意识状态调节节律性时间注意: 来自行为、分层漂移扩散模型与脑电指标的证据

doi:10.3724/SP.J.1041.2026.0450

摘要/Abstract

摘要：

时间注意是指个体根据刺激发生的时间优先处理信息的能力, 对日常生活中的行为反应至关重要。然而, 节律性时间注意是否受意识状态调控尚不明确。本研究通过高频闪烁技术操纵视觉节律刺激被感知的意识状态水平, 将行为测量、分层漂移扩散模型(hierarchical drift-diffusion model, HDDM)分析与事件相关电位和时频分析技术相结合, 系统考察了意识状态对节律性时间注意的调节作用以及节律线索在亚秒与超秒时间尺度上的加工机制差异。实验1结果表明, 节律线索在有、无意识状态下均能引发时间注意效应, 但效应在无意识条件下显著减弱。HDDM分析进一步揭示, 有意识状态下节律线索能降低个体的决策边界, 提示其激活了决策层面的内源性加工, 而无意识状态下该效应不显著。实验2在此基础上发现, CNV成分与α震荡抑制均在有意识条件下更为显著, 进一步支持意识状态通过调节认知准备和注意维持机制增强时间注意效应。此外, 尽管节律线索时间间隔(ISI)不影响时间注意效应的强度, 但超秒间隔条件下整体反应更快, 支持时间认知分段综合模型的预测。综上, 节律性时间注意不仅依赖外在节奏驱动, 也可能涉及基于意识水平调节的内源性决策机制。

关键词: 节律线索, 时间注意, 意识状态, 分层漂移扩散模型, CNV

Abstract:

Temporal cues enable individuals to anticipate upcoming events, thereby facilitating goal-directed behavior. While temporal association cues are known to engage endogenous temporal attention that is modulated by conscious perception, it remains unclear whether rhythmic cues—typically considered to evoke exogenous temporal attention—are similarly affected by the state of consciousness. Addressing this gap, the present study investigated whether rhythmic temporal attention is subject to modulation by conscious awareness and whether it involves endogenous cognitive components akin to those recruited by symbolic temporal cues.

Two experiments were conducted, each involving 24 different Chinese participants and comprising three conditions: (a) a rhythmic cueing task under conscious perception, (b) the same task under unconscious perception manipulated via high-frequency flicker (50 Hz), and (c) a two-alternative forced-choice awareness check. Experiment 2 replicated the design of Experiment 1 with simultaneous EEG recordings. Participants performed an orientation discrimination task in rhythmic versus random cue conditions, with inter-stimulus intervals (ISIs) of either 800 ms or 1300 ms to compare sub-second and supra-second timing.

Behavioral results showed robust temporal attention effects in both conscious and unconscious states, though significantly larger under conscious perception. ERP analyses revealed that rhythmic cues elicited greater contingent negative variation (CNV) amplitudes when participants were conscious, indicating enhanced temporal preparation at the neural level. Hierarchical drift-diffusion modeling (HDDM) further showed that under conscious perception, rhythmic cues reduced decision boundaries, suggesting more confident and efficient decision-making—a hallmark of endogenous control. These effects were absent under unconscious conditions. Additionally, faster responses in supra-second versus sub-second intervals support the segmented timing hypothesis and indicate that longer temporal contexts may recruit higher-order cognitive processes. Importantly, time−frequency analysis revealed stronger alpha-band (8~12 Hz) suppression during the rhythmic encoding phase under conscious perception, particularly over frontal and occipital regions, with wider spatial distribution in the supra-second interval. This enhanced alpha desynchronization suggests greater attentional engagement and top-down modulation of sensory areas, supporting the notion that conscious perception of rhythmic structure facilitates the neural entrainment of anticipatory attention.

Together, these findings challenge the view that rhythmic temporal attention is purely exogenous, showing instead that it contains an endogenous component that is modulated by the state of consciousness. This study provides converging behavioral, electrophysiological, and computational evidence for a dual-process account of rhythmic temporal attention and offers novel insights into the interaction between temporal structure and awareness in shaping anticipatory cognition.

Key words: rhythmic cues, temporal attention, consciousness states, hierarchical drift-diffusion modeling, contingent negative variation

中图分类号:

B842

梁星杰, 陈慧芳, 王璐瑶, 孙彦良. (2026). 意识状态调节节律性时间注意: 来自行为、分层漂移扩散模型与脑电指标的证据. 心理学报, 58(3), 450-466.

