Latency-dependent filtering and compact representation of the complete auditory pathway response
Metadatos
Mostrar el registro completo del ítemAutor
Torre Vega, Ángel De La; Valderrama Valenzuela, Joaquín Tomás; Álvarez Ruiz, Isaac; Segura Luna, José CarlosEditorial
AIP Publishing
Fecha
2020-08Referencia bibliográfica
de la Torre A, Valderrama JT, Alvarez IM, Segura JC. Latency-dependent filtering and compact representation of the complete auditory pathway response. The Journal of the Acoustical Society of America (2020) 148, 599-613. doi: 10.1121/10.0001673.
Patrocinador
EQC2018-004988-P project grant, funded by the Spanish Ministry of Science, Innovation and UniversitiesResumen
Auditory evoked potentials (AEPs) include the auditory brainstem response (ABR), middle latency response (MLR), and cortical auditory evoked potentials (CAEPs), each one covering a specific latency range and frequency band. For this reason, ABR, MLR, and CAEP are usually recorded separately using different protocols. This article proposes a procedure providing a latency-dependent filtering and down-sampling of the AEP responses. This way, each AEP component is appropriately filtered, according to its latency, and the complete auditory pathway response is conveniently represented (with the minimum number of samples, i.e., without unnecessary redundancies). The compact representation of the complete response facilitates a comprehensive analysis of the evoked potentials (keeping the natural continuity related to the neural activity transmission along the auditory pathway), which provides a new perspective in the design and analysis of AEP experiments. Additionally, the proposed compact representation reduces the storage or transmission requirements when large databases are manipulated for clinical or research purposes. The analysis of the AEP responses shows that a compact representation with 40 samples/decade (around 120 samples) is enough for accurately representing the response of the complete auditory pathway and provides appropriate latency-dependent filtering. MATLAB/Octave code implementing the proposed procedure is included in the supplementary materials.




