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REVIEW 3 major objections 3 minor 39 references

Memristor-Driven Spike Encoding for Fully Implantable Cochlear Implants

T0 review · 3 major / 3 minor · reviewed 2026-08-04 · deepseek-v4-flash

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Pith's one-line read This paper demonstrates that a single sensing channel—a piezo-MEMS cantilever coupled to a VO2 memristor oscillator—converts nanometer-scale mechanical vibrations directly into rate-coded spiking signals in the 100 Hz–1 kHz range, and shape

desk verdict A neat single-channel proof-of-concept that shows real rate-encoding from a MEMS cantilever through a VO2 oscillator, but the headline '10 nm / dB SPL' numbers lean on an unverified actuator calibration and there are no repeated measurements. read the letter →

arxiv 2509.26582 v2 pith:GHYWZ74S submitted 2025-09-30 cond-mat.mes-hall physics.bio-phphysics.med-ph

Tímea Nóra Török , Roland Kövecs , Ferenc Braun , Zsigmond Pollner , Tamás Zeffer , Nguyen Quoc Khánh , László Pósa , Péter Révész
show 4 more authors
Heungsoo Kim Alberto Piqué András Halbritter János Volk
This is my paper
classification cond-mat.mes-hallphysics.bio-phphysics.med-ph
keywords actionpotentialcochlearimplantfrequency-resolvedMEMSarraynanogapmemristorpiezo-MEMSrateencodingtonotopyVO2
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

This paper is trying to establish that a single hardware channel can do what a cochlear implant's front end normally does in software: take a tiny mechanical vibration, pick out its frequency, and encode its loudness as a train of neural-style spikes. The proposed chain is a piezo-MEMS cantilever that resonates at a specific frequency, a rectifier that turns its AC output into a DC level, and a VO2 nanogap memristor oscillator that converts that DC level into current spikes. The authors report spikes between roughly 100 Hz and 1 kHz whose frequency grows with the stimulus amplitude in the nanometer range, matching the rate-encoding behavior of auditory nerve fibers. They also show that adding a parallel inductor-resistor network turns the unipolar spikes into a biphasic waveform, the charge-balanced form required for implant electrodes. If true, this is a direct, energy-lean path to a fully implantable cochlear implant that avoids FFT-based signal processing and its associated power, footprint, and latency costs.

What carries the argument

The load-bearing element is a relaxation oscillator built from a resistor, capacitor, and a vanadium dioxide (VO2) nanogap memristor: a planar device with a 30–60 nm gap between electrodes. The memristor switches between insulating and metallic states through an insulator-metal transition at a threshold voltage, and each switching cycle emits a current spike. The RC values set the baseline spike timescale, while the DC input voltage—which tracks the rectified cantilever signal—tunes the spike rate. The piezo-MEMS cantilever, a spiral-shaped ScAlN resonator with quality factors above 200, supplies the frequency-selective front end by converting a narrow band of mechanical vibration into an AC

What would settle it

Measure the cantilever's real displacement with a laser interferometric vibrometer while sweeping the piezo drive voltage used in the rate-encoding experiment; if the true displacement does not track the nominal 6 nm/V conversion, or the spike-rate versus true-displacement curve is not the reported approximately linear ramp, the central claim is not supported.

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Extended reading notes

Core claim

The paper claims, for the first time, a direct conversion of analog microelectromechanical signals into biomimetic spiking signals. In the key experiment, a piezo-MEMS cantilever with a resonance near 637 Hz is excited mechanically at amplitudes of 26–60 nm, calculated from the actuator's nominal 6 nm/V sensitivity. The cantilever's AC output is amplified, rectified, and smoothed to a DC level that drives a VO2 nanogap memristor relaxation oscillator; the oscillator emits current spikes whose frequency increases approximately linearly with stimulus amplitude, falling in the 100–800 Hz range. Adding a parallel LR circuit converts the unipolar spikes into a biphasic waveform whose numerical in

Load-bearing premise

The claimed nanometer-scale stimulus amplitudes and the rate-encoding curve are computed from the piezoelectric actuator's drive voltage using its nominal 6 nm/V sensitivity; if the actual motion delivered to the cantilever through the mounting differs from that value, the biological-relevance and amplitude-to-rate mapping shift.

