Research Article
BibTex RIS Cite

İŞİTSEL KORTEKSİN GÜRÜLTÜDEKİ SESLERİ ALGILAMAK İÇİN KONTRASTA UYUM SAĞLAMASI

Year 2025, Volume: 28 Issue: 4, 2080 - 2092, 03.12.2025

Fatma Özcan

Abstract

Zorlu işitme koşullarında, işlevini yerine getirebilmek için çok çeşitli mekanizmalar geliştiren işitme sistemi, çevresel bilgileri kullanarak kaynakları birbirinden ayırmalıdır. Amacımız, işitsel korteksteki nöronal aktivitenin, çeşitli gürültü seviyelerinde davranışsal performansı öngörüp öngörmediğini doğrulamaktır. Bu çalışmada, derin öğrenme teknikleri kullanılarak, gürültülü bir ortamda, hedef sesin varlığı ve yoğunluğunun işitsel kortekste nasıl kodlandığı incelenmiştir. Nöronal veriler, Skalogram veya Mel-spektrogram görüntülere dönüştürülmüştür. Bu görüntüler seslerle önceden eğitilmiş yapay sinir ağı ile işlenmiştir ve sonuçlar karşılaştırılmıştır. Nöronal kodlama kapsamında, hedef sesin yüksek veya düşük gürültü ortamında mevcut olup olmadığı ve 6 hedef ses seviyesinin ayırt edilip edilemeyeceği analiz edilmiştir. Yüksek veya düşük kontrast içerisinde hedef sesin varlığının ve seviyesinin beyinde kodlanması değerlendirilmiştir. Yüksek kontrastta en zayıf hedef ses, %90,4 AUC değeriyle tespit edilirken, düşük kontrastta en zayıf hedef ses, %100 AUC değeriyle sınıflandırılmıştır. Bu işlemin anlaşılması, duyusal engelli kişilere yardımcı olabilecek yapay sistemlerin geliştirilmesine olanak sağlayacaktır.

