Search

Purpose: In this study, the objectification of the subjective perception of loudness was investigated using electroencephalography (EEG). In particular, the emergence of objective markers in the domain of the acoustic discomfort threshold was examined. Methods: A cohort of 27 adults with normal hearing, aged between 18 and 30, participated in the study. The participants were presented with 500 ms long noise stimuli via in-ear headphones. The acoustic signals were presented with sound levels of [55, 65, 75, 85, 95 dB]. After each stimulus, the subjects provided their subjective assessment of the perceived loudness using a colored scale on a touchscreen. EEG signals were recorded, and afterward, event-related potentials (ERPs) locked to sound onset were analyzed. Results: Our findings reveal a linear dependency between the N100 component and both the sound level and the subjective loudness categorization of the sound. Additionally, the data demonstrated a nonlinear relationship between the P300 potential and the sound level as well as for the subjective loudness rating. The P300 potential was elicited exclusively when the stimuli had been subjectively rated as ”very loud” or ”too loud”. Conclusion: The findings of the present study suggest the possibility of the identification of the subjective uncomfortable loudness level by objective neural parameters.

• P300 potential as a marker for the subjective loudness perception. • Event-related potentials show a relation to uncomfortably loud stimuli. • The P300 potential could serve as a tool for objectively assessing discomfort levels in infants or adult people who cannot self-report. In this study, the objectification of the subjective perception of loudness was investigated using electroencephalography (EEG). In particular, the emergence of objective markers in the domain of the acoustic discomfort threshold was examined. A cohort of 27 adults with normal hearing, aged between 18 and 30, participated in the study. The participants were presented with 500 ms long noise stimuli via in-ear headphones. The acoustic signals were presented with sound levels of [55, 65, 75, 85, 95 dB]. After each stimulus, the subjects provided their subjective assessment of the perceived loudness using a colored scale on a touchscreen. EEG signals were recorded, and afterward, event-related potentials (ERPs) locked to sound onset were analyzed. Our findings reveal a linear dependency between the N100 component and both the sound level and the subjective loudness categorization of the sound. Additionally, the data demonstrated a nonlinear relationship between the P300 potential and the sound level as well as for the subjective loudness rating. The P300 potential was elicited exclusively when the stimuli had been subjectively rated as "very loud" or "too loud". The findings of the present study suggest the possibility of the identification of the subjective uncomfortable loudness level by objective neural parameters. [ABSTRACT FROM AUTHOR]

Recent functional MRI (fMRI) studies have highlighted differences in responses to natural sounds along the rostral-caudal axis of the human superior temporal gyrus. However, due to the indirect nature of the fMRI signal, it has been challenging to relate these fMRI observations to actual neuronal response properties. To bridge this gap, we present a forward model of the fMRI responses to natural sounds combining a neuronal model of the auditory cortex with physiological modeling of the hemodynamic BOLD response. Neuronal responses are modeled with a dynamic recurrent firing rate model, reflecting the tonotopic, hierarchical processing in the auditory cortex along with the spectro-temporal tradeoff in the rostral-caudal axis of its belt areas. To link modeled neuronal response properties with human fMRI data in the auditory belt regions, we generated a space of neuronal models, which differed parametrically in spectral and temporal specificity of neuronal responses. Then, we obtained predictions of fMRI responses through a biophysical model of the hemodynamic BOLD response (P-DCM). Using Bayesian model comparison, our results showed that the hemodynamic BOLD responses of the caudal belt regions in the human auditory cortex were best explained by modeling faster temporal dynamics and broader spectral tuning of neuronal populations, while rostral belt regions were best explained through fine spectral tuning combined with slower temporal dynamics. These results support the hypotheses of complementary neural information processing along the rostral-caudal axis of the human superior temporal gyrus.

Recent functional MRI (fMRI) studies have highlighted differences in responses to natural sounds along the rostral-caudal axis of the human superior temporal gyrus. However, due to the indirect nature of the fMRI signal, it has been challenging to relate these fMRI observations to actual neuronal response properties. To bridge this gap, we present a forward model of the fMRI responses to natural sounds combining a neuronal model of the auditory cortex with physiological modeling of the hemodynamic BOLD response. Neuronal responses are modeled with a dynamic recurrent firing rate model, reflecting the tonotopic, hierarchical processing in the auditory cortex along with the spectro-temporal tradeoff in the rostral-caudal axis of its belt areas. To link modeled neuronal response properties with human fMRI data in the auditory belt regions, we generated a space of neuronal models, which differed parametrically in spectral and temporal specificity of neuronal responses. Then, we obtained predictions of fMRI responses through a biophysical model of the hemodynamic BOLD response (P-DCM). Using Bayesian model comparison, our results showed that the hemodynamic BOLD responses of the caudal belt regions in the human auditory cortex were best explained by modeling faster temporal dynamics and broader spectral tuning of neuronal populations, while rostral belt regions were best explained through fine spectral tuning combined with slower temporal dynamics. These results support the hypotheses of complementary neural information processing along the rostral-caudal axis of the human superior temporal gyrus. [ABSTRACT FROM AUTHOR]