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Touching events predict human action segmentation in brain and behavior
NeuroImage ( IF 5.7 ) Pub Date : 2021-08-29 , DOI: 10.1016/j.neuroimage.2021.118534
Jennifer Pomp 1 , Nina Heins 1 , Ima Trempler 1 , Tomas Kulvicius 2 , Minija Tamosiunaite 3 , Falko Mecklenbrauck 4 , Moritz F Wurm 5 , Florentin Wörgötter 6 , Ricarda I Schubotz 1
Affiliation  

Recognizing the actions of others depends on segmentation into meaningful events. After decades of research in this area, it remains still unclear how humans do this and which brain areas support underlying processes. Here we show that a computer vision-based model of touching and untouching events can predict human behavior in segmenting object manipulation actions with high accuracy. Using this computational model and functional Magnetic Resonance Imaging (fMRI), we pinpoint the neural networks underlying this segmentation behavior during an implicit action observation task. Segmentation was announced by a strong increase of visual activity at touching events followed by the engagement of frontal, hippocampal and insula regions, signaling updating expectation at subsequent untouching events. Brain activity and behavior show that touching-untouching motifs are critical features for identifying the key elements of actions including object manipulations.



中文翻译:

感人事件预测大脑和行为中的人类行为分割

识别他人的行为取决于分割成有意义的事件。在这一领域进行了数十年的研究之后,仍然不清楚人类是如何做到这一点的,以及哪些大脑区域支持潜在的过程。在这里,我们展示了基于计算机视觉的触摸和非触摸事件模型可以预测人类在分割对象操作动作时的高精度行为。使用这种计算模型和功能性磁共振成像 (fMRI),我们在隐式动作观察任务期间查明了这种分割行为背后的神经网络。分割是通过在触摸事件中视觉活动的强烈增加以及随后额叶、海马和岛叶区域的参与来宣布的,这表明对后续非接触事件的期望更新。

更新日期:2021-09-01
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