Department of Informatics, Bioengineering, Robotics, and Systems Engineering, University of Genova, Genoa, Italy.
Department of Neuroscience and Movement Science, University of Fribourg, Fribourg, Switzerland.
Front Neural Circuits. 2019 Oct 30;13:68. doi: 10.3389/fncir.2019.00068. eCollection 2019.
Spatial orientation relies on a representation of the position and orientation of the body relative to the surrounding environment. When navigating in the environment, this representation must be constantly updated taking into account the direction, speed, and amplitude of body motion. Visual information plays an important role in this updating process, notably via optical flow. Here, we systematically investigated how the size and the simulated portion of the field of view (FoV) affect perceived visual speed of human observers. We propose a computational model to account for the patterns of human data. This model is composed of hierarchical cells' layers that model the neural processing stages of the dorsal visual pathway. Specifically, we consider that the activity of the MT area is processed by populations of modeled MST cells that are sensitive to the differential components of the optical flow, thus producing selectivity for specific patterns of optical flow. Our results indicate that the proposed computational model is able to describe the experimental evidence and it could be used to predict expected biases of speed perception for conditions in which only some portions of the visual field are visible.
空间定位依赖于身体相对于周围环境的位置和方向的表示。当在环境中导航时，必须根据身体运动的方向、速度和幅度不断更新此表示。视觉信息在这个更新过程中起着重要作用，特别是通过光流。在这里，我们系统地研究了大小和模拟视场 (FoV) 的部分如何影响人类观察者感知的视觉速度。我们提出了一个计算模型来解释人类数据的模式。该模型由分层细胞层组成，模拟了背侧视觉通路的神经处理阶段。具体来说，我们认为 MT 区域的活动是由对光流的差分成分敏感的模拟 MST 细胞群体处理的，从而产生对特定光流模式的选择性。我们的结果表明，所提出的计算模型能够描述实验证据，并且可以用于预测在只有部分视野可见的情况下对速度感知的预期偏差。
