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Sonification of electronic dynamical systems: Spectral characteristics and sound evaluation using EEG features

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Abstract

Chaos is often described as the limited development of nonlinear dynamic systems that create intricate and non-repetitive patterns. In this study, we questioned how chaotic electronic signals can be transformed into sound stimuli and explored their impact on brain activity using Electroencephalography (EEG). Our experiment involved 31 participants exposed to sounds generated from three processes from electronic implementations: signals from chaotic attractors, periodic limit cycles,and aleatory distributions. Our goal was to analyze characteristics and EEG signals to uncover the complex relationship between chaotic auditory stimuli and cognitive processes. Interestingly the chaotic stimuli caused a reduction in synchronization in the delta (\(\delta\)) and theta (\(\theta\)) frequency bands. We observed differences of up to 30 and 40%, primarily concentrated in the brain’s frontal areas. This desynchronization in \(\delta\) and \(\theta\) bands, seen in individuals, has implications for regulating irregular \(\theta\) power in certain neural disorders. On the other hand, exposure to signals had mostly minimal effects on EEG readings. This research significantly contributes to our understanding of how the brain responds to stimuli derived from electronic systems. It sheds light on applications for modulating activity. Examining unpredictable sounds offers an understanding of the unique impacts of chaotic auditory inputs on brain activity, opening possibilities for further investigations at the crossroads of chaos theory, acoustics, and neuroscience.

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Acknowledgements

Gerardo Acosta would like to thank Consejo Nacional de Ciencia y Tecnología for the mixed scholarship for master’s degree studies (number 462043). E. Guevara acknowledges support from Cátedras CONAHCYT program project No. 528. Luis Javier Ontanon acknowledges COPOCYT for the financial support of project number DG-522/2023 with title "Predicción y seguimiento de trayectorias de sistemas dinámicos mediante redes neuronales artificiales recurrentes y su aplicación en vehículos autónomos”.

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Authors and Affiliations

  1. Instituto de Investigación en Comunicación Óptica, Universidad Autónoma de San Luis Potosí, Av Karakorum # 1470, Lomas 4ta Sección, S. L. P., 78216, San Luis Potosí, Mexico

    G. Acosta Martínez & E. Tristán Hernández

  2. Coordinación para la Innovación y la Aplicación de la Ciencia y la Tecnología, Universidad Autónoma de San Luis Potosí, Sierra Leona 550, Lomas 2da. Sección, S. L. P., 78210, San Luis Potosí, Mexico

    E. Guevara & E. S. Kolosovas-Machuca

  3. CONAHCYT-Universidad Autónoma de San Luis Potosí, Sierra Leona 550, Lomas 2da. Sección, S. L. P., 78210, San Luis Potosí, Mexico

    E. Guevara

  4. Engineering, Modeling and Applied Social Sciences Center, Universidade Federal do ABC, Rua Arcturus, # 03 Jardim Antares, São Bernardo do Campo, Brazil

    P. G. Rodrigues & D. C. Soriano

  5. Coordinación Académica Región Altiplano Oeste, Universidad Autónoma de San Luis Potosí, Carretera Salinas-Santo Domingo #200, Salinas, 78600, San Luis Potosí, Mexico

    L. J. Ontañón-García

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  1. G. Acosta Martínez
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  2. E. Guevara
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Acosta Martínez, G., Guevara, E., Kolosovas-Machuca, E.S. et al. Sonification of electronic dynamical systems: Spectral characteristics and sound evaluation using EEG features. Cogn Neurodyn (2024). https://doi.org/10.1007/s11571-024-10112-1

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