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Behavioral results indicating the effects of the two forms of sound conduction (air, bone) on accuracy (left) and response times (right) in self-other voice discrimination task. The abscissa of both plots indicates the percentage of the self-voice present in a Voice Morph. The shaded areas around each curve represent the 95% confidence intervals. Accuracy was higher and response times were faster for bone conduction.
Source publication
There is growing evidence showing that the representation of the human "self" recruits special systems across different functions and modalities. Compared to self-face and self-body representations, few studies have investigated neural underpinnings specific to self-voice. Moreover, self-voice stimuli in those studies were consistently presented th...
Contexts in source publication
Context 1
... present or other voice (15%) (Estimate = 1.22, Z = 2.57, P = 0.01). Difference in accuracy between other Voice Morphs was not significant (all P > 0.05). Together, these findings indicated that participants discriminated own from a stranger's voice better with bone compared to air conduction, and this was most prominent for other-dominant morphs (Fig. 3, ...
Context 3
... for map 4, there was a significant interaction between Parameter and Dominant Voice (F(3, 227.04) = 4.51, P = 0.004) and between Parameter and Conduction (F(3, 227.62) = 5.47, P = 0.001). A three-way interaction between the effects of Parameter, Dominant Voice, and Conduction was not significant (F(3, 226.93) = 0.91, P = 0.437). Thus, for each Parameter, we conducted a separate linear mixedeffects regression with Parameter Value as dependent variable, and Conduction and Dominant Voice as fixed effects. ...
Citations
... This is to give the machine a sense of hearing, so that the machine can understand human language, recognize the sound or the content of the sound, and accurately convert the human voice into words or meaningful symbols. This enables the machine to execute, and realizes the automation and intelligence of industrial production (Iannotti et al. 2022). ...
In the AI sports training system, the traditional optical imaging technology limits the resolution of the image. Therefore, the use of optical super-resolution imaging technology to improve image resolution can promote the further development of AI motion training systems. In this study, high-resolution images and corresponding low-resolution images are collected as training data, and an optical superresolution imaging model based on deep learning is established. The GPU parallel computing technology is used to accelerate the training and inference process of the model. Finally, the optimized high-resolution image is applied to the AI sports training system, and the experimental evaluation is carried out. The experimental results show that the optical superresolution imaging technology based on GPU parallel computing can significantly improve the resolution and clarity of the image. Compared with the traditional optical imaging technology, the image processed by optical superresolution imaging has better performance in detail and edge. Through the test of the motion capture system, it is observed that the images processed by optical super-resolution imaging can detect and analyze the motion details more accurately.
... This microstate was backfitted to each participant's original, spatially filtered, averaged, error-related activity using the same backfitting procedure as described for resting-state data; however, for task data, polarity was accounted for, the minimum spatial correlation was .25 instead of .50 (as done in Iannotti et al. 2022 and to exclude highly dissimilar topographies), and backfitting was only performed in the window of time represented by that particular microstate as identified during segmentation. The backfitting procedure produced values of this microstate's GEV for each participant. ...
The error-related negativity (ERN) is a negative deflection in the electroencephalography (EEG) waveform at frontal-central scalp sites that occurs after error commission. The relationship between the ERN and broader patterns of brain activity measured across the entire scalp that support error processing during early childhood is unclear. We examined the relationship between the ERN and EEG microstates – whole-brain patterns of dynamically evolving scalp potential topographies that reflect periods of synchronized neural activity – during both a go/no-go task and resting-state in 90, 4-8-year-old children. The mean amplitude of the ERN was quantified during the -64 to 108 millisecond (ms) period of time relative to error commission, which was determined by data-driven microstate segmentation of error-related activity. We found that greater magnitude of the ERN associated with greater global explained variance (GEV; i.e., the percentage of total variance in the data explained by a given microstate) of an error-related microstate observed during the same -64 to 108 ms period (i.e., error-related microstate 3), and to greater anxiety risk as measured by parent-reported behavioral inhibition. During resting-state, six data-driven microstates were identified. Both greater magnitude of the ERN and greater GEV values of error-related microstate 3 associated with greater GEV values of resting-state microstate 4, which showed a frontal-central scalp topography. Source localization results revealed overlap between the underlying neural generators of error-related microstate 3 and resting-state microstate 4 and canonical brain networks (e.g., ventral attention) known to support the higher-order cognitive processes involved in error processing. Taken together, our results clarify how individual differences in error-related and intrinsic brain activity are related and enhance our understanding of developing brain network function and organization supporting error processing during early childhood.
