Meso Andrew Isaac, Vacher Jonathan, Gekas Nikos, Mamassian Pascal, Perrinet Laurent U, Masson Guillaume S
Neuroimaging Department, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK.
MAP5, Université Paris Cité, CNRS, Paris, France.
J Vis. 2025 Sep 2;25(11):2. doi: 10.1167/jov.25.11.2.
The visual systems of animals work in diverse and constantly changing environments where organism survival requires effective senses. To study the hierarchical brain networks that perform visual information processing, vision scientists require suitable tools, and Motion Clouds (MCs)-a dense mixture of drifting Gabor textons-serve as a versatile solution. Here, we present an open toolbox intended for the bespoke use of MC functions and objects within modeling or experimental psychophysics contexts, including easy integration within Psychtoolbox or PsychoPy environments. The toolbox includes output visualization via a Graphic User Interface. Visualizations of parameter changes in real time give users an intuitive feel for adjustments to texture features like orientation, spatiotemporal frequencies, bandwidth, and speed. Vector calculus tools serve the frame-by-frame autoregressive generation of fully controlled stimuli, and use of the GPU allows this to be done in real time for typical stimulus array sizes. We give illustrative examples of experimental use to highlight the potential with both simple and composite stimuli. The toolbox is developed for, and by, researchers interested in psychophysics, visual neurophysiology, and mathematical and computational models. We argue the case that in all these fields, MCs can bridge the gap between well- parameterized synthetic stimuli like dots or gratings and more complex and less controlled natural videos.
动物的视觉系统在多样且不断变化的环境中运作，而生物体的生存需要有效的感官。为了研究执行视觉信息处理的层级式脑网络，视觉科学家需要合适的工具，而运动云（MCs）——一种由漂移的伽柏纹理元组成的密集混合物——就是一种通用的解决方案。在这里，我们展示了一个开放的工具箱，旨在供在建模或实验心理物理学环境中定制使用MC函数和对象，包括能轻松集成到Psychtoolbox或PsychoPy环境中。该工具箱包括通过图形用户界面进行输出可视化。实时的参数变化可视化让用户能直观地感受对诸如方向、时空频率、带宽和速度等纹理特征的调整。向量微积分工具用于逐帧自回归生成完全可控的刺激，并且使用图形处理器（GPU）能针对典型的刺激阵列大小实时完成此操作。我们给出实验用途的示例，以突出简单和复合刺激的潜力。该工具箱是为对心理物理学、视觉神经生理学以及数学和计算模型感兴趣的研究人员开发的，也是由他们开发的。我们认为在所有这些领域中，MCs能够弥合像点或光栅这样参数化良好的合成刺激与更复杂且控制较少的自然视频之间的差距。
