Frequency-dependent fine structure in the frequency-following response: The byproduct of multiple generators

Tichko, Parker; Skoe, Erika

doi:10.1016/j.heares.2017.01.014

Cited by 88 publications

(89 citation statements)

References 92 publications

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“…Our results corroborate the EFR reductions observed for higher 8 modulation frequencies in temporal modulation transfer functions (Purcell et al, 2004). 9 Because we compensated for the frequency dependent noise floor (~1/f) by using the EFR SNR 10 metric, the effect of modulation frequency on the EFR is likely attributed to the frequency 11 dependent constructive and destructive phase interferences of multiple neural generators 12 thought to be responsible for the EFR generation (Tichko and Skoe, 2017). Even though it is 13 much harder to measure the EFR to a 480-Hz modulator, they might reflect more peripheral 14 generators than the IC and offer a better proxy measure for synaptopathy (Shaheen et al, 15 2015).…”

Section: Effects Of Modulation Frequency and The Efr Generatorssupporting

confidence: 81%

Applicability of subcortical EEG metrics of synaptopathy to older listeners with impaired audiograms

Garrett

Verhulst

2018

Preprint

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2Emerging evidence suggests that cochlear synaptopathy is a common feature of sensorineural 3 hearing loss, but it is not known whether electrophysiological metrics targeting synaptopathy in 4 animals can be applied to a broad range of people, such as those with impaired audiograms. 5 This study investigates the applicability of subcortical electrophysiological measures associated 6 with synaptopathy such as auditory brainstem responses (ABRs) and envelope following 7 responses (EFRs) in older participants with high-frequency sloping audiograms. This is important 8 for the development of reliable and sensitive synaptopathy diagnostics in people with normal or 9 impaired outer-hair-cell function. Broadband click-ABRs at different sound pressure levels and 10 EFRs to amplitude-modulated stimuli were recorded, as well as relative EFR and ABR metrics 11 which reduce individual factors such as head size and noise floor level. Most tested metrics 12 showed significant differences between the groups and did not always follow the trends 13 expected from synaptopathy. Audiometric hearing loss and age-related hearing related deficits 14 interacted to affect the electrophysiological metrics and complicated their interpretation in 15 terms of synaptopathy. This study contributes to a better understanding of how 16 electrophysiological synaptopathy metrics differ in ears with healthy and impaired audiograms, 17 which is an important first step towards unravelling the perceptual consequences of 18 synaptopathy. 19 20 21 Keywords 22 auditory brainstem response, envelope following response, cochlear synaptopathy, diagnostics, 23 sensorineural hearing loss, deafferentation 24 25 26 27

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Section: Effects Of Modulation Frequency and The Efr Generatorssupporting

confidence: 81%

Applicability of subcortical EEG metrics of synaptopathy to older listeners with impaired audiograms

Garrett

Verhulst

2018

Preprint

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“…It has been shown that the generally decreasing relation between response amplitude or SNR and frequency has many peaks and valleys (Gransier et al, 2016; Kuwada et al, 2002; Purcell et al, 2004; Purcell and John, 2010; Tichko and Skoe, 2017), in part because of destructive and constructive interference between various FFR sources (Tichko and Skoe, 2017). In this study, it was found that response SNR was significantly lower for the mid-frequency stimuli compared to the low-and high-frequency stimuli, indicating a valley near the mid-frequency, i.e.…”

Section: Discussionmentioning

confidence: 99%

“…These simple stimuli are often unnatural, but they allow for precise manipulation of the acoustic cues. Examples are tonebursts (Clinard et al, 2010; Gardi et al, 1979; Glaser et al, 1976; Tichko and Skoe, 2017), pure tones (Gockel et al, 2015; Holmes et al, 2018), tone sweeps (Billings et al, 2019; Clinard and Cotter, 2015; Krishnan and Parkinson, 2000; Purcell et al, 2004) and (sinusoidally) amplitude modulated (AM) stimuli (Bidelman and Patro, 2016; Dimitrijevic et al, 2016; Van Canneyt et al, 2019). It is unclear whether findings for these non-speech stimuli can be generalized to responses evoked by speech stimuli.…”

