Analysing non-linear systems in the frequency domain--II. The phase response

Billings, S.A.; Zhang, H.

doi:10.1006/mssp.1994.1004

Cited by 19 publications

(4 citation statements)

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“…so that the phase of each SC is shifted by a constant factor / l (k). The phase response relating input and output responses of the non-linear transfer function has been well characterized by Billings and Zhang (1994). The latter reference demonstrates the assertion that the phase of a SC (output), whose frequency is a linear combination of primary frequencies (inputs), will be the same linear combination of the primary phases.…”

Section: A the Primary Tone Phase Variation Technique And The Frequementioning

confidence: 95%

“…Two limitations of the gPTPV method can be encountered when several non-linearities contribute to the same SC. On the one hand, if the contributing non-linearities have different phase responses, which is generally the case if their respective orders differ (Billings and Zhang, 1994), the phase of the output response cannot be predicted from the phases of the primaries. On the other hand, if they share the same phase response the gPTPV method will yield a single output waveform, irrespective of the number of contributing non-linearities.…”

Section: Intrinsic Limitationsmentioning

confidence: 99%

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Generalization of the primary tone phase variation method: An exclusive way of isolating the frequency-following response components

Lucchetti

Deltenre

Avan³

et al. 2018

The Journal of the Acoustical Society of America

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The primary tone phase variation (PTPV) technique combines selective sub-averaging with systematic variation of the phases of multitone stimuli. Each response component having a known phase relationship with the stimulus components phases can be isolated in the time domain. The method was generalized to the frequency-following response (FFR) evoked by a two-tone (f 1 and f 2) stimulus comprising both linear and non-linear, as well as transient components. The generalized PTPV technique isolated each spectral component present in the FFR, including those sharing the same frequency, allowing comparison of their latencies. After isolation of the envelope component f 2f 1 from its harmonic distortion 2f 2-2f 1 and from the transient auditory brainstem response, a computerized analysis of instantaneous amplitudes and phases was applied in order to objectively determine the onset and offset latencies of the response components. The successive activation of two generators separated by 3.7 ms could be detected in all (N ¼ 12) awake adult normal subjects, but in none (N ¼ 10) of the sleeping/sedated children with normal hearing thresholds. The method offers an unprecedented way of disentangling the various FFR subcomponents. These results open the way for renewed investigations of the FFR components in both human and animal research as well as for clinical applications. V

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Section: A the Primary Tone Phase Variation Technique And The Frequementioning

confidence: 95%

Section: Intrinsic Limitationsmentioning

confidence: 99%

Generalization of the primary tone phase variation method: An exclusive way of isolating the frequency-following response components

Lucchetti

Deltenre

Avan³

et al. 2018

The Journal of the Acoustical Society of America

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“…The energy at 2 F 0 in S ( f ) may reflect one or more of the following sources: (1) rectifier distortion to carrier energy at F 0 , (2) beating between (carrier) harmonics that are separated by 2 F 0 , and (3) effects of transduction nonlinearities on the beating between (carrier) harmonics that are separated by F 0 . In these special cases, additional stimulus phase variations can be used to separate out these components [ 84 , 85 ].…”

Section: Discussionmentioning

confidence: 99%

Spectrally specific temporal analyses of spike-train responses to complex sounds: A unifying framework

