Dynamics of Vocalization-Induced Modulation of Auditory Cortical Activity at Mid-utterance

Chen, Zhaocong; Jones, Jeffery A.; Liu, Peng; Liu, Weifeng; Huang, Dongfeng; Liu, Hanjun

doi:10.1371/journal.pone.0060039

Cited by 13 publications

(20 citation statements)

References 43 publications

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“…This finding is consistent with previous studies in animals and humans that showed a similar vocalization-induced enhancement of cortical responses [Behroozmand et al, 2009[Behroozmand et al, , 2015Chang et al, 2013;Chen et al, 2013b;Eliades and Wang, 2008;Greenlee et al, 2013;Liu et al, 2010]. This finding is consistent with previous studies in animals and humans that showed a similar vocalization-induced enhancement of cortical responses [Behroozmand et al, 2009[Behroozmand et al, , 2015Chang et al, 2013;Chen et al, 2013b;Eliades and Wang, 2008;Greenlee et al, 2013;Liu et al, 2010].…”

Section: Discussionsupporting

confidence: 93%

“…Individuals with PD and healthy controls were exposed to FAF regarding their ongoing vocalizations while they sustained a vowel phonation. Previous research has also shown that active vocalization elicits significantly larger P2 responses than passive listening [Behroozmand et al, 2009Chen et al, 2013b], so we expected this vocalization-induced enhancement to be observed in individuals with PD and healthy controls. The magnitudes and latencies of vocal responses and N1 and P2 ERP components [Chen et al, 2012;Hawco et al, 2009] were compared across conditions.…”

Section: Introductionmentioning

confidence: 79%

“…We used both objective and subjective methods to ensure that the level of the playback during passive listening was identical to the level of voice feedback participants heard during active vocalization Chen et al, 2013b]. We used both objective and subjective methods to ensure that the level of the playback during passive listening was identical to the level of voice feedback participants heard during active vocalization Chen et al, 2013b].…”

Section: Apparatusmentioning

confidence: 99%

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The impact of parkinson's disease on the cortical mechanisms that support auditory–motor integration for voice control

Huang

Chen

Yan

et al. 2016

Human Brain Mapping

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Several studies have shown sensorimotor deficits in speech processing in individuals with idiopathic Parkinson's disease (PD). The underlying neural mechanisms, however, remain poorly understood. In the present event-related potential (ERP) study, 18 individuals with PD and 18 healthy controls were exposed to frequency-altered feedback (FAF) while producing a sustained vowel and listening to the playback of their own voice. Behavioral results revealed that individuals with PD produced significantly larger vocal compensation for pitch feedback errors than healthy controls, and exhibited a significant positive correlation between the magnitude of their vocal responses and the variability of their unaltered vocal pitch. At the cortical level, larger P2 responses were observed for individuals with PD compared with healthy controls during active vocalization due to left-lateralized enhanced activity in the superior and inferior frontal gyrus, premotor cortex, inferior parietal lobule, and superior temporal gyrus. These two groups did not differ, however, when they passively listened to the playback of their own voice. Individuals with PD also exhibited larger P2 responses during active vocalization when compared with passive listening due to enhanced activity in the inferior frontal gyrus, precental gyrus, postcentral gyrus, and middle temporal gyrus. This enhancement effect, however, was not observed for healthy controls. These findings provide neural evidence for the abnormal auditory-vocal integration for voice control in individuals with PD, which may be caused by their deficits in the detection and correction of errors in voice auditory feedback. Hum Brain Mapp 37:4248-4261, 2016. © 2016 Wiley Periodicals, Inc.