Editorial extensions

If this is right

  • A single analog channel can perform frequency-selective sensing and rate-encoding of amplitude without any Fourier transform or digital signal processing.
  • The output spike frequencies land in the biologically relevant 100 Hz–1 kHz auditory nerve range, so the circuit can interface with neural coding schemes directly.
  • The biphasic waveform produced by the added LR network satisfies the charge-balance safety requirement for cochlear implant electrodes.
  • Because the VO2 switching events are orders of magnitude faster than the millisecond-scale target spikes, the spike rate is set by RC parameters and can be tuned to the neural domain.
  • The direct analog path could reduce the roughly 10 ms latency experienced with conventional cochlear implants, which would improve sound localization.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • If the linear rate-encoding curve holds across cantilever channels tuned to different resonance frequencies, the full array would produce a sound spectrogram directly as a spike raster, with no digital filter bank; the paper does not demonstrate multi-channel behavior.
  • The paper routes only the rectified DC signal into the oscillator; coupling the unfiltered AC cantilever signal into the oscillator could add phase-locking, a temporal coding strategy the authors mention as possible but do not test.
  • The nominal 6 nm/V displacement calibration is a single-point assumption; an independent interferometric measurement of the true cantilever displacement during spiking would pin the amplitude scale and directly test the biological-relevance claim.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

3 major / 3 minor

Summary. The manuscript reports a single-channel auditory sensing concept for fully implantable cochlear implants. A piezoelectric ScAlN MEMS cantilever is mechanically excited by a piezo actuator, and its rectified output drives a VO2 nanogap memristor relaxation oscillator. The authors show that changing the nominal drive amplitude changes the oscillator spike rate, claim this rate encoding operates at biologically realistic nanometer-scale displacements and produces auditory-nerve-like rates, and demonstrate that adding a parallel inductor converts the unipolar output into a biphasic waveform suitable for cochlear stimulation. The central claim is an FFT-free, hardware-level conversion from mechanical vibration to rate-coded spikes.

Significance. If the rate-encoding result is robust and the displacement calibration is verified, this is a valuable experimental proof of concept for low-power neuromorphic auditory front ends. The manuscript is careful in describing the VO2 device fabrication and oscillator operation, and the biphasic shaping via a parallel LR circuit is a useful practical contribution. However, the headline quantitative claims—operation at ~10 nm amplitudes, 82–92 dB SPL equivalence, and 100 Hz–1 kHz rate range—are supported by a single device, a nominal actuator calibration, and a limited range of stimulus amplitudes. The concept is interesting, but the evidence as currently presented is not sufficient for the strength of the conclusions.

major comments (3)
  1. [II A and Fig. 7d] The mechanical displacement values S0 and S are not measured; they are calculated from the piezo actuator drive voltage using its nominal 6 nm/V sensitivity, and the Fig. 7d caption states this. Because the cantilever is mounted in a custom holder with PCB and ribbon cables, the actual displacement delivered at 637 Hz could differ systematically. The x-axis of Fig. 7d, the '~10 nm' biological-relevance statement, and the inferred 82–92 dB SPL range all depend on this calibration. I request either a direct measurement of the cantilever displacement under the same experimental conditions (e.g., with the vibrometer already used for Fig. 6b) or a clearly stated uncertainty/transfer-function calibration, and correspondingly hedged claims.
  2. [III B / Fig. 7d] The rate-encoding result is presented as a linear dependence f_osc vs S0, but no error bars, repeated measurements, device-to-device variation, or goodness-of-fit metrics are reported. With a single device and a small number of amplitude steps, the linearity and reproducibility of the encoding are not established. At minimum, the authors should report multiple trials, variability, and a fit with confidence bounds, and state whether the trend is linear or sigmoid-like as claimed.
  3. [Abstract, III B, Conclusion] The stated ranges overstate the demonstrated data. The electromechanical rate-encoding experiment uses S0 = 26–60 nm, not '~10 nm', and the measured spike rates are 100–800 Hz, not '100 Hz–1 kHz'. The abstract and conclusion should be bounded by the measured parameter range, or additional experiments covering ~10 nm and rates up to 1 kHz should be provided.
minor comments (3)
  1. [Fig. 6] Panel (c) is mislabeled as '(e)' in the caption.
  2. [III B] In the list of oscillator parameters, 'resistance states R_HRS, R_HRS' should read 'R_HRS, R_LRS'.
  3. [Introduction] Typos: 'standrad' in the first paragraph and 'Freqency' in Fig. 6b should be corrected.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the central claims are supported by direct measurements; the nominal 6 nm/V displacement calibration is an explicit external assumption, not a circular step.

