High and low pitch sound stimuli effects on heart-brain coupling

This study aimed to explore the influence of sound stimulation on heart rate and the potential coupling between cardiac and cerebral activities. Thirty-one participants underwent exposure to periods of silence and two distinct continuous, non-repetitive pure tone stimuli: low pitch (110 Hz) and high pitch (880 Hz). Electroencephalography (EEG) data from electrodes F3, F4, F7, F8, Fp1, Fp2, T3, T4, T5, and T6 were recorded, along with R-R interval data for heart rate. Heart-brain connectivity was assessed using wavelet coherence between heart rate variability (HRV) and EEG envelopes (EEGE). Heart rates were significantly lower during high and low-pitch sound periods than in silence (p < 0.002). HRV-EEGE coherence was significantly lower during high-pitch intervals than silence and low-pitch sound intervals (p < 0.048), specifically between the EEG Beta band and the low-frequency HRV range. These results imply a differential involvement of the frontal and temporal brain regions in response to varying auditory stimuli. Our findings highlight the essential nature of discerning the complex interrelations between sound frequencies and their implications for heart-brain connectivity. Such insights could have ramifications for conditions like seizures and sleep disturbances. A deeper exploration is warranted to decipher specific sound stimuli's potential advantages or drawbacks in diverse clinical scenarios.

Relationship between Subjective and Biological Responses to Comfortable and Uncomfortable Sounds

Various kinds of biological sensors are now embedded in wearable devices and data on human biological information have recently become more widespread. Among various environmental stressors, sound has emotional and biological impacts on humans, and it is worthwhile to investigate the relationship between the subjective impressions of and biological responses to such sounds. In this study, the relationship between subjective and biological responses to acoustic stimuli with two contrasting kinds of sounds, a murmuring river sound and white noise, was investigated. The subjective and biological responses were measured during the presentation of the sounds. Compared with the murmuring river sound, the white noise had a significantly decreased EEG-related index of α-EEG and HRV-related index of SD2/SD1. The correlation between each index of subjective and biological responses indicated that α-EEG was highly correlated with the results of subjective evaluation. However, based on a more detailed analysis with clustering, some subjects showed different biological responses in each trial since they felt the sound was powerful when listening to the murmuring river sound, as well as feeling that it was beautiful. It was suggested that biological responses to sound exposure may be affected by the impression of the sound, which varies by individual.

Interpreting null models of resting-state functional MRI dynamics: not throwing the model out with the hypothesis

Null models are useful for assessing whether a dataset exhibits a non-trivial property of interest. These models have recently gained interest in the neuroimaging community as means to explore dynamic properties of functional Magnetic Resonance Imaging (fMRI) time series. Interpretation of null-model testing in this context may not be straightforward because (i) null hypotheses associated to different null models are sometimes unclear and (ii) fMRI metrics might be 'trivial', i.e. preserved under the null hypothesis, and still be useful in neuroimaging applications. In this commentary, we review several commonly used null models of fMRI time series and discuss the interpretation of the corresponding tests. We argue that, while null-model testing allows for a better characterization of the statistical properties of fMRI time series and associated metrics, it should not be considered as a mandatory validation step to assess their relevance in representing brain functional dynamics.