COMPUTATIONAL AND BIOMECHANICAL MODELS OF CHORDOTONAL ORGANS FOR VIBRO-ACOUSTIC MECHANOSENSING: A SCOPING REVIEW PROTOCOL

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Authors: Thiago Mathias Mathias de Oliveira, Sebastian M. Oberst, Jan M. Hemmi, Naqash Afzal
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Abstract

This project consists of a scoping review protocol entitled “Computational and Biomechanical Models of Chordotonal Organs for Vibro-Acoustic Mechanosensing.” The purpose of this research is to systematically map and critically analyse existing computational and biomechanical modelling approaches used to represent vibroacoustic mechanosensing and mechanotransduction in insect chordotonal organs. Chordotonal organs are key mechanosensory systems responsible for detecting substrate vibrations, airborne sound, and body movements through coupled structural and neurophysiological processes. Although multiple modelling strategies have been proposed over the past two decades, substantial heterogeneity remains in mechanical formulations, parameterisation of mass–stiffness–damping systems, representation of base excitation, modelling of ion-channel dynamics, and integration with neural encoding mechanisms. This scoping review will identify modelling architectures (e.g., lumped mass–spring–damper systems, finite element models, continuous formulations, and hybrid mechanical–neural models), reported biomechanical parameters, mechanotransduction representations, and validation strategies. A structured multi-database search (2000–2026) will be conducted, followed by systematic screening and structured data extraction. Expected outcomes include (i) a comprehensive mapping of current modelling trends, (ii) identification of methodological and conceptual gaps, and (iii) a theoretically grounded framework to support the development of an integrative vibroacoustic model of chordotonal organ function, bridging biomechanics, mechanotransduction, and neural encoding.

Fields of Study & Subjects

Neurobiology and Insect Physiology Research Hearing Cochlea Tinnitus Genetics Biomimetic flight and propulsion mechanisms

Publication details

Publication date
1 January 2026
Language
EN
Document type
Preprint