Georgiev Christian, Legrand Thomas, Mongold Scott J, Fiedler-Valenta Manoa, Guittard Frédéric, Bourguignon Mathieu
Laboratory of Neurophysiology and Movement Biomechanics, UNI - ULB Neuroscience Institute, Université Libre de Bruxelles (ULB), Brussels, Belgium.
Laboratoire de Neuroanatomie et Neuroimagerie Translationnelles, UNI - ULB Neuroscience Institute, Université Libre de Bruxelles (ULB), Brussels, Belgium.
Front Psychol. 2024 Sep 25;15:1407458. doi: 10.3389/fpsyg.2024.1407458. eCollection 2024.
Video presentation has become ubiquitous in paradigms investigating the neural and behavioral responses to observed actions. In spite of the great interest in uncovering the processing of observed bodily movements and actions in neuroscience and cognitive science, at present, no standardized set of video stimuli for action observation research in neuroimaging settings exists. To facilitate future action observation research, we developed an open-access database of 135 high-definition videos of a male actor performing object-oriented actions. Actions from 3 categories: kinematically natural and goal-intact (), kinematically unnatural and goal-intact (), or kinematically natural and goal-violating (), directed toward 15 different objects were filmed from 3 angles. Psychometric evaluation of the database revealed high video recognition accuracy ( accuracy = 88.61 %) and substantial inter-rater agreement (Fleiss' = 0.702), establishing excellent validity and reliability. Videos' exact timing of motion onset was identified using a custom motion detection frame-differencing procedure. Based on its outcome, the videos were edited to assure that motion begins at the second frame of each video. The videos' timing of category recognition was also identified using a novel behavioral up-down staircase procedure. The identified timings can be incorporated in future experimental designs to counteract jittered stimulus onsets, thus vastly improving the sensitivity of neuroimaging experiments. All videos, their psychometric evaluations, and the timing of their frame of category recognition, as well as our custom programs for performing these evaluations on our, or on other similar video databases, are available at the Open Science Framework (https://osf.io/zexc4/).
在研究对观察到的动作的神经和行为反应的范式中,视频呈现已变得无处不在。尽管神经科学和认知科学对揭示观察到的身体运动和动作的处理过程有着浓厚兴趣,但目前在神经成像环境中不存在用于动作观察研究的标准化视频刺激集。为了促进未来的动作观察研究,我们开发了一个开放获取的数据库,其中包含一名男性演员执行面向对象动作的135个高清视频。拍摄了针对15个不同物体的3类动作:运动学上自然且目标完整的()、运动学上不自然且目标完整的()或运动学上自然且目标违反的(),并从3个角度进行拍摄。对该数据库的心理测量评估显示出高视频识别准确率(准确率 = 88.61%)和较高的评分者间一致性(Fleiss' = 0.702),确立了良好的有效性和可靠性。使用定制的运动检测帧差程序确定视频运动开始的确切时间。根据其结果,对视频进行编辑以确保运动在每个视频的第二帧开始。还使用一种新颖的行为上下阶梯程序确定视频类别识别的时间。所确定的时间可纳入未来的实验设计中,以抵消刺激起始的抖动,从而极大地提高神经成像实验的敏感性。所有视频、它们的心理测量评估、类别识别帧的时间,以及我们用于在我们自己的或其他类似视频数据库上进行这些评估的定制程序,均可在开放科学框架(https://osf.io/zexc4/)上获取。