Greater up-modulation of intra-individual brain signal variability makes a high-load cognitive task more arduous for older adults

任务(项目管理) 静息状态功能磁共振成像 功能近红外光谱 大脑活动与冥想 信号(编程语言) 调制(音乐) 认知 工作记忆 基本认知任务 神经科学 心理学 计算机科学 听力学 脑电图 医学 前额叶皮质 程序设计语言 管理 经济 哲学 美学
作者
Hong Li,Ying Han,Haijing Niu
出处
期刊:NeuroImage [Elsevier BV]
卷期号:: 120577-120577
标识
DOI:10.1016/j.neuroimage.2024.120577
摘要

The extent to which brain responses are less distinctive across varying cognitive loads in older adults is referred to as neural dedifferentiation. Moment-to-moment brain signal variability, an emerging indicator, reveals not only the adaptability of an individual's brain as an inter-individual trait, but also the allocation of neural resources within an individual due to ever-changing task demands, thus shedding novel insight into the process of neural dedifferentiation. However, how the modulation of intra-individual brain signal variability reflects behavioral differences related to cognitively demanding tasks remains unclear. In this study, we employed functional near-infrared spectroscopy (fNIRS) imaging to capture the variability of brain signals, which was quantified by the standard deviation, during both the resting state and an n-back task (n=1, 2, 3) in 57 healthy older adults. Using multivariate Partial Least Squares (PLS) analysis, we found that fNIRS signal variability increased from the resting state to the task and increased with working memory load in older adults. We further confirmed that greater fNIRS signal variability generally supported faster and more stable response time in the 2- and 3-back conditions. However, the intra-individual level analysis showed that the greater the up-modulation in fNIRS signal variability with cognitive loads, the more its accuracy decreases and mean response time increases, suggesting that a greater intra-individual brain signal variability up-modulation may reflect decreased efficiency in neural information processing. Taken together, our findings offer new insights into the nature of brain signal variability, suggesting that inter- and intra-individual brain signal variability may index distinct theoretical constructs.

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