Cortical Contributions to Frequency Following Responses and Modulation

Study Overview
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Brief Summary
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The frequency-following response (FFR), a scalp-recorded neurophonic potential, is a widely used metric of speech encoding integrity in healthy and clinical human populations. The translational potential of the FFR as a biomarker is constrained by poor understanding of its neural generators and influencing factors. This study leverages a cross-species and cross-level approach to provide mechanistic insight into the properties of the cortical source of the FFR, and elucidate the role of cortical feedback via cortico-collicular projections on modulation of the FFR as a function of stimulus context, arousal state, and category relevance. This clinical trial will focus on the influences of category relevance, predictability, and participant arousal state on the FFRs in neurotypical human participants.

Detailed Description
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Participants will listen to a variety of sounds while the frequency-following response (FFR) is recorded. The FFR is a sound-evoked response that mirrors the acoustic properties of the incoming acoustic signal with remarkable fidelity. The FFR is now recognized as an integrated response resulting from an interplay of early auditory subcortical and cortical systems. The cortical dynamics underlying the FFR are unclear. All stimuli will be normalized to the same root mean squared amplitude and stimulus duration and played at the same in-the-ear intensity. Thirty-two stimuli from human and animal natural productions with a wide-range of F0 will be used to elicit the FFR. At least 1000 artifact-free trials will be collected for every stimulus. Participants will sit in a quiet room (patients) or a sound-treated booth and listen to sounds while electroencephalography (EEG) and pupillometry signals are continuously acquired. EEG signals will be collected using Ag-AgCl scalp electrodes, with the active electrode placed at the central zero (Cz) point, the reference at the right mastoid, and the ground at the left mastoid. Contact impedence will be< 5 kΩ for all electrodes for all recording sessions, and responses will be recorded at a sampling rate of 25 kHz using Brain Vision PyCorder 1.0.7 (Brain Products, Gilching, Germany). Alternating polarities of the stimuli will be binaurally presented in sound field (identical to the animal protocols), with an inter-stimulus interval jittered between 122 to 148ms. Participants will be instructed to stay awake and refrain from making extraneous movements. EEG and pupil measures will allow continuous monitoring of participant state. The order of blocks will be counterbalanced across participants, and stimulus presentation will be controlled by E-Prime 2.0.10 software. The electrophysiological data will be preprocessed with BrainVision Analyzer 2.0 (Brain Products, Gilching, Germany), bandpass filtered (varies based on stimulus F0; 12 dB/octave, zero phase-shift). The bandpass filter will approximately reflect the lower and upper limits of phase-locking along the auditory pathway that contributes to the FFR (auditory cortex, midbrain). Responses will be segmented into epochs, baseline corrected to the mean voltage of the noise floor(-40 to 0ms). Epochs in which the amplitude exceeds ± 35μV will be considered artifacts and rejected. In each session, a preset number of artifact-free FFR trials (500 for each polarity) will be obtained. For pupillometry, participants will be seated in a chair and will place their head on a chin rest. The stabilized mount also has a small horizontal bar that they can place their forehead against. To calibrate the eye tracker, participants will be asked to follow 9 dots that appear on a monitor with their eyes. Insert earbuds will be placed in both ears, and auditory stimuli will be presented binaurally. Pupillometry data will be preprocessed to remove noise from the analysis. The pupil data will be downsampled to 50 Hz. Trials with more than 15% of the samples detected as blinks will be removed. Missing samples due to blinks will be linearly interpolated from approximately100 ms prior to and 100 ms after the blink. Pupil responses will be baseline normalized using the average pupil size in the 500-1000 ms prior to the onset of the auditory stimuli. A key variable reported will be the percent change in pupil size.

Official Title
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Cortical Contributions to Frequency Following Responses and Modulation

Conditions
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Language

Intervention / Treatment
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* Behavioral: Speech and non-speech sound stimulation


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Age 13 years up to 25 years Healthy volunteers Native English speaking individuals with no exposure or experience to tonal languages Native Mandarin speakers Hearing sensitivity within normal limits (Puretone hearing thresholds < 25dB from 250 Hz to 8000 Hz) Less than six years of formal music training or experience Exclusion Criteria: Proficiency in languages other than English or Chinese History of or current complaint of hearing loss or tinnitus History of or current complaint of cognitive impairments Individuals with more than 5 years of formal music experience or training Complaints of impaired speech perception in noise

Ages Eligible for Study
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Minimum Age: 13 Years
Maximum Age: 25 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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Accepts Healthy Volunteers

Study Plan
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How is the study designed?
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Design Details

Primary Purpose: Basic Science
Intervention Model: Single Group Assignment
Masking: None (Open Label)


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Experimental: Neurotypical Human Participants<br>Native speakers of Chinese and native speakers of English | Behavioral: Speech and non-speech sound stimulation<br>* Listening to repetitive and extended sound presentation induces specific neural and physiological activity that we will measure via electroencephalography and pupillometry<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Pitch tracking and decoding accuracies for dynamically varying pitch in naturally produced Mandarin tone categories | The similarity between the stimulus and the FFR will be evaluated. The pitch tracking ability will be estimated by comparing the sliding window autocorrelation pitch tracks of the stimulus and FFR. Machine learning models will be trained to decode FFR to different stimulus categories based on pitch height and pitch direction. The chance estimates of the decoding accuracies will be estimated. | During EEG session, up to 3 hours | 
| Stimulus-specific effects in Chinese vs. English participants | The stimulus-specific effects in human participants, based on pitch tracking and decoding accuracies, will be assessed. The decoding accuracies and pitch tracking metrics for mandarin tone categories will be compared between Chinese listeners and English listeners. The focus will be to evaluate the specific benefits in Chinese listeners to track pitch height and direction patterns in Mandarin tones. | During EEG session, up to 3 hours | 
| Arousal state and predictability effects on the FFRs | Arousal state and its dependence on encoding of predictability effects on the FFRs will be evaluated. The pitch tracking metrics and decoding accuracies will be compared across repetitive and contextual stimulus sequences while sorting the trials based on peak pupillary dilation as a proxy for arousal state. The predictability effects will be charted as a function of the arousal states and evaluated. | During simultaneous EEG and pupillometry session, up to 3 hours |