full rationale

The paper is an experimental characterization rather than a derivation, and its central claims are supported by direct measurements. Frequency-selective cantilever response (Fig. 6), VO2 memristor relaxation oscillation (Fig. 4), spike rate-encoding with f_osc depending on stimulus amplitude (Fig. 7d), and biphasic waveform shaping (Fig. 8) are all observed empirical results, not predictions obtained from a fitted model. The rate-encoding curve in Fig. 7d is an independent measurement of oscillator frequency versus commanded stimulus amplitude, and is not equivalent by construction to any fitted parameter. The displacement values S0 and S are calculated from the piezoelectric actuator's nominal 6 nm/V sensitivity (Section II A and Fig. 7d caption); this is an explicit calibration assumption that could introduce systematic error if the delivered mechanical displacement differs, but it is a risk to external validity and biological-relevance claims, not a circularity, because the spiking output is measured independently and the rate-encoding trend does not reduce to the calibration relation. The self-citations (Refs. 10, 24, 25-29, 30-31) provide fabrication recipes, cantilever designs, and prior characterization of VO2 devices; these are normal citations to the authors' previous published work and are not used as a uniqueness theorem or as a substitute for the present measurements. No equation or parameter in the paper is defined in terms of the quantity it is used to establish, and no fitted input is relabeled as a prediction. Therefore the claim chain is self-contained and no significant circularity is present.

Assumptions & free parameters 3 free parameters · 5 assumptions · 0 invented entities

The central proof-of-concept uses standard circuit components and known device physics; no new theoretical entities are introduced. The main external inputs are the memristor's switching thresholds/resistances, the cantilever resonance, and the actuator calibration. The listed free parameters are standard circuit values chosen by hand to achieve desired timescales; they are not fitted to data in a way that would make the claims circular.

free parameters (3)
  • Oscillator series resistance R = 15 kΩ (audio experiments)
    Chosen by hand to set the oscillation frequency range and load line stability; affects the relationship between input voltage and spike rate.
  • Oscillator parallel capacitance C = 611 nF (audio experiments)
    Chosen to set the RC timescale and thus the oscillation frequency; directly determines the spiking frequency range.
  • Output inductor L = 2.2 mH
    Added in the modified oscillator circuit to shape the unipolar spike waveform into a biphasic signal, as described in Section IIIC.
assumptions (5)
  • domain assumption The VO2 memristor can be modeled as an ideal switch between HRS and LRS with threshold voltages V_set and V_reset, and switching is instantaneous on the ms timescale.
    Section IIB: The oscillator timing is governed by RC time constants; switching timescales (~ps–ns) are cited from Refs. 30-31 as negligible.
  • domain assumption The rectified/smoothed MEMS signal V_DC_MEMS is proportional to the amplitude of the cantilever output and thereby to the mechanical stimulus amplitude.
    Section IIC: The custom-built amplification/rectification electronics are not fully specified, and a linear relationship is assumed.
  • domain assumption The cantilever behaves as a high-Q resonator, so its output at resonance is sinusoidal and its amplitude is proportional to the mechanical stimulus amplitude.
    Section IIIA: The cantilevers have Q>200, but operation at exact resonance and linearity of piezoelectric readout are assumed.
  • ad hoc to paper Nominal actuator displacement equals actual displacement delivered to the cantilever.
    Section IIA: The 6 nm/V sensitivity is taken from the manufacturer, with no in-situ calibration of the mechanical coupling.
  • domain assumption Middle-ear umbo displacement in the 26–60 nm range corresponds to ~82–92 dB SPL (based on Ref. 34).
    Section IIIB: Used to argue biological relevance of the tested amplitudes.

