Recording Frequency-following Responses to Voice Pitch in Guinea Pigs: Preliminary Results

Abstract

Although scalp-recorded frequency-following response (FFR) to voice pitch has shown great potential to examine pitch processing mechanisms in human participants and animals, few reports have addressed the test-retest reliability of such a response in an animal model. The purpose of this study was to investigate the feasibility and reliability of recording such a response in an animal model and to evaluate the extent to which the response could be separated from background noise. A Chinese monosyllable with a rising pitch was used to elicit the FFR to voice pitch in four guinea pigs. Four objective measures (Root-Mean-Square, Amplitude, Tracking Accuracy, Frequency Error, and Slope Error) were computed from recorded brain waves and were used to examine the phase-locking magnitude and test-retest reliability of the response. Results demonstrated that the animal model produced FFR trends that were repeatable, reliable, and significantly different from responses to the background noise.

Implementation of Machine Learning on Human Frequency-Following Responses: A Tutorial

“…33 34 The FFR recorded from different species (e.g., human, macaque, cat, and guinea pig) demonstrates its usefulness in advancing knowledge for basic science and developing new treatments for clinical applications. 34 35 36 Improvements of the FFR after short-term or long-term training facilitate decision making for appropriate treatment and rehabilitation. 37 38 39 40…”

“…33,34 The FFR recorded from different species (e.g., human, macaque, cat, and guinea pig) demonstrates its usefulness in advancing knowledge for basic science and developing new treatments for clinical applications. [34][35][36] Improvements of the FFR after short-term or longterm training facilitate decision making for appropriate treatment and rehabilitation. [37][38][39][40] Potential clinical applications of the FFR are boundless, because characteristics of an FFR can be analyzed in both the time (e.g., peak latency and amplitude, pitch strength, and recording-to-stimulus correlation) and frequency (e.g., spectral amplitude, tracking accuracy, phase consistency) domains with great detail.…”

Frequency-Following Responses to Speech Sounds Are Highly Conserved across Species and Contain Cortical Contributions

“…In addition, animal models can also provide the freedom to record intracortical and scalp FFRs in the same animal to further deconstruct the cortical contribution to the scalp FFRs. The rhesus macaque and guinea pig are vocally communicating animals and have been successfully used as animal models to augment our understanding of the FFRs ( Yamada et al, 1980 ; Chou et al, 2014 ; He et al, 2014 ; Ayala et al, 2017 ; Teichert et al, 2021 ). These animal models are highly similar to humans with respect to audible frequency range, auditory perceptual characteristics, and neuroanatomy ( Sinnott et al, 1976 ; Sinnott and Kreiter, 1991 ; Kaas and Hackett, 2000 ; Rauschecker and Tian, 2000 ; Heffner and Heffner, 2007 ; Grimsley et al, 2012 ; Naert et al, 2019 ).…”

Deconstructing the Cortical Sources of Frequency Following Responses to Speech: A Cross-species Approach

“…In addition, animal models can also provide the freedom to record intracortical and scalp FFRs in the same animal to further deconstruct the cortical contribution to the scalp FFRs. The rhesus macaque and guinea pig are vocally communicating animals and have been successfully used as animal models to augment our understanding of the FFRs (Yamada et al, 1980;Chou et al, 2014;He et al, 2014;Ayala et al, 2017;Teichert et al, 2021). These animal models are highly similar to humans with respect to audible frequency range, auditory perceptual characteristics, and neuroanatomy (Sinnott et al, 1976;Sinnott and Kreiter, 1991;Kaas and Hackett, 2000;Rauschecker and Tian, 2000;Heffner and Heffner, 2007;Grimsley et al, 2012;Naert et al, 2019).…”