... outgroup-related information (Walker et al. 2008;Schiller et al. 2020a), less vs. more attractive faces (Han et al. 2020(Han et al. , 2022, self-vs. other-voice processing This table includes studies using the EEG microstate approach analyzing socio-affective states ("states") or individual differences ("traits") in the socio-affective mind in healthy populations 1 Total sample size before participant exclusion (Iannotti et al. 2022), social vs. non-social stimuli/contexts (Thierry et al. 2006;Ortigue et al. 2009Ortigue et al. , 2010Cacioppo et al. 2012Cacioppo et al. , 2015Cacioppo et al. , 2016Cacioppo et al. , 2018Koban et al. 2012;Decety and Cacioppo 2012;Pegna et al. 2015), stereotype-congruent vs. stereotype-incongruent information (Schiller et al. 2016), stress vs. no stress (Schiller et al. 2023a) and neutral vs. emotional stimuli (Pizzagalli et al. 2000;Gianotti et al. 2007Gianotti et al. , 2008Cacioppo et al. 2016;Tanaka et al. 2021;Zerna et al. 2021;Liang et al. 2022;Prete et al. 2022) (Fig. 3). Schiller et al. (2016) provide an example demonstrating quantitative differences across ERPs in the incongruent and the congruent condition of the Implicit Association Test (IAT), a widely-cited measure of implicit bias (Greenwald et al. 1998). ...
Social interactions require both the rapid processing of multifaceted socio-affective signals (e.g., eye gaze, facial expressions, gestures) and their integration with evaluations, social knowledge, and expectations. Researchers interested in understanding complex social cognition and behavior face a “black box” problem: What are the underlying mental processes rapidly occurring between perception and action and why are there such vast individual differences? In this review, we promote electroencephalography (EEG) microstates as a powerful tool for both examining socio-affective states (e.g., processing whether someone is in need in a given situation) and identifying the sources of heterogeneity in socio-affective traits (e.g., general willingness to help others). EEG microstates are identified by analyzing scalp field maps (i.e., the distribution of the electrical field on the scalp) over time. This data-driven, reference-independent approach allows for identifying, timing, sequencing, and quantifying the activation of large-scale brain networks relevant to our socio-affective mind. In light of these benefits, EEG microstates should become an indispensable part of the methodological toolkit of laboratories working in the field of social and affective neuroscience.
... Speech-in-noise perception is also done with the participation of all areas of the brain. The neural centers for speech perception are various and temporal lobe is influenced by several sensory processings and mechanisms, the auditory brain is not actually monosensory and had multi-modal processing [38,50,51]. ...
... The SVSS is in the range of the fundamental frequency of the human voice [36], which differs between men = 100 HZ , women = 200 HZ , and infants = up to 400 HZ [54]. Considering that the saccule is close to the larynx and is also connected to the cochlea [2], the afferent nerve fibers of the saccule are stimulated during self-voice production [34,38], and the person ossifies his own voice through feedback control or bone-conducted pathway [38]. ...
... The SVSS is in the range of the fundamental frequency of the human voice [36], which differs between men = 100 HZ , women = 200 HZ , and infants = up to 400 HZ [54]. Considering that the saccule is close to the larynx and is also connected to the cochlea [2], the afferent nerve fibers of the saccule are stimulated during self-voice production [34,38], and the person ossifies his own voice through feedback control or bone-conducted pathway [38]. ...