Keywords

Gürültü İşitsel Korteks Nöronal kod çözümü Skalogram derin öğrenme

References

  • Abrams, E. B., Marantz, A., Krementsov, I., & Gwilliams, L. (2025). Dynamics of Pitch Perception in the Auditory Cortex. J Neurosci, 45(12). https://doi.org/10.1523/JNEUROSCI.1111-24.2025
  • Alishbayli, A. (2024). Processing of Statistically Defined Sounds in the Auditory Cortex. https://hdl.handle.net/2066/301602
  • Angeloni, C. F., Mlynarski, W., Piasini, E., Williams, A. M., Wood, K. C., Garami, L., . . . Geffen, M. N. (2023). Dynamics of cortical contrast adaptation predict perception of signals in noise. Nat Commun, 14(1), 4817. DOI: 10.1038/s41467-023-40477-6
  • Arandjelovic, R., & Zisserman, A. (2017). Look, Listen and Learn. Paper presented at the 2017 IEEE International Conference on Computer Vision. https://doi.org/10.48550/arXiv.1705.0816
  • Bisharat, G., Kaganovski, E., Sapir, H., Temnogorod, A., Levy, T., & Resnik, J. (2025). Repeated stress gradually impairs auditory processing and perception. PLoS Biol, 23(2), e3003012. DOI: 10.1371/journal.pbio.3003012
  • Ceravolo, L., Scariati, J. E., Frühholz, S., Van De Ville, D., & Grandjean, D. (2024). Functional and causal neural mechanisms of human voice perception in noisy situations bioRxiv. doi: https://doi.org/10.1101/2024.10.21.619396
  • Clayton, K. K., McGill, M., Awwad, B., Stecyk, K. S., Kremer, C., Skerleva, D., . . . Polley, D. B. (2024). Cortical determinants of loudness perception and auditory hypersensitivity. bioRxiv. DOI: 10.1101/2024.05.30.596691
  • Cramer, J., Wu, H. H., Salamon, J., & Bello, J. P. (2019). Look listen and learn more: design choices for deep audio embeddings. IEEE. DOI: 10.1109/ICASSP.2019.8682475
  • Kang, H., & Kanold, P. O. (2024). Sparse representation of neurons for encoding complex sounds in the auditory cortex. Prog Neurobiol, 241, 102661. DOI: 10.1016/j.pneurobio.2024.102661
  • Kell, A. J. E., & McDermott, J. H. (2019). Invariance to background noise as a signature of non-primary auditory cortex. Nat Commun, 10(1), 3958. DOI: 10.1038/s41467-019-11710-y
  • Lee, T. Y., Weissenberger, Y., King, A. J., & Dahmen, J. C. (2024). Midbrain encodes sound detection behavior without auditory cortex. elife, 12. DOI: 10.7554/eLife.89950
  • Lilly, J. M., & Olhede, S. C. (2012). Generalized Morse wavelets as a superfamily of analytic wavelets. IEEE Transactions on Signal Processing, 60(11), 6036-6041. DOI: 10.1109/TSP.2012.2210890
  • Liu, C. (2022). More Performance Evaluation Metrics for Classification Problems You Should Know. https://www.kdnuggets.com/2020/04/performance-evaluation-metrics-classification.html
  • Mai, A., Hillyard, S. A., & Strauss, D. J. (2025). Linear modeling of brain activity during selective attention to continuous speech: the critical role of the N1 effect in event-related potentials to acoustic edges. Cogn Neurodyn, 19(1), 110. https://doi.org/10.1007/s11571-025-10289-z(0
  • Marios Akritas, A. G. A., Jules M Lebert, Arne F Meyer, Maneesh Sahani, Jennifer F Linden. (2024). Nonlinear sensitivity to acoustic context is a stable feature of neuronal responses to complex sounds in auditory cortex of awake mice. elife. https://doi.org/10.7554/eLife.98415.1
  • Mathworks. (2025). Matlab R2025a. https://www.mathworks.com/products/matlab.html
  • Olhede, S. C., & Walden, A. T. (2002). Generalized morse wavelets. IEEE Transactions on Signal Processing, 50(11), 2661-2670. DOI: 10.1109/TSP.2002.804066
  • Özcan, F. (2025). Differentiability of voice disorders through explainable AI. Scientific Reports. https://doi.org/10.1038/s41598-025-03444-3
  • Özcan, F., & Alkan, A. (2021). Frontal Cortex Neuron Type Classification with Deep Learning and Recurrence Plot. Traitement du Signal. DOI: https://doi.org/10.18280/ts.380327
  • Özcan, F., & Alkan, A. (2023). Neural decoding of inferior colliculus multiunit activity for sound category identification with temporal correlation and transfer learning. Network-Computation in neural Systems. DOI: 10.1080/0954898X.2023.2282576
  • Pachitariu, M., Steinmetz, N., Kadir, S., Carandini, M., & Harris, K. (2016). Fast and accurate spike sorting of high-channel count probes with KiloSort. Advances in Neural Information Processing Systems, 29. https://dl.acm.org/doi/pdf/10.5555/3157382.3157595
  • Shehabi, S., Comstock, D. C., Mankel, K., Bormann, B. M., Das, S., Brodie, H., . . . Miller, L. M. (2025). Individual Differences in Cognition and Perception Predict Neural Processing of Speech in Noise for Audiometrically Normal Listeners. eNeuro, 12(4). DOI: 10.1523/ENEURO.0381-24.2025
  • Treisman, A. M. (1969). Strategies and models of selective attention. Psychol Rev, 76(3), 282-299. https://doi.org/10.1037/h0027242
  • Tseng, H. C., & Hsieh, I. H. (2024). Effects of absolute pitch on brain activation and functional connectivity during hearing-in-noise perception. Cortex, 174, 1-18. DOI: 10.1016/j.cortex.2024.02.011
  • Wang, M., Jendrichovsky, P., & Kanold, P. O. (2024). Auditory discrimination learning differentially modulates neural representation in auditory cortex subregions and inter-areal connectivity. Cell Rep, 43(5), 114172. DOI: 10.1016/j.celrep.2024.114172
  • Yang, L., Wang, S., Chen, Y., Liang, Y., Chen, T., Wang, Y., . . . Wang, S. (2024). Effects of Age on the Auditory Cortex During Speech Perception in Noise: Evidence From Functional Near-Infrared Spectroscopy. Ear Hear, 45(3), 742-752. DOI: 10.1097/AUD.0000000000001460