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Cite this review

Pith. "Pith review of Memristor-Driven Spike Encoding for Fully Implantable Cochlear Implants." pith.science (2026). https://pith.science/paper/GHYWZ74S

@misc{pith2026250926582,
  author       = {Pith},
  title        = {Pith review of: Memristor-Driven Spike Encoding for Fully Implantable Cochlear Implants},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/GHYWZ74S}},
  note         = {Machine review of arXiv:2509.26582}
}
abstract

Objective: This work aims to demonstrate a low-power, biomimetic auditory sensing concept for fully implantable cochlear implants. The approach draws inspiration from the frequency selectivity and temporal encoding of the cochlea, and uses neuromorphic spike generation to replace conventional signal processing blocks. The goal is to establish a compact, energy-efficient front-end architecture suitable for future implantable systems. Methods: An auditory sensing unit was implemented, consisting of a piezoelectric MEMS cantilever mechanically coupled to a single VO$_2$ nanogap Mott memristor-based oscillator. This configuration enables FFT-free, frequency-selective sensing and direct spike generation, forming a biomimetic auditory front end. The concept was experimentally examined using controlled mechanical excitation. Results: The sensing unit exhibited frequency-selective detection of mechanical vibrations in the nanometer to tens-of-nanometers displacement range and generated biomimetic spiking waveforms. Spike rate-encoding of the input amplitude was demonstrated, with output spiking frequencies tunable between approximately 100 Hz and 1 kHz depending on the excitation level. The waveform was finally converted to a biphasic shape suitable for cochlear implant stimulation. Significance: Temporal encoding is fundamental to natural auditory signal processing in the nervous system. By implementing this principle through neuromorphic spike encoding, the proposed approach can provide significant benefits for cochlear implants. In addition, the circuit has the potential to reduce footprint, energy consumption, and latencies compared with current commercial solutions.

Figures

Figures reproduced from arXiv: 2509.26582 by the authors.

Figure 1
Figure 1. FIG. 1: Concept of our bio-inspired auditory sensing system. Vi [PITH_FULL_IMAGE:figures/full_fig_p002_1.png] view at source ↗
Figure 2
Figure 2. FIG. 2: Measurement setups for the characterization of piezo-MEMS [PITH_FULL_IMAGE:figures/full_fig_p003_2.png] view at source ↗
Figure 3
Figure 3. FIG. 3: Fabrication and characterization of VO [PITH_FULL_IMAGE:figures/full_fig_p003_3.png] view at source ↗
Figures from the paper (4 more)
Figure 4
Figure 4. Figure 4: FIG. 4: Relaxation oscillator made of a VO [PITH_FULL_IMAGE:figures/full_fig_p004_4.png]
Figure 5
Figure 5. Figure 5: FIG. 5: Circuit schematics of a single channel of the proposed audi [PITH_FULL_IMAGE:figures/full_fig_p004_5.png]
Figure 6
Figure 6. Figure 6: FIG. 6: Characterization of piezo-MEMS cantilevers. (a) Tilt-view [PITH_FULL_IMAGE:figures/full_fig_p005_6.png]
Figure 7
Figure 7. Figure 7: FIG. 7: Results of electromechanical experiments performed on a [PITH_FULL_IMAGE:figures/full_fig_p006_7.png]

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Works this paper leans on

39 extracted references · 4 canonical work pages

  1. [1]