Sensitivity of vestibular system to sounds (SVSS) can be measureable by cervical vestibular evoked myogenic potentials (cVEMPs). The aim of this study is to investigate central representation of vestibular system sensitivity to sound. The research was conducted in 2022–2023 by searching English language databases. The criterion for selecting documents was their overlap with the aim of this work. The animals studies were not included. The saccule is stimulated by sounds, that are transmitted through air and bone conduction. Utricle and semicircular canals are activated only by the vibrations. The afferent nerve fibers of the vestibular system project to the temporal, frontal, parietal, primary visual cortex, insula and the cingulate cortex. There is a relationship between normal results of the cVEMPs and these parameters. Improved phonemes recognition scores and word recognition scores in white noise, the efficiency of auditory training, incraed amplitude of the auditory brainstem responses to 500 HZ tone burst. Learning the first words is not only based on the hearing and other senses participate. The auditory object is a three-dimensional imaging in people's minds, when they hear a word. The words expressed by a speaker create different auditory objects in people's minds. Each of these auditory objects has its own color, shape, aroma and characteristics. For the formation of the auditory objects, all senses and whole areas of the brain contribute. Like other senses, central representation of vestibular system sensitivity to sound are also involved in the formation of auditory objects.
... instead of .50 (as done inIannotti et al., 2022), and back tting was only performed in the window of time represented by that particular microstate. The back tting procedure produced values of this microstate's GEV for each participant.Reliability via internal consistency values were calculated for each microstate measure of interest. ...
The error-related negativity (ERN) is a negative deflection in the electroencephalography (EEG) waveform at frontal-central scalp sites that occurs after error commission. The relationship between the ERN and broader patterns of brain activity measured across the entire scalp that support error processing during early childhood is unclear. We examined the relationship between the ERN and EEG microstates – whole-brain patterns of dynamically evolving scalp potential topographies that reflect periods of synchronized neural activity – during both a go/no-go task and resting-state in 90, 4-8-year-old children. The mean amplitude of the ERN was quantified during the − 64 to 108 millisecond (ms) period of time relative to error commission, which was determined by data-driven microstate segmentation of error-related activity. We found that greater magnitude of the ERN associated with greater global explained variance (GEV; i.e., the percentage of total variance in the data explained by a given microstate) of an error-related microstate observed during the same − 64 to 108 ms period (i.e., error-related microstate 3), and to greater parent-report-measured anxiety risk. During resting-state, six data-driven microstates were identified. Both greater magnitude of the ERN and greater GEV values of error-related microstate 3 associated with greater GEV values of resting-state microstate 4, which showed a frontal-central scalp topography. Source localization results revealed overlap between the underlying neural generators of error-related microstate 3 and resting-state microstate 4 and canonical brain networks (e.g., ventral attention) known to support the higher-order cognitive processes involved in error processing. Taken together, our results clarify how individual differences in error-related and intrinsic brain activity are related and enhance our understanding of developing brain network function and organization supporting error processing during early childhood.
... For each voice morph, participants were instructed to indicate whether the voice they heard more closely resembled their own or someone else's voice by pressing on one of two buttons. Based on our previous work [58,59], six voice ratios (% self-voice: 15, 30, 45, 55, 70, 85; figure 1a) were chosen and repeated 10 times within a block in a randomized order (total of 60 trials). The study contained four experimental blocks, which differed based on the sound conduction type (air, bone) and whether participants were exposed to the unmorphed self-voice immediately prior to the experiment. ...
... The results of the three discrimination tasks (self-other, familiar-other and self-familiar) are illustrated in Overall, these data demonstrate that bone conduction improved the performance in VD tasks if the task involved self-voice morphs, regardless of other-voice familiarity (steeper psychometric curves in self-other and self-familiar, but not in familiar-other task; asterisks in the middle of plots in figure 3). Lower intercepts for bone conduction (asterisks in the left end of plots in figure 3) indicate that this was especially prominent for other-dominant voice morphs (i.e. containing lower rate of self-voice present) [59]. ...