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Section: Discussionsupporting

confidence: 93%

Section: Introductionmentioning

confidence: 79%

Section: Apparatusmentioning

confidence: 99%

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The impact of parkinson's disease on the cortical mechanisms that support auditory–motor integration for voice control

Huang

Chen

Yan

et al. 2016

Human Brain Mapping

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“…The pitch-shift stimuli and the ensuing vocal responses have been shown to elicit well-documented patterns of ERPs (Behroozmand, Karvelis, Liu, & Larson, 2009; Behroozmand, Korzyukov, & Larson, 2011; Z. Chen, et al, 2013; Korzyukov, Karvelis, Behroozmand, & Larson, 2012; H.…”

Section: Introductionmentioning

confidence: 99%

Bioelectrical brain effects of one's own voice identification in pitch of voice auditory feedback

et al. 2017

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Control of voice fundamental frequency (F0) relies in part on comparison of the intended F0 level and auditory feedback. This comparison impacts “sense of agency”, or SoA, commonly defined as being the agent of one's own actions and plays a key role for self-awareness and social interactions. SoA is aberrant in several psychiatric disorders. Knowledge about brain activity reflecting SoA can be used in clinical practice for these disorders. It was shown that perception of voice feedback as one’s own voice, reflecting the recognition of SoA, alters auditory sensory processing. Using a voice perturbation paradigm we contrasted vocal and bioelectrical brain responses to auditory stimuli that differed in magnitude: 100 and 400 cents. Results suggest the different magnitudes were perceived as a pitch error in self-vocalization (100 cents) or as a pitch shift generated externally (400 cents). Vocalizations and neural responses to changes in pitch of self-vocalization were defined as those made to small magnitude pitch- shifts (100 cents) and which did not show differential neural responses to upward versus downward changes in voice pitch auditory feedback. Vocal responses to large magnitude pitch shifts (400 cents) were smaller than those made to small pitch shifts, and neural responses differed according to upwards versus downward changes in pitch. Our results suggest that the presence of SoA for self-produced sounds may modify bioelectrical brain responses reflecting differences in auditory processing of the direction of a pitch shift. We suggest that this modification of bioelectrical response can be used as a biological index of SoA. Possible neuronal mechanisms of this modification of bioelectrical brain response are discussed.

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“…H. Chen, Liu, Xu, & Larson, 2007; Z. Chen et al, 2013;Liu, Meshman, Behroozmand, & Larson, 2011;Sitek et al, 2013;Sugimori, Asai, & Tanno, 2013). Abnormalities in the detection of self-generated voice feedback during speech production disrupt verbal communication processes (Lane & Webster, 1991;Moeller et al, 2007;Oller & Eilers, 1988;Schauwers et al, 2004).…”

mentioning

confidence: 99%

The effects of stimulus complexity on the preattentive processing of self-generated and nonself voices: An ERP study

Conde

Gonçalves

Pinheiro

2015

Cogn Affect Behav Neurosci

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The ability to differentiate one's own voice from the voice of somebody else plays a critical role in successful verbal self-monitoring processes and in communication. However, most of the existing studies have only focused on the sensory correlates of self-generated voice processing, whereas the effects of attentional demands and stimulus complexity on self-generated voice processing remain largely unknown. In this study, we investigated the effects of stimulus complexity on the preattentive processing of self and nonself voice stimuli. Event-related potentials (ERPs) were recorded from 17 healthy males who watched a silent movie while ignoring prerecorded self-generated (SGV) and nonself (NSV) voice stimuli, consisting of a vocalization (vocalization category condition: VCC) or of a disyllabic word (word category condition: WCC). All voice stimuli were presented as standard and deviant events in four distinct oddball sequences. The mismatch negativity (MMN) ERP component peaked earlier for NSV than for SGV stimuli. Moreover, when compared with SGV stimuli, the P3a amplitude was increased for NSV stimuli in the VCC only, whereas in the WCC no significant differences were found between the two voice types. These findings suggest differences in the time course of automatic detection of a change in voice identity. In addition, they suggest that stimulus complexity modulates the magnitude of the orienting response to SGV and NSV stimuli, extending previous findings on self-voice processing.

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Dynamics of Vocalization-Induced Modulation of Auditory Cortical Activity at Mid-utterance

Cited by 13 publications

References 43 publications

The impact of parkinson's disease on the cortical mechanisms that support auditory–motor integration for voice control

The impact of parkinson's disease on the cortical mechanisms that support auditory–motor integration for voice control

Bioelectrical brain effects of one's own voice identification in pitch of voice auditory feedback

The effects of stimulus complexity on the preattentive processing of self-generated and nonself voices: An ERP study

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