Time-Perception Network and Default Mode Network Are Associated with Temporal Prediction in a Periodic Motion Task
Time-Perception Network and Default Mode Network Are Associated with Temporal Prediction in a Periodic Motion Task
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DOI：
10.3389/fnhum.2016.00268
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发表时间：
2016-06-02
影响因子：
2.9
通讯作者：
de Araujo, Draulio B.
中科院分区：
文献类型：
--
作者：
Carvalho, Fabiana M.;Chaim, Khallil T.;de Araujo, Draulio B.
为了准确预测未来的观测结果，有必要更新预期的内部模型。不确定性驱动的内部模型更新已被研究使用各种感知范式，并揭示了参与额顶叶区。在不同的文献中，时间期望的研究也具有时间感知网络的特征，它依赖于注意力的时间定向。然而，前瞻性内部模型的更新高度依赖于时间注意，因为时间注意必须根据当前的环境需求重新定位。在这项研究中，我们使用功能性磁共振成像（fMRI）来评估在何种程度上持续操纵时间预测将招募更新相关区域和时间感知网络区域。我们开发了一个外源性的时间任务，结合节奏提示和时间接触的原则，以产生内隐的时间期望。创建了两种运动模式：周期性（简谐振动）和非周期性（变加速度的简谐振动）。我们发现，非周期性运动从事外源性的时间定向网络，其中包括腹侧前运动和下顶叶皮质，小脑，以及presupplementary运动区，这在以前已经牵连到内部模型更新，和运动敏感区MT+。有趣的是，我们发现右半球的优势表明参与明确的计时机制。我们还表明，周期性运动的条件下，相比于非周期性运动，激活了一个特定的子集的默认模式网络（DMN）中线区域，包括左背内侧前额叶皮层（DMPFC），前扣带皮层（ACC），和双边后扣带皮层/楔前叶（PCC/PC）。它表明，DMN在处理上下文预期信息中发挥作用，并支持最近的证据表明，DMN可能反映了前瞻性内部模型和预测控制的验证。总而言之，我们的研究结果表明，持续操纵的时间预测从事的时间预测以及任务独立的内部模型更新的表示。
The updating of prospective internal models is necessary to accurately predict future observations. Uncertainty-driven internal model updating has been studied using a variety of perceptual paradigms, and have revealed engagement of frontal and parietal areas. In a distinct literature, studies on temporal expectations have also characterized a time-perception network, which relies on temporal orienting of attention. However, the updating of prospective internal models is highly dependent on temporal attention, since temporal attention must be reoriented according to the current environmental demands. In this study, we used functional magnetic resonance imaging (fMRI) to evaluate to what extend the continuous manipulation of temporal prediction would recruit update-related areas and the time-perception network areas. We developed an exogenous temporal task that combines rhythm cueing and time-to-contact principles to generate implicit temporal expectation. Two patterns of motion were created: periodic (simple harmonic oscillation) and non-periodic (harmonic oscillation with variable acceleration). We found that non-periodic motion engaged the exogenous temporal orienting network, which includes the ventral premotor and inferior parietal cortices, and the cerebellum, as well as the presupplementary motor area, which has previously been implicated in internal model updating, and the motion-sensitive area MT+. Interestingly, we found a right-hemisphere preponderance suggesting the engagement of explicit timing mechanisms. We also show that the periodic motion condition, when compared to the non-periodic motion, activated a particular subset of the default-mode network (DMN) midline areas, including the left dorsomedial prefrontal cortex (DMPFC), anterior cingulate cortex (ACC), and bilateral posterior cingulate cortex/precuneus (PCC/PC). It suggests that the DMN plays a role in processing contextually expected information and supports recent evidence that the DMN may reflect the validation of prospective internal models and predictive control. Taken together, our findings suggest that continuous manipulation of temporal predictions engages representations of temporal prediction as well as task-independent updating of internal models.