... While previous self-voice tasks have been characterized by ceiling effects, the paradigm proposed here is able to capture inter-subject variability, which allows us to dissect perceptual specificities (e.g. a bias, general sensitivity, or effects specific to self-or other-voice perception) and personalize studies of selfother VD. Most participants in Studies 1 and 3 (as well as in our follow-up EEG study [59]) spontaneously reported that they perceived the self-other VD task to be very difficult and showed poor metacognition; that is, they misjudged their ability of successfully performing the task. Moreover, in Study 1, we observed large differences in performance across participants. ...
One's own voice is one of the most important and most frequently heard voices. Although it is the sound we associate most with ourselves, it is perceived as strange when played back in a recording. One of the main reasons is the lack of bone conduction that is inevitably present when hearing one's own voice while speaking. The resulting discrepancy between experimental and natural self-voice stimuli has significantly impeded self-voice research, rendering it one of the least investigated aspects of self-consciousness. Accordingly, factors that contribute to self-voice perception remain largely unknown. In a series of three studies, we rectified this ecological discrepancy by augmenting experimental self-voice stimuli with bone-conducted vibrotactile stimulation that is present during natural self-voice perception. Combining voice morphing with psychophysics, we demonstrate that specifically self-other but not familiar-other voice discrimination improved for stimuli presented using bone as compared with air conduction. Furthermore, our data outline independent contributions of familiarity and acoustic processing to separating the own from another's voice: although vocal differences increased general voice discrimination, self-voices were more confused with familiar than unfamiliar voices, regardless of their acoustic similarity. Collectively, our findings show that concomitant vibrotactile stimulation improves auditory self-identification, thereby portraying self-voice as a fundamentally multi-modal construct.
... High task sensitivity also enabled us to observe that the bone-conduction advantage is most advantageous for other-dominant self-other voice morphs (i.e., containing more other-voice features). This was observed in Study 3 in both self-other and self-familiar tasks (left side of psychometric curves on Fig 3), and replicated in a follow-up EEG study with an independent cohort of participants performing the same self-other task with five times more trials 54 . This suggests that, rather than labelling an ambiguous voice as 'self', bone conduction facilitates discarding an ambiguous voice as being 'not self'. ...
One’s own voice is one of the most important and most frequently heard voices and the sound we associate most with ourselves, and yet, it is perceived as strange when played back in a recording. One of the main reasons is the lack of bone conduction that is inevitably present when hearing own voice while speaking. The resulting discrepancy between experimental and natural self-voice stimuli has significantly impeded self-voice research, rendering it one of the least investigated aspects of self-consciousness. Accordingly, factors that contribute to self-voice perception remain largely unknown. In a series of three studies, we rectified this ecological discrepancy by augmenting experimental self-voice stimuli with bone-conducted vibrotactile stimulation that is present during natural self-voice perception. Combining voice-morphing with psychophysics, we demonstrate that specifically self-other but not familiar-other voice discrimination improved for stimuli presented using bone as compared to air conduction. Furthermore, our data outline independent contributions of familiarity and acoustic processing to separating the own from another’s voice: although vocal differences increased general voice discrimination, self-voices were more confused with familiar than unfamiliar voices, regardless of their acoustic similarity. Collectively, our findings show that concomitant vibrotactile stimulation improves auditory self-identification, thereby portraying self-voice as a fundamentally multimodal construct.
... High task sensitivity also enabled us to observe that the bone-conduction advantage is most advantageous for other-dominant self-other voice morphs (i.e., containing more other-voice features). This was observed in Study 3 in both self-other and self-familiar tasks (left side of psychometric curves on Fig 3), and replicated in a follow-up EEG study with an independent cohort of participants performing the same self-other task with five times more trials 54 . This suggests that, rather than labelling an ambiguous voice as 'self', bone conduction facilitates discarding an ambiguous voice as being 'not self'. ...