LIANG Xingjie, CHEN Huifang, WANG Luyao, SUN Yanliang. (2026). Modulation of rhythmic temporal attention by conscious awareness: Evidence from behavior, hierarchical drift-diffusion modeling, and EEG measures. Acta Psychologica Sinica, 58(3), 450-466.

图/表 19

图1 实验1流程图注: 该流程图为示意图, 正式实验中屏幕背景为灰色, 光栅、注视点等刺激的参数以文字描述为准。

图2 实验1a和1b的反应时结果注: *表示p < 0.05, **表示p < 0.01, ***表示p < 0.001, n.s.表示无显著差异。误差线代表被试内95%的置信区间。

图3 实验1时间注意效应结果注: **表示p < 0.01。误差线代表被试内95%的置信区间。彩图见电子版, 下同

表1 实验1中随意识状态和线索呈现方式变化的模型参数和ΔDIC

模型	随条件变化的参数	ΔDIC
Model_a	a	0
Model_v	v	138.6
Model_t	t	325.8

图4 实验1对意识状态和线索呈现方式的hddm拟合结果注: 左图为参数的后验分布图, 右图为群体水平参数均值柱状图。*表示p < 0.05, n.s.表示无显著差异。

表2 实验1中随ISI变化的模型参数和ΔDIC

模型	随条件变化的参数	ΔDIC
Model_a	a	7.7
Model_v	v	0
Model_t	t	34.4

图5 实验1对ISI的hddm拟合结果注：左图为参数的后验分布图, 右图为群体水平参数均值柱状图。n.s.表示无显著差异。

图6 实验2a和2b的反应时结果注: ***表示p < 0.001, n.s.表示无显著差异。误差线代表被试内95%的置信区间。

图7 实验2时间注意效应结果注: *表示p < 0.05。误差线代表被试内95%的置信区间。

表3 实验2中随意识状态和线索呈现方式变化的模型参数和ΔDIC

模型	随条件变化的参数	ΔDIC
Model_a	a	0.4
Model_v	v	0
Model_t	t	80.9

图8 实验2对意识状态和线索呈现方式的HDDM拟合结果注：左图为参数的后验分布图, 右图为群体水平参数均值柱状图。*表示p < 0.05, n.s.表示无显著差异。

表4 实验2中随ISI变化的模型参数和ΔDIC

模型	随条件变化的参数	ΔDIC
Model_a	a	40.5
Model_v	v	74
Model_t	t	0

图9 实验2对ISI的HDDM拟合结果注: 左图为参数的后验分布图, 右图为群体水平参数均值柱状图。n.s.表示无显著差异。

表5 实验2中随意识状态和ISI变化的模型参数和ΔDIC

模型	随条件变化的参数	ΔDIC
Model_a	a	62.2
Model_v	v	0
Model_t	t	135.3

图10 实验2对意识状态和ISI的HDDM拟合结果注: 左图为参数的后验分布图, 右图为群体水平参数均值柱状图。*表示p < 0.05, n.s.表示无显著差异。

图11 实验2不同条件下CNV差值波形图及地形图注: 图中蓝色实线代表有意识状态下的CNV差值(节律−随机), 橙色虚线代表无意识状态下的CNV差值; 蓝色、橙色阴影是误差线, 代表被试内95%的置信区间; 灰色阴影区域代表分析CNV的时间窗口; 右侧为不同意识状态和ISI条件下的CNV差值地形图(数据取自时间窗口内的差值均值)。

图12 实验2中CNV成分上的时间注意效应注: *表示p < 0.05, n.s.表示无显著差异。误差线代表被试内95%的置信区间。

图13 实验2编码阶段的α频段地形图以及时频图注: a图为α频段意识状态差值(有意识−无意识)地形图, 左图为800 ms ISI条件, 右图为1300 ms ISI条件。图a中的紫色圆点为b图时频分析中所挑选的额叶电极, 黄色圆点则为所挑选的枕叶电极。b图为不同时间间隔和脑区下的意识状态差值(有意识−无意识)时频图。

图14 实验2编码阶段的α频段功率图注: 图中蓝色实线代表有意识状态下的α频段功率, 橙色虚线代表无意识状态下的α频段功率; 蓝色、橙色阴影是误差线, 代表被试内95%的置信区间; 灰色阴影区域代表分析的时间窗口(1500~2500 ms)。*表示p < 0.05, ***表示p > 0.001。

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