    Zhang, J.-y

    Z.-q. Zhang, J.-y. Li, S.-t. Ge, T.-y. Ma, F.-y. Li, J.-l. Lu, S.-r. Si, Z.-z. Cui, Y.-l. Jin, and X.-h. Jin, Fron- tiers in Public Health11, 1281689 (2024), ISSN 2296- 2565, URLhttps://www.frontiersin.org/articles/ 10.3389/fpubh.2023.1281689/full

    arXiv 2024

  2. [2]

    L. M. Haile, K. Kamenov, P. S. Briant, A. U. Orji, J. D. Steinmetz, A. Abdoli, M. Abdollahi, E. Abu-Gharbieh, A. Afshin, H. Ahmed, et al., The Lancet397, 996 (2021), ISSN 01406736, URLhttps://linkinghub.elsevier. com/retrieve/pii/S014067362100516X

    2021

  3. [3]

    F.-G. Zeng, S. Rebscher, W. Harrison, X. Sun, and H. Feng, IEEE Reviews in Biomedical Engineering1, 115 (2008), ISSN 1937-3333, 1941-1189, URLhttps: //ieeexplore.ieee.org/document/4664429/

    arXiv 2008

  4. [4]

    A. M. Nassiri, D. L. Sorkin, and M. L. Carlson, Otol- ogy & Neurotology43, e558 (2022), ISSN 1531-7129, 1537-4505, URLhttps://journals.lww.com/10.1097/ MAO.0000000000003513

    2022

  5. [5]

    Rosenhall, C

    U. Rosenhall, C. Hederstierna, and E. Idrizbegovic, In- ternational Journal of Audiology50, 578 (2011), ISSN 1499-2027, 1708-8186, URLhttp://www.tandfonline. com/doi/full/10.3109/14992027.2011.580786

    arXiv 2011

  6. [6]

    D. L. Sorkin, Cochlear Implants International14, S12 (2013), ISSN 1467-0100, 1754-7628, URL http://www.tandfonline.com/doi/full/10.1179/ 1467010013Z.00000000076

    2013

  7. [7]

    Von B´ ek´ esy,Experiments in hearing., Experiments in hearing

    G. Von B´ ek´ esy,Experiments in hearing., Experiments in hearing. (Mcgraw Hill, Oxford, England, 1960), pages: x, 745

    1960

  8. [8]

    Cohen, Ear & Hearing28, 100S (2007), ISSN 0196-0202, URLhttps://journals.lww.com/ 00003446-200704001-00024

    N. Cohen, Ear & Hearing28, 100S (2007), ISSN 0196-0202, URLhttps://journals.lww.com/ 00003446-200704001-00024

    2007

Show all 39 references
  1. [9]

    J. R. Dornhoffer, S. K. Lawlor, A. A. Saoji, and C. L. W. Driscoll, Journal of Clinical Medicine12, 5875 (2023), ISSN 2077-0383, URLhttps://www.mdpi.com/ 2077-0383/12/18/5875

    2023

  2. [10]

    Udvardi, J

    P. Udvardi, J. Rad´ o, A. Straszner, J. Ferencz, Z. Hajnal, S. Soleimani, M. Schneider, U. Schmid, P. R´ ev´ esz, and J. Volk, Micromachines8(2017), ISSN 2072-666X, URL https://www.mdpi.com/2072-666X/8/10/311

    2017

  3. [11]

    Csaba and W

    G. Csaba and W. Porod, Applied Physics Reviews7, 011302 (2020), ISSN 1931-9401

    2020

  4. [12]

    Sebastian, M

    A. Sebastian, M. Gallo, R. Khaddam-Aljameh, and E. Eleftheriou, Nature Nanotechnology15, 529 (2020)

    2020

  5. [13]

    Z. Wang, H. Wu, G. W. Burr, C. S. Hwang, K. L. Wang, Q. Xia, and J. J. Yang, Nature Reviews Materials5, 173 (2020), ISSN 2058-8437, URLhttps://doi.org/10. 1038/s41578-019-0159-3

    2020

  6. [14]