One’s own voice is one of the most important and most frequently heard voices and the sound we associate most with ourselves, and yet, it is perceived as strange when played back in a recording. One of the main reasons is the lack of bone conduction that is inevitably present when hearing own voice while speaking. The resulting discrepancy between experimental and natural self-voice stimuli has significantly impeded self-voice research, rendering it one of the least investigated aspects of self-consciousness. Accordingly, factors that contribute to self-voice perception remain largely unknown. In a series of three studies, we rectified this ecological discrepancy by augmenting experimental self-voice stimuli with bone-conducted vibrotactile stimulation that is present during natural self-voice perception. Combining voice-morphing with psychophysics, we demonstrate that specifically self-other but not familiar-other voice discrimination improved for stimuli presented using bone as compared to air conduction. Furthermore, our data outline independent contributions of familiarity and acoustic processing to separating the own from another’s voice: although vocal differences increased general voice discrimination, self-voices were more confused with familiar than unfamiliar voices, regardless of their acoustic similarity. Collectively, our findings show that concomitant vibrotactile stimulation improves auditory self-identification, thereby portraying self-voice as a fundamentally multimodal construct.
... 27,[35][36][37][38] or indirectly (e.g. 39 ). That being said, other brain regions, not explored in the present study, might also be implicated in perceptual precision weighting. ...
Background and hypothesis:
Hallucinations may be driven by an excessive influence of prior expectations on current experience. Initial work has supported that contention and implicated the anterior insula in the weighting of prior beliefs.
Study design:
Here we induce hallucinated tones by associating tones with the presentation of a visual cue. We find that people with schizophrenia who hear voices are more prone to the effect and using computational modeling we show they overweight their prior beliefs. In the same participants, we also measured glutamate levels in anterior insula, anterior cingulate, dorsolateral prefrontal, and auditory cortices, using magnetic resonance spectroscopy.
Study results:
We found a negative relationship between prior-overweighting and glutamate levels in the insula that was not present for any of the other voxels or parameters.
Conclusions:
Through computational psychiatry, we bridge a pathophysiological theory of psychosis (glutamate hypofunction) with a cognitive model of hallucinations (prior-overweighting) with implications for the development of new treatments for hallucinations.
... Here, we investigated cardiac and respiratory phase dependency of self-voice perception. We recorded heartbeat and respiration signals of healthy participants performing two self-related auditory tasks (self-other voice discrimination; loudness judgment) (Iannotti et al., 2021;Orepic et al., 2021). We investigated whether self-voice perception would differ in trials occurring during different phases of respiratory (inspiration, expiration) and heartbeat (systole, diastole) cycles. ...
A growing number of studies have focused on identifying cognitive processes that are modulated by interoceptive signals, particularly in relation to the respiratory or cardiac cycle. Considering the fundamental role of interoception in bodily self-consciousness, we here investigated whether interoceptive signals also impact self-voice perception. We applied an interactive, robotic paradigm associated with somatic passivity (a bodily state characterized by illusory misattribution of self-generated touches to someone else) to investigate whether somatic passivity impacts self-voice perception as a function of concurrent interoceptive signals. Participants' breathing and heartbeat signals were recorded while they performed two self-voice tasks (self-other voice discrimination and loudness perception) and while simultaneously experiencing two robotic conditions (somatic passivity condition; control condition). Our data reveal that respiration, but not cardiac activity, affects self-voice perception: participants were better at discriminating self-voice from another person's voice during the inspiration phase of the respiration cycle. Moreover, breathing effects were prominent in participants experiencing somatic passivity and a different task with the same stimuli (i.e., judging the loudness and not identity of the voices) was unaffected by breathing. Combining interoception and voice perception with self-monitoring framework, these data extend findings on breathing-dependent changes in perception and cognition to self-related processing.