2021

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Significant scientific and translational questions remain in auditory neuroscience surrounding the neural correlates of perception. Relating perceptual and neural data collected from humans can be useful; however, human-based neural data are typically limited to evoked far-field responses, which lack anatomical and physiological specificity. Laboratory-controlled preclinical animal models offer the advantage of comparing single-unit and evoked responses from the same animals. This ability provides opportunities to develop invaluable insight into proper interpretations of evoked responses, which benefits both basic-science studies of neural mechanisms and translational applications, e.g., diagnostic development. However, these comparisons have been limited by a disconnect between the types of spectrotemporal analyses used with single-unit spike trains and evoked responses, which results because these response types are fundamentally different (point-process versus continuous-valued signals) even though the responses themselves are related. Here, we describe a unifying framework to study temporal coding of complex sounds that allows spike-train and evoked-response data to be analyzed and compared using the same advanced signal-processing techniques. The framework uses a set of peristimulus-time histograms computed from single-unit spike trains in response to polarity-alternating stimuli to allow advanced spectral analyses of both slow (envelope) and rapid (temporal fine structure) response components. Demonstrated benefits include: (1) novel spectrally specific temporal-coding measures that are less confounded by distortions due to hair-cell transduction, synaptic rectification, and neural stochasticity compared to previous metrics, e.g., the correlogram peak-height, (2) spectrally specific analyses of spike-train modulation coding (magnitude and phase), which can be directly compared to modern perceptually based models of speech intelligibility (e.g., that depend on modulation filter banks), and (3) superior spectral resolution in analyzing the neural representation of nonstationary sounds, such as speech and music. This unifying framework significantly expands the potential of preclinical animal models to advance our understanding of the physiological correlates of perceptual deficits in real-world listening following sensorineural hearing loss.

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“…The energy at 2F 0 in S(f ) may reflect one or more of the following sources: (1) rectifier distortion to carrier energy at F 0 , (2) beating between (carrier) harmonics that are separated by 2F 0 , and (3) effects of transduction nonlinearities on the beating between (carrier) harmonics that are separated by F 0 . In these special cases, additional stimulus phase variations can be used to separate out these components (Billings and Zhang, 1994;Lucchetti et al, 2018).…”

Section: Alternating-polarity Stimulimentioning

confidence: 99%

Spectrally specific temporal analyses of spike-train responses to complex sounds: A unifying framework

Parida

Bharadwaj

Heinz

2020

Preprint

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Significant scientific and translational questions remain in auditory neuroscience surrounding the neural correlates of perception. Relating perceptual and neural data collected from humans can be useful; however, human-based neural data are typically limited to evoked far-field responses, which lack anatomical and physiological specificity. Laboratory-controlled preclinical animal models offer the advantage of comparing single-unit and evoked responses from the same animals. This ability provides opportunities to develop invaluable insight into proper interpretations of evoked responses, which benefits both basic-science studies of neural mechanisms and translational applications, e.g., diagnostic development. However, these comparisons have been limited by a disconnect between the types of spectrotemporal analyses used with single-unit spike trains and evoked responses, which results because these response types are fundamentally different (point-process versus continuous-valued signals) even though the responses themselves are related. Here, we describe a unifying framework to study temporal coding of complex sounds that allows spike-train and evoked-response data to be analyzed and compared using the same advanced signal-processing techniques. The framework uses alternating-polarity peristimulus-time histograms computed from single-unit spike trains to allow advanced spectral analyses of both slow (envelope) and rapid (temporal fine structure) response components. Demonstrated benefits include: (1) generalization beyond classic metrics of temporal coding, e.g., vector strength and correlograms, (2) novel spectrally specific temporal-coding measures that are less corrupted by distortions due to hair-cell transduction, synaptic rectification, and neural stochasticity compared to previous metrics, e.g., the correlogram peak-height, (3) spectrally specific analyses of spike-train modulation coding that can be directly compared to perceptually based models of speech intelligibility, and (4) superior spectral resolution in analyzing the neural representation of nonstationary sounds, such as speech and music. This unifying framework significantly expands the potential of preclinical animal models to advance our understanding of the physiological correlates of perceptual deficits in real-world listening following sensorineural hearing loss.

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Analysing non-linear systems in the frequency domain--II. The phase response

Cited by 19 publications

References 0 publications

Generalization of the primary tone phase variation method: An exclusive way of isolating the frequency-following response components

Generalization of the primary tone phase variation method: An exclusive way of isolating the frequency-following response components

Spectrally specific temporal analyses of spike-train responses to complex sounds: A unifying framework

Spectrally specific temporal analyses of spike-train responses to complex sounds: A unifying framework

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