HumanFrequency-Following Responses to Voice Pitch: Effects of Silent Interval Subjects: Twelve adults with hearing sensitivity ≤ 20 dB HL at octave frequencies from 250 to 8000 Hz were recruited. All participants were native speakers of Mandarin Chinese. Token: A monosyllabic Mandarin Chinese syllable (/i/ with a rising pitch) was used. Presentation: The stimulus token was presented monaurally to the right ear at a level of 70 dB SPL. The silent intervals were set at 5 ms, 10 ms, 30 ms, 45 ms, 60 ms, 125 ms and 250 ms. A control condition was conducted at the end of each testing session Recording: Four gold-plated recording electrodes were applied to all participants at the high forehead, low forehead, and right mastoid. Data Analysis: All data were analyzed using MatLab 2008a. · Transition zone between response and noise floor identified between 285-295 ms ·Shortest silent interval that can be used without compromising responses is between 35-45 ms · One way repeated measures ANOVA for the 10 ms pre-stimulus interval not significant (p=0.079) · For future research, larger number of participants to account for subject variability Ronny P. Warrington Dr. Fuh-CherngJeng Method Introduction Discussion Fig. 2: Hilbert Envelope References Changes in voice pitch over time carry important information for speech understanding. Voice pitch also carries lexical meanings of speech for tonal languages, such as Chinese, Korean and Thai. It is evident that voice pitch is essential in speech understanding; therefore, an assessment of voice pitch may shed light on the neural processing of speech perception. Human frequency-following responses (FFR) to voice pitch have provided valuable information on how the human brain processes speech information. The FFR is an objective, non-invasive method reflecting the neural phase-locking activity within the human brainstem (Jenget al., 2010, 2011a, 2011b; Li & Jeng, 2011; Skoe & Kraus, 2010). Although recording parameters for FFRs vary from study to study, causing overlap in brainstem responses, the FFR has been a key component in providing information on the brain’s ability to process speech. Jeng, F.-C., Hu, J., Dickman M. B., Montgomery-Reagan, K., Tong, M., Wu, G., & Lin, C.-D. (2011b, in press). Cross-linguistic comparison of frequency-following responses to voice pitch in American and Chinese neonates and adults. Ear Hear (accepted on March 26, 2011). Jeng, F.-C., Hu, J., Dickman, B. M., Lin, C.-Y., Lin, C.-D., Wang, C.-Y., Chung, H.-K., & Li, X. (2011a). Evaluation of two algorithms for detecting human frequency-following responses to voice pitch. Int J Audiol, 50(1), 14-26 (DOI:10.3109/14992027.2010.515620). Jeng, F.-C., Schnabel, E. A., Dickman, B. M., Hu, J., Li, X., Lin, C.-D., & Chung, H.-K. (2010). Early maturation of frequency-following responses to voice pitch in infants with normal hearing. Percept Mot Skills, 111(3), 765-784 (DOI:10.2466/10.22.24.PMS.111.6.765-784). Li, X. & Jeng, F.-C. (2011). Noise tolerance in human frequency-following responses to voice pitch. J Acoust Soc Am, 129(1), EL21-26 (DOI:10.1121/1.3528775). Skoe, E. & Kraus, N. (2010). Auditory brain stem response to complex sounds: A tutorial. Ear &Hearing, 31, 302-324. Fig. 1: RMS Envelope An RMS (root-mean-square) (Figure 1) and Hilbert (Figure 2) envelopes were completed to illustrate the energy of the responses and to assist in identifying the shortest silent interval with no overlap in responses. One way repeated measures ANOVA was not significant (p=0.079) in defining the magnitude of overlaps for the 10 ms pre-stimulus interval. Results ·The primary aim of the study was to determinethe shortest silent interval that will have no overlap in recorded brainstem responses. · It was hypothesized that as the silent interval decreases, FFR waveforms will increasingly overlap with adjacent waveforms as there is insufficient time for the response to return to baseline. Purpose and Hypothesis Acknowledgements · This study was supported in part by the OU CHSP Research Challenge Award.