Section: Introductionmentioning

confidence: 99%

From Modulated Noise to Natural Speech: the Effect of Stimulus Parameters on the Frequency Following Response

Canneyt

Wouters

Francart

2019

Preprint

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5Frequency following responses (FFRs) can be evoked by a wide range of auditory stimuli, but for many stimulus parameters the effect on FFR strength is not fully understood. This complicates the comparison of earlier studies and the design of new studies. Furthermore, the most optimal stimulus parameters are unknown. To help resolve this issue, we investigated the effects of four important stimulus parameters and their interactions on the FFR. FFRs were measured in 16 normal hearing subjects evoked by stimuli with four levels of stimulus complexity (amplitude modulated noise, artificial vowels, natural vowels and nonsense words), three frequencies (around 105 Hz, 185 Hz and 245 Hz), three frequency contours (upward sweeping, downward sweeping and flat) and three vowels (Flemish /a:/, /u:/, and /i:/). We found that FFRs evoked by artificial vowels were on average 4 to 6 dB SNR larger than responses evoked by the other stimulus complexities, probably because of (unnaturally) strong higher harmonics. Moreover, response amplitude decreased with stimulus frequency but response SNR did not. Thirdly, frequency variation within the stimulus did not impact FFR strength, but only when rate of change remained low (e.g. not the case for sweeping natural vowels). Finally, the vowel /i:/ appeared to evoke larger response amplitudes compared to /a:/ and /u:/, but analysis power was too small to confirm this statistically. Differences in response strength between evoking vowels have been suggested to stem from destructive interference between response components. We show how a model of the auditory periphery can simulate these interference patterns and predict response strength. Altogether, the results of this study can guide stimulus choice for future FFR research and practical applications.

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“…Previous studies measuring FFRs in humans concluded that FFRs obtained in response to fast frequencies (i.e. >100 Hz) typically result from activity in subcortical structures 62,86,87 . The same could be true for C. perspicillata, since in this species most auditory cortex neurons cannot track amplitude modulations above 20 Hz 41,88 , even though field potentials measured at the cortical level do entrain to faster acoustic rhythms 39,40 .…”

Section: Possible Neural Mechanisms For Fast Periodicity Extractionmentioning

confidence: 99%

Superfast periodicities in distress vocalizations emitted by bats

Hechavarría

Beetz

García‐Rosales

et al. 2019

Preprint

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spectrum Abbreviations:AM: amplitude modulation, d: Cliff's delta, DPOAE; distortion product otoacoustic emissions, FFR: frequency following response, FOI, frequency of interest, FPV: fast periodic vocalizations, HND: harmonic-to-noise difference, HR: heart rate, iEEG: intracortical encephalogram, IQR; interquartile range, MPS: modulation power spectrum, qCF-FM: quasiconstant frequencyfrequency modulated, SFM: sinusoidal frequency modulation, SVM: support vector machine, TMS: temporal modulation spectrum. AbstractCommunication sounds are ubiquitous in the animal kingdom, where they play a role in advertising physiological states and/or socio-contextual scenarios. Distress sounds, for example, are typically uttered in distressful scenarios such as agonistic interactions. Here, we report on the occurrence of superfast temporal periodicities in distress calls emitted by bats (species Carollia perspicillata). Distress vocalizations uttered by this bat species are temporally modulated at frequencies close to 1.7 kHz, that is, ~17 times faster than modulation rates observed in human screams. Fast temporal periodicities are represented in the bats' brain by means of frequency following responses, and temporally periodic sounds are more effective in boosting the heart rate of awake bats than their demodulated versions. Altogether, our data suggest that bats, an animal group classically regarded as ultrasonic, can exploit the low frequency portion of the soundscape during distress calling to create spectro-temporally complex, arousing sounds.

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Frequency-dependent fine structure in the frequency-following response: The byproduct of multiple generators

Cited by 88 publications

References 92 publications

Applicability of subcortical EEG metrics of synaptopathy to older listeners with impaired audiograms

Applicability of subcortical EEG metrics of synaptopathy to older listeners with impaired audiograms

From Modulated Noise to Natural Speech: the Effect of Stimulus Parameters on the Frequency Following Response

Superfast periodicities in distress vocalizations emitted by bats

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