    Kumar, X

    S. Kumar, X. Wang, J. P. Strachan, Y. Yang, and W. D. Lu, Nature Reviews Materials7, 575 (2022), ISSN 2058-8437, URLhttps://doi.org/10. 1038/s41578-022-00434-z. 8

    2022

  7. [15]

    H. Liu, Y. Qin, H.-Y. Chen, J. Wu, J. Ma, Z. Du, N. Wang, J. Zou, S. Lin, X. Zhang, et al., Advanced Materials35, 2205047 (2023), URLhttps://onlinelibrary.wiley.com/doi/abs/10. 1002/adma.202205047

    2023

  8. [16]

    Song, J.-H

    M.-K. Song, J.-H. Kang, X. Zhang, W. Ji, A. Ascoli, I. Messaris, A. S. Demirkol, B. Dong, S. Aggarwal, W. Wan, et al., ACS Nano17, 11994 (2023)

    2023

  9. [17]

    Huang, T

    Y. Huang, T. Ando, A. Sebastian, M.-F. Chang, J. J. Yang, and Q. Xia, Nature Reviews Electrical Engi- neering1, 286 (2024), ISSN 2948-1201, publisher: Na- ture Publishing Group, URLhttps://www.nature.com/ articles/s44287-024-00037-6

    2024

  10. [18]

    G. Zhou, Z. Wang, B. Sun, F. Zhou, L. Sun, H. Zhao, X. Hu, X. Peng, J. Yan, H. Wang, et al., Advanced Electronic Materials8, 2101127 (2022), ISSN 2199-160X, URLhttps://onlinelibrary.wiley.com/doi/abs/10. 1002/aelm.202101127

    2022

  11. [19]

    Boybat, M

    I. Boybat, M. Le Gallo, S. R. Nandakumar, T. Moraitis, T. Parnell, T. Tuma, B. Rajendran, Y. Leblebici, A. Se- bastian, and E. Eleftheriou, Nature Communications9, 2514 (2018)

    2018

  12. [20]

    W. Yi, K. K. Tsang, S. K. Lam, X. Bai, J. A. Crowell, and E. A. Flores, Nature Communications9, 4661 (2018)

    2018

  13. [21]

    Han, S.-Y

    J.-K. Han, S.-Y. Yun, S.-W. Lee, J.-M. Yu, and Y.- K. Choi, Advanced Functional Materials32, 2204102 (2022), ISSN 1616-3028, URLhttps://onlinelibrary. wiley.com/doi/abs/10.1002/adfm.202204102

    2022 doi

  14. [22]

    C. A. Navntoft, J. Marozeau, and T. R. Barkat, Scientific Reports10(2020), URLhttps://api. semanticscholar.org/CorpusID:211253757

    2020

  15. [23]

    M. A. Rutherford, H. von Gersdorff, and J. D. Gout- man, The Journal of Physiology599, 2527 (2021), ISSN 1469-7793, URLhttps://onlinelibrary.wiley. com/doi/abs/10.1113/JP279189

    2021 doi

  16. [24]

    N. Q. Kh´ anh, Z. E. Horv´ ath, Z. Zolnai, P. Petrik, L. P´ osa, and J. Volk, Materials Science in Semicon- ductor Processing169, 107902 (2024), ISSN 1369- 8001, URLhttps://www.sciencedirect.com/science/ article/pii/S1369800123005954

    2024

  17. [25]

    H. Kim, N. S. Bingham, N. A. Charipar, and A. Piqu´ e, AIP Advances7, 105116 (2017), ISSN 2158-3226

    2017

  18. [26]

    H. Kim, N. Charipar, M. Osofsky, S. B. Qadri, and A. Piqu´ e, Applied Physics Letters104, 081913 (2014), ISSN 0003-6951, URLhttps://doi.org/10.1063/1. 4866806

    2014 doi

  19. [27]

    H. Kim, N. Charipar, E. Breckenfeld, A. Rosenberg, and A. Piqu´ e, Thin Solid Films596, 45 (2015), ISSN 0040- 6090, the 42nd International Conference on Metallurgical Coatings and Thin Films