THE AUDITORY CORTEX ADAPTS TO CONTRAST IN ORDER TO PERCEIVE SOUNDS IN NOISE

Year 2025, Volume: 28 Issue: 4, 2080 - 2092, 03.12.2025

Fatma Özcan

Abstract

In challenging hearing conditions, the auditory system, which has developed a wide variety of mechanisms to perform its function, must distinguish between sources using environmental information. Our aim is to verify whether neuronal activity in the auditory cortex predicts behavioural performance at various noise levels. In this study, deep learning techniques were used to investigate how the presence and intensity of the target sound are encoded in the auditory cortex in a noisy environment. Neuronal data were converted into Scalogram or Mel-spectrogram images. These images were processed using an artificial neural network pre-trained with sounds, and the results were compared. Within the scope of neural coding, it was analysed whether the target sound was present in high or low noise environments and whether 6 target sound levels could be distinguished. The encoding of the target sound's presence and level in the brain within high or low contrast was evaluated. In high contrast, the weakest target sound was detected with an AUC value of 90.4%, while in low contrast, the weakest target sound was classified with an AUC value of 100%. Understanding this process will enable the development of artificial systems that could assist individuals with sensory impairments.

Keywords

Noise Auditory Cortex Neuronal Decoding Scalogram deep learning

References

  • Abrams, E. B., Marantz, A., Krementsov, I., & Gwilliams, L. (2025). Dynamics of Pitch Perception in the Auditory Cortex. J Neurosci, 45(12). https://doi.org/10.1523/JNEUROSCI.1111-24.2025
  • Alishbayli, A. (2024). Processing of Statistically Defined Sounds in the Auditory Cortex. https://hdl.handle.net/2066/301602
  • Angeloni, C. F., Mlynarski, W., Piasini, E., Williams, A. M., Wood, K. C., Garami, L., . . . Geffen, M. N. (2023). Dynamics of cortical contrast adaptation predict perception of signals in noise. Nat Commun, 14(1), 4817. DOI: 10.1038/s41467-023-40477-6
  • Arandjelovic, R., & Zisserman, A. (2017). Look, Listen and Learn. Paper presented at the 2017 IEEE International Conference on Computer Vision. https://doi.org/10.48550/arXiv.1705.0816
  • Bisharat, G., Kaganovski, E., Sapir, H., Temnogorod, A., Levy, T., & Resnik, J. (2025). Repeated stress gradually impairs auditory processing and perception. PLoS Biol, 23(2), e3003012. DOI: 10.1371/journal.pbio.3003012
  • Ceravolo, L., Scariati, J. E., Frühholz, S., Van De Ville, D., & Grandjean, D. (2024). Functional and causal neural mechanisms of human voice perception in noisy situations bioRxiv. doi: https://doi.org/10.1101/2024.10.21.619396
  • Clayton, K. K., McGill, M., Awwad, B., Stecyk, K. S., Kremer, C., Skerleva, D., . . . Polley, D. B. (2024). Cortical determinants of loudness perception and auditory hypersensitivity. bioRxiv. DOI: 10.1101/2024.05.30.596691
  • Cramer, J., Wu, H. H., Salamon, J., & Bello, J. P. (2019). Look listen and learn more: design choices for deep audio embeddings. IEEE. DOI: 10.1109/ICASSP.2019.8682475
  • Kang, H., & Kanold, P. O. (2024). Sparse representation of neurons for encoding complex sounds in the auditory cortex. Prog Neurobiol, 241, 102661. DOI: 10.1016/j.pneurobio.2024.102661
  • Kell, A. J. E., & McDermott, J. H. (2019). Invariance to background noise as a signature of non-primary auditory cortex. Nat Commun, 10(1), 3958. DOI: 10.1038/s41467-019-11710-y
  • Lee, T. Y., Weissenberger, Y., King, A. J., & Dahmen, J. C. (2024). Midbrain encodes sound detection behavior without auditory cortex. elife, 12. DOI: 10.7554/eLife.89950
