on the autocorrelation of the sensor output may be a fundamental principle in neuronal systems.
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Affiliation(s)
- Patrick Krauss
- Department of Otorhinolaryngology, University Erlangen, Nürnberg, Germany.,Department of Physics, University Erlangen, Nürnberg, Germany
| | - Claus Metzner
- Department of Physics, University Erlangen, Nürnberg, Germany
| | - Achim Schilling
- Department of Otorhinolaryngology, University Erlangen, Nürnberg, Germany.,Department of Physics, University Erlangen, Nürnberg, Germany
| | - Christian Schütz
- Department of Otorhinolaryngology, University Erlangen, Nürnberg, Germany
| | | | - Ben Fabry
- Department of Physics, University Erlangen, Nürnberg, Germany
| | - Holger Schulze
- Department of Otorhinolaryngology, University Erlangen, Nürnberg, Germany.
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Krauss P, Tziridis K, Metzner C, Schilling A, Hoppe U, Schulze H. Stochastic Resonance Controlled Upregulation of Internal Noise after Hearing Loss as a Putative Cause of Tinnitus-Related Neuronal Hyperactivity. Front Neurosci 2016; 10:597. [PMID: 28082861 PMCID: PMC5187388 DOI: 10.3389/fnins.2016.00597] [Citation(s) in RCA: 60] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2016] [Accepted: 12/14/2016] [Indexed: 11/25/2022] Open
Abstract
Subjective tinnitus is generally assumed to be a consequence of hearing loss. In animal studies it has been demonstrated that acoustic trauma induced cochlear damage can lead to behavioral signs of tinnitus. In addition it was shown that noise trauma may lead to deafferentation of cochlear inner hair cells (IHC) even in the absence of elevated hearing thresholds, and it seems conceivable that such hidden hearing loss may be sufficient to cause tinnitus. Numerous studies have indicated that tinnitus is correlated with pathologically increased spontaneous firing rates and hyperactivity of neurons along the auditory pathway. It has been proposed that this hyperactivity is the consequence of a mechanism aiming to compensate for reduced input to the auditory system by increasing central neuronal gain, a mechanism referred to as homeostatic plasticity (HP), thereby maintaining mean firing rates over longer timescales for stabilization of neuronal processing. Here we propose an alternative, new interpretation of tinnitus-related development of neuronal hyperactivity in terms of information theory. In particular, we suggest that stochastic resonance (SR) plays a key role in both short- and long-term plasticity within the auditory system and that SR is the primary cause of neuronal hyperactivity and tinnitus. We argue that following hearing loss, SR serves to lift signals above the increased neuronal thresholds, thereby partly compensating for the hearing loss. In our model, the increased amount of internal noise-which is crucial for SR to work-corresponds to neuronal hyperactivity which subsequently causes neuronal plasticity along the auditory pathway and finally may lead to the development of a phantom percept, i.e., subjective tinnitus. We demonstrate the plausibility of our hypothesis using a computational model and provide exemplary findings in human patients that are consistent with that model. Finally we discuss the observed asymmetry in human tinnitus pitch distribution as a consequence of asymmetry of the distribution of auditory nerve type I fibers along the cochlea in the context of our model.
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Affiliation(s)
- Patrick Krauss
- Experimental Otolaryngology, ENT-Hospital, Head and Neck Surgery, Friedrich-Alexander University Erlangen-NürnbergErlangen, Germany
- Biophysics Group, Department of Physics, Center for Medical Physics and Technology, Friedrich-Alexander University Erlangen-NürnbergErlangen, Germany
| | - Konstantin Tziridis
- Experimental Otolaryngology, ENT-Hospital, Head and Neck Surgery, Friedrich-Alexander University Erlangen-NürnbergErlangen, Germany
| | - Claus Metzner
- Biophysics Group, Department of Physics, Center for Medical Physics and Technology, Friedrich-Alexander University Erlangen-NürnbergErlangen, Germany
| | - Achim Schilling
- Experimental Otolaryngology, ENT-Hospital, Head and Neck Surgery, Friedrich-Alexander University Erlangen-NürnbergErlangen, Germany
- Biophysics Group, Department of Physics, Center for Medical Physics and Technology, Friedrich-Alexander University Erlangen-NürnbergErlangen, Germany
| | - Ulrich Hoppe
- Department of Audiology, ENT-Hospital, Head and Neck Surgery, Friedrich-Alexander University Erlangen-NürnbergErlangen, Germany
| | - Holger Schulze
- Experimental Otolaryngology, ENT-Hospital, Head and Neck Surgery, Friedrich-Alexander University Erlangen-NürnbergErlangen, Germany
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