fNIRS-Based Dynamic Functional Connectivity Reveals the Innate Musical Sensing Brain Networks in Preterm Infants

The impact of internet pornography addiction on brain function: a functional near-infrared spectroscopy study

Introduction

There is extensive awareness of internet pornography addiction. It not only affects the mental health of adolescents but also promotes criminal activity. However, the impact of internet pornography addiction on functional in the brain remains unclear.

Methods

16 healthy college students and five college students with severe internet pornography addiction were invited to participate in the experiment and watch a pornographic video. Functional near-infrared spectroscopy (fNIRS) was used to measure the dynamic changes in hemoglobin in the brain during a 10 min session of viewing internet pornography. Participants completed the Stroop Color and Word Task (SCWT) before and after they had watched the video. Facial expressions and life signs were measured continuously during the experiment.

Results

Compared with the group that frequently viewed pornographic videos, the group with low-frequency pornography viewing exhibited enhanced functional connectivity in the inferior prefrontal cortex and pars triangularis of Broca's area in the frontal lobe, the primary somatosensory cortex in the parietal lobe, and the pre-motor and supplementary motor cortices. Moreover, the high-frequency pornography-viewing group exhibited hyperactive parasympathetic activity, more pronounced sexual arousal, and stronger functional connectivity in the dorsolateral prefrontal cortex and frontopolar area. After viewing the pornography, the high-frequency group demonstrated longer reaction times and significantly reduced accuracy while completing the Stroop Color and Word Test (SCWT) compared to the low-frequency group and also their own performance before and after viewing the pornography.

Discussion

This study demonstrated the hyperactive and inhibited brain areas under the impact of pornography video addiction. The results may strengthen our understanding of neurobiology and facilitate the development of prevention policies for adolescents.

An alternating breathing pattern significantly affects the brain functional connectivity and mood states

Introduction

To explore the impact of different breathing patterns on brain connectivity and emotional states.

Methods

We recruited 31 participants with an average age of 19 years. They were instructed to perform controlled breathing, including calm, shallow, deep, and alternating deep and shallow breathing patterns. We employed functional near-infrared spectroscopy (fNIRS) to investigate disparities in the effects of multiple breathing patterns on the brain. Meanwhile, we captured the participants' facial expressions and vital signs.

Results

There were significant variations in the effects of four breathing patterns on functional connectivity between brain regions, facial expressions, and vital signs. The four breathing patterns impacted six brain regions. Among them, alternating deep and shallow breathing had a particularly pronounced effect, and there was robust functional connectivity in different brain regions. Additionally, this breathing pattern elevated autonomic nervous system activity, which contributed to achieving a more tranquil state. Furthermore, alternating deep and shallow breathing had a more positive influence on the changes in oxyhaemoglobin concentration (Δ [HbO2]) of the brain compared with deep breathing.

Discussion

Alternating shallow and deep breathing could enhance emotional stability, improve autonomic nervous system function, and promote brain functional connectivity. Our findings unveiled distinct effects of diverse breathing patterns on both the brain and mood state, establishing a theoretical foundation for respiratory rehabilitation training for stroke patients.

DFC-Igloo: A dynamic functional connectome learning framework for identifying neurodevelopmental biomarkers in very preterm infants

BACKGROUND AND OBJECTIVE

Very preterm infants are susceptible to neurodevelopmental impairments, necessitating early detection of prognostic biomarkers for timely intervention. The study aims to explore possible functional biomarkers for very preterm infants at born that relate to their future cognitive and motor development using resting-state fMRI. Prior studies are limited by the sample size and suffer from efficient functional connectome (FC) construction algorithms that can handle the noisy data contained in neonatal time series, leading to equivocal findings. Therefore, we first propose an enhanced functional connectome construction algorithm as a prerequisite step. We then apply the new FC construction algorithm to our large prospective very preterm cohort to explore multi-level neurodevelopmental biomarkers.

METHODS

There exists an intrinsic relationship between the structural connectome (SC) and FC, with a notable coupling between the two. This observation implies a putative property of graph signal smoothness on the SC as well. Yet, this property has not been fully exploited for constructing intrinsic dFC. In this study, we proposed an advanced dynamic FC (dFC) learning model, dFC-Igloo, which leveraged SC information to iteratively refine dFC estimations by applying graph signal smoothness to both FC and SC. The model was evaluated on artificial small-world graphs and simulated graph signals.

RESULTS

The proposed model achieved the best and most robust recovery of the ground truth graph across different noise levels and simulated SC pairs from the simulation. The model was further applied to a cohort of very preterm infants from five Neonatal Intensive Care Units, where an enhanced dFC was obtained for each infant. Based on the improved dFC, we identified neurodevelopmental biomarkers for neonates across connectome-wide, regional, and subnetwork scales.

CONCLUSION

The identified markers correlate with cognitive and motor developmental outcomes, offering insights into early brain development and potential neurodevelopmental challenges.

Understanding the Effect of Listening to Music, Playing Music, and Singing on Brain Function: A Scoping Review of fNIRS Studies

Music is integrated into daily life when listening to it, playing it, and singing, uniquely modulating brain activity. Functional near-infrared spectroscopy (fNIRS), celebrated for its ecological validity, has been used to elucidate this music-brain interaction. This scoping review synthesizes 22 empirical studies using fNIRS to explore the intricate relationship between music and brain function. This synthesis of existing evidence reveals that diverse musical activities, such as listening to music, singing, and playing instruments, evoke unique brain responses influenced by individual traits and musical attributes. A further analysis identifies five key themes, including the effect of passive and active music experiences on relevant human brain areas, lateralization in music perception, individual variations in neural responses, neural synchronization in musical performance, and new insights fNIRS has revealed in these lines of research. While this review highlights the limited focus on specific brain regions and the lack of comparative analyses between musicians and non-musicians, it emphasizes the need for future research to investigate the complex interplay between music and the human brain.

The underlying roles and neurobiological mechanisms of music-based intervention in Alzheimer's disease: A comprehensive review

Non-pharmacological therapy has gained popularity in the intervention of Alzheimer's disease (AD) due to its apparent therapeutic effectiveness and the limitation of biological drug. A wealth of research indicates that music interventions can enhance cognition, mood and behavior in individuals with AD. Nonetheless, the underlying mechanisms behind these improvements have yet to be fully and systematically delineated. This review aims to holistically review how music-based intervention (MBI) ameliorates abnormal emotion, cognition decline, and behavioral changes in AD patients. We cover several key dimensions: the regulation of MBIs on cerebral blood flow (CBF), their impact on neurotransmission (including GABAergic and monoaminergic transmissions), modulation of synaptic plasticity, and hormonal release. Additionally, we summarize the clinical applications and limitations of active music-based intervention (AMBI), passive music-based intervention (PMBI), and hybrid music-based intervention (HMBI). This thorough analysis enhances our understanding of the role of MBI in AD and supports the development of non-pharmacological therapeutic strategies.