The influence of visual training on predicting complex action sequences
The influence of visual training on predicting complex action sequences
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DOI：
10.1002/hbm.21450
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发表时间：
2013-02-01
影响因子：
4.8
通讯作者：
Prinz, Wolfgang
中科院分区：
文献类型：
--
作者：
Cross, Emily S.;Stadler, Waltraud;Prinz, Wolfgang
连接观察到的和可执行的行动似乎是通过行动观察网络（AON），包括顶叶，运动前区，和枕颞皮层区域的人类大脑。在动作观察期间的AON参与被认为有助于轻松、有效地预测正在进行的动作，以支持动作理解。在这里，我们调查如何AON响应时，观察和预测的行动，我们不能轻易再现之前和之后的视觉训练。在训练前和训练后的神经成像会议期间，参与者观察体操运动员和发条玩具在封堵器后面移动，并在他们期望每个代理重新出现时按下按钮。在扫描过程之间，参与者接受视觉训练，以预测刺激的子集何时会再次出现。训练后扫描显示，与感知相比，当预测闭塞动作时，顶叶下部、上级颞叶和小脑皮质的激活。更大的活动出现时，预测未经训练的相比，训练序列在枕颞叶皮质和运动前皮质在较小程度上。在预测未经训练的代理时，枕颞叶反应表现出进一步的专业化，在预测体操运动员的动作时，身体处理区域内的反应更大，在预测玩具的动作时，对象选择皮质中的反应更大。结果表明：（1）AON的选择部分被招募来预测不容易映射到观察者身体上的复杂运动;（2）这些AON区域的更多招募支持对不太熟悉的序列的预测。我们认为，研究结果通知前运动模型的行动预测和预测编码帐户的AON功能。^Brain Mapp，2013. (C)2011 Wiley Periodicals，Inc.
Linking observed and executable actions appears to be achieved by an action observation network (AON), comprising parietal, premotor, and occipitotemporal cortical regions of the human brain. AON engagement during action observation is thought to aid in effortless, efficient prediction of ongoing movements to support action understanding. Here, we investigate how the AON responds when observing and predicting actions we cannot readily reproduce before and after visual training. During pre- and posttraining neuroimaging sessions, participants watched gymnasts and wind-up toys moving behind an occluder and pressed a button when they expected each agent to reappear. Between scanning sessions, participants visually trained to predict when a subset of stimuli would reappear. Posttraining scanning revealed activation of inferior parietal, superior temporal, and cerebellar cortices when predicting occluded actions compared to perceiving them. Greater activity emerged when predicting untrained compared to trained sequences in occipitotemporal cortices and to a lesser degree, premotor cortices. The occipitotemporal responses when predicting untrained agents showed further specialization, with greater responses within body-processing regions when predicting gymnasts' movements and in object-selective cortex when predicting toys' movements. The results suggest that (1) select portions of the AON are recruited to predict the complex movements not easily mapped onto the observer's body and (2) greater recruitment of these AON regions supports prediction of less familiar sequences. We suggest that the findings inform both the premotor model of action prediction and the predictive coding account of AON function. Hum Brain Mapp, 2013. (C) 2011 Wiley Periodicals, Inc.