Task-based functional connectivity in infants after exposure to regular white noise during natural sleep measured by fNIRS

The infant brain is primitive and immature. Investigating changes in the brain during infants' rapid developmental stages has been a research hotspot. However, due to the unique characteristics of the infant population, maintaining an absolute resting state is limited. Consequently, studies comparing differences between absolute resting-state and task-state brain networks are extremely difficult. Therefore, studying infant brain networks during sleep has become a promising direction. Based on adult studies, task-state brain networks demonstrate stronger behavioral correlations, but research on differences between task-state and resting-state brain networks reveals individual variability. This study provides evidence for individual differences in infant brain networks transitioning from the resting-state to the task-state during sleep. Furthermore, it analyzes differences in graph-theoretical brain network properties among groups with different response types. This work establishes a scientific basis for future investigations into the differences between task-state and resting-state brain networks in sleeping infants exposed to various stimuli. The goal is to find intuitive methods that can reveal individual sensitivity to stimuli and group individuals based on different response types, in order to study the connectivity of brain networks corresponding to different response patterns. A total of 21 normally developing infants were included in the study. All infants underwent 5 min of resting-state data collection after naturally falling asleep, followed by 15 s of white noise stimulation and 20 s of rest, repeated for 5 cycles in the task-state. The task frequency was kept constant at 0.0286 Hz. We developed an intuitive approach to assess individual responses to stimuli, characterized by the sparsity of Pearson correlation coefficients across distinct narrow frequency bands. This method revealed three distinct response patterns: Sensitive-Positive, Sensitive-Negative, and Insensitive. Upon analyzing the sparsity associated with these response patterns, we observed that the reduction in functional connectivity during task engagement may be linked to interference between the task-related frequency and the individual's baseline cognitive frequency. Furthermore, when examining brain network properties through graph-theoretical analysis, we found that individuals exhibiting stronger small-worldness in the resting-state tended to show heightened sensitivity to stimuli. Different individual infants show different changes in brain functional connectivity after receiving the same stimulus. Different response types should be analyzed separately.

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Journal
Scientific Reports
Published
2025-08-12
DOI
https://doi.org/10.1038/s41598-025-14774-7
Primary Topic
Functional Brain Connectivity Studies
Type
article
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article

Task-based functional connectivity in infants after exposure to regular white noise during natural sleep measured by fNIRS

Yong Zhang, Zhaohui Wang, Kun Li
1 links
Scientific Reports
Functional Brain Connectivity Studies
article

Task-based functional connectivity in infants after exposure to regular white noise during natural sleep measured by fNIRS

Yong Zhang, Zhaohui Wang, Kun Li
article en

Abstract

The infant brain is primitive and immature. Investigating changes in the brain during infants' rapid developmental stages has been a research hotspot. However, due to the unique characteristics of the infant population, maintaining an absolute resting state is limited. Consequently, studies comparing differences between absolute resting-state and task-state brain networks are extremely difficult. Therefore, studying infant brain networks during sleep has become a promising direction. Based on adult studies, task-state brain networks demonstrate stronger behavioral correlations, but research on differences between task-state and resting-state brain networks reveals individual variability. This study provides evidence for individual differences in infant brain networks transitioning from the resting-state to the task-state during sleep. Furthermore, it analyzes differences in graph-theoretical brain network properties among groups with different response types. This work establishes a scientific basis for future investigations into the differences between task-state and resting-state brain networks in sleeping infants exposed to various stimuli. The goal is to find intuitive methods that can reveal individual sensitivity to stimuli and group individuals based on different response types, in order to study the connectivity of brain networks corresponding to different response patterns. A total of 21 normally developing infants were included in the study. All infants underwent 5 min of resting-state data collection after naturally falling asleep, followed by 15 s of white noise stimulation and 20 s of rest, repeated for 5 cycles in the task-state. The task frequency was kept constant at 0.0286 Hz. We developed an intuitive approach to assess individual responses to stimuli, characterized by the sparsity of Pearson correlation coefficients across distinct narrow frequency bands. This method revealed three distinct response patterns: Sensitive-Positive, Sensitive-Negative, and Insensitive. Upon analyzing the sparsity associated with these response patterns, we observed that the reduction in functional connectivity during task engagement may be linked to interference between the task-related frequency and the individual's baseline cognitive frequency. Furthermore, when examining brain network properties through graph-theoretical analysis, we found that individuals exhibiting stronger small-worldness in the resting-state tended to show heightened sensitivity to stimuli. Different individual infants show different changes in brain functional connectivity after receiving the same stimulus. Different response types should be analyzed separately.

Scientific ReportsVol. 15(1)
Xi’an Children’s Hospital (CN)
Openalex Percentile: Top 80%
Functional Brain Connectivity Studies
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