  • Lilly, J. M., & Olhede, S. C. (2012). Generalized Morse wavelets as a superfamily of analytic wavelets. IEEE Transactions on Signal Processing, 60(11), 6036-6041. DOI: 10.1109/TSP.2012.2210890
  • Liu, C. (2022). More Performance Evaluation Metrics for Classification Problems You Should Know. https://www.kdnuggets.com/2020/04/performance-evaluation-metrics-classification.html
  • Mai, A., Hillyard, S. A., & Strauss, D. J. (2025). Linear modeling of brain activity during selective attention to continuous speech: the critical role of the N1 effect in event-related potentials to acoustic edges. Cogn Neurodyn, 19(1), 110. https://doi.org/10.1007/s11571-025-10289-z(0
  • Marios Akritas, A. G. A., Jules M Lebert, Arne F Meyer, Maneesh Sahani, Jennifer F Linden. (2024). Nonlinear sensitivity to acoustic context is a stable feature of neuronal responses to complex sounds in auditory cortex of awake mice. elife. https://doi.org/10.7554/eLife.98415.1
  • Mathworks. (2025). Matlab R2025a. https://www.mathworks.com/products/matlab.html
  • Olhede, S. C., & Walden, A. T. (2002). Generalized morse wavelets. IEEE Transactions on Signal Processing, 50(11), 2661-2670. DOI: 10.1109/TSP.2002.804066
  • Özcan, F. (2025). Differentiability of voice disorders through explainable AI. Scientific Reports. https://doi.org/10.1038/s41598-025-03444-3
  • Özcan, F., & Alkan, A. (2021). Frontal Cortex Neuron Type Classification with Deep Learning and Recurrence Plot. Traitement du Signal. DOI: https://doi.org/10.18280/ts.380327
  • Özcan, F., & Alkan, A. (2023). Neural decoding of inferior colliculus multiunit activity for sound category identification with temporal correlation and transfer learning. Network-Computation in neural Systems. DOI: 10.1080/0954898X.2023.2282576
  • Pachitariu, M., Steinmetz, N., Kadir, S., Carandini, M., & Harris, K. (2016). Fast and accurate spike sorting of high-channel count probes with KiloSort. Advances in Neural Information Processing Systems, 29. https://dl.acm.org/doi/pdf/10.5555/3157382.3157595
  • Shehabi, S., Comstock, D. C., Mankel, K., Bormann, B. M., Das, S., Brodie, H., . . . Miller, L. M. (2025). Individual Differences in Cognition and Perception Predict Neural Processing of Speech in Noise for Audiometrically Normal Listeners. eNeuro, 12(4). DOI: 10.1523/ENEURO.0381-24.2025
  • Treisman, A. M. (1969). Strategies and models of selective attention. Psychol Rev, 76(3), 282-299. https://doi.org/10.1037/h0027242
  • Tseng, H. C., & Hsieh, I. H. (2024). Effects of absolute pitch on brain activation and functional connectivity during hearing-in-noise perception. Cortex, 174, 1-18. DOI: 10.1016/j.cortex.2024.02.011
  • Wang, M., Jendrichovsky, P., & Kanold, P. O. (2024). Auditory discrimination learning differentially modulates neural representation in auditory cortex subregions and inter-areal connectivity. Cell Rep, 43(5), 114172. DOI: 10.1016/j.celrep.2024.114172
  • Yang, L., Wang, S., Chen, Y., Liang, Y., Chen, T., Wang, Y., . . . Wang, S. (2024). Effects of Age on the Auditory Cortex During Speech Perception in Noise: Evidence From Functional Near-Infrared Spectroscopy. Ear Hear, 45(3), 742-752. DOI: 10.1097/AUD.0000000000001460
There are 26 citations in total.

Details

Primary Language Turkish
Subjects Deep Learning, Neural Networks
Journal Section Research Article
Authors

Fatma Özcan 0000-0001-5112-1046

Publication Date December 3, 2025
Submission Date August 3, 2025
Acceptance Date November 25, 2025
Published in Issue Year 2025 Volume: 28 Issue: 4

Cite

APA Özcan, F. (2025). İŞİTSEL KORTEKSİN GÜRÜLTÜDEKİ SESLERİ ALGILAMAK İÇİN KONTRASTA UYUM SAĞLAMASI. Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi, 28(4), 2080-2092.
 Download Cover Image