    2015

  20. [28]

    R. J. Suess, N. S. Bingham, K. M. Charipar, H. Kim, S. A. Mathews, A. Piqu´ e, and N. A. Charipar, Advanced Materials Interfaces4, 1700810 (2017)

    2017

  21. [29]

    P´ osa, P

    L. P´ osa, P. Hornung, T. N. T¨ or¨ ok, S. W. Schmid, S. Arj- mandabasi, G. Moln´ ar, Z. Baji, G. Draˇ zi´ c, A. Halbritter, and J. Volk, ACS Applied Nano Materials6, 9137 (2023)

    2023

  22. [30]

    Pollner, T

    Z. Pollner, T. N. T¨ or¨ ok, L. P´ osa, M. Csontos, S. W. Schmid, Z. Balogh, A. B¨ ukkfejes, H. Kim, A. Piqu´ e, J. Leuthold, et al.,Vo 2 oscillator circuits optimized for ultrafast, 100 mhz-range operation(2025), 2506.01139, URLhttps://arxiv.org/abs/2506.01139

    2025 arXiv

  23. [31]

    S. W. Schmid, L. P´ osa, T. N. T¨ or¨ ok, B. S´ anta, Z. Pollner, G. Moln´ ar, Y. Horst, J. Volk, J. Leuthold, A. Halbritter, et al., ACS Nano18, 21966 (2024), ISSN 1936-0851, pub- lisher: American Chemical Society, URLhttps://doi. org/10.1021/acsnano.4c03840

    2024 doi

  24. [32]

    P´ erez-Gonz´ alez and M

    D. P´ erez-Gonz´ alez and M. S. Malmierca, Frontiers in Integrative Neuroscience8, 19 (2014), ISSN 1662-5145, URLhttps://europepmc.org/articles/PMC3931124

    2014

  25. [33]

    I. C. Bruce, Y. Erfani, and M. S. A. Zilany, Hearing Research360, 40 (2018), ISSN 0378- 5955, URLhttps://www.sciencedirect.com/science/ article/pii/S0378595517303696

    2018

  26. [34]

    M. A. Zurcher, M. Semaan, C. A. Megerian, W. H. Ko, and D. J. Young, Sensors and Materials22, 297 (2010), URLhttps://api.semanticscholar.org/ CorpusID:14243550

    2010

  27. [35]

    C. Lenk, K. Ved, S. Durstewitz, T. Ivanov, M. Ziegler, and P. H¨ ovel (Springer International Publishing, 2023), pp. 287–315, section: Bio-inspired, Neuromorphic Acous- tic Sensing

    2023

  28. [36]

    L. A. Westerman and R. L. Smith, The Journal of the Acoustical Society of America81, 680 (1987), ISSN 0001- 4966, URLhttps://doi.org/10.1121/1.394836

    1987 doi

  29. [37]

    ˇZ´ ak, Z

    J. ˇZ´ ak, Z. Hadaˇ s, D. Duˇ sek, J. Pek´ arek, V. Svatoˇ s, L. Jan´ ak, and J. Pr´ aˇ sek, Mechatronics31, 30 (2015), publisher: Elsevier

    2015

  30. [38]

    K¨ ortje, T

    M. K¨ ortje, T. St¨ over, U. Baumann, and T. Weissgerber, European Archives of Oto-Rhino-Laryngology280, 5241 (2023), ISSN 0937-4477, URLhttps://pmc.ncbi.nlm. nih.gov/articles/PMC10620283/

    2023

  31. [39]

    Riss, J.-S

    D. Riss, J.-S. Hamzavi, M. Blineder, C. Honeder, I. Ehrenreich, A. Kaider, W.-D. Baumgartner, W. Gstoettner, and C. Arnoldner, Ear and Hearing35, e272 (2014), ISSN 1538-4667, URLhttps://journals. lww.com/ear-hearing/Abstract/2014/11000/FS4%2C_ FS4_p%2C_and_FSP__A_4_Month_Cross...

    2014

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