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 ( = 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.

中文翻译：

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个体内大脑信号变异性的更大上调使得老年人的高负荷认知任务更加艰巨

老年人在不同认知负荷下大脑反应不太明显的程度被称为神经去分化。脑信号的瞬时变异性作为一项新兴指标，不仅揭示了个体大脑作为个体间特征的适应性，而且还揭示了由于不断变化的任务需求而导致个体内部神经资源的分配，从而摆脱了新的认知。深入了解神经去分化的过程。然而，个体内大脑信号变异性的调节如何反映与认知要求高的任务相关的行为差异仍不清楚。在这项研究中，我们采用功能性近红外光谱 (fNIRS) 成像来捕获静息状态和 n-back 任务 (= 1, 2, 3) 期间大脑信号的变化，并通过标准差进行量化在 57 名健康老年人中。使用多元偏最小二乘 (PLS) 分析，我们发现 fNIRS 信号变异性从静息状态到任务状态增加，并且随着老年人的工作记忆负载而增加。我们进一步证实，更大的 fNIRS 信号变异性通常支持在 2-back 和 3-back 条件下更快、更稳定的响应时间。然而，个体内水平分析表明，fNIRS 信号变异性随认知负荷的上调越大，其准确性下降越多，平均反应时间增加，这表明个体内大脑信号变异性上调越大，可能反映了认知负荷对 fNIRS 信号变异性的影响。神经信息处理效率下降。总而言之，我们的研究结果为大脑信号变异性的本质提供了新的见解，表明个体间和个体内的大脑信号变异性可能预示着不同的理论结构。