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.

中文翻译：

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一种受生物学启发的模型，用于预测感知视觉速度作为视野刺激部分的函数。

空间方向依赖于身体相对于周围环境的位置和方向的表示。在环境中导航时，必须考虑身体运动的方向、速度和幅度，不断更新这种表示。视觉信息在这个更新过程中发挥着重要作用，特别是通过光流。在这里，我们系统地研究了视场 (FoV) 的大小和模拟部分如何影响人类观察者的感知视觉速度。我们提出了一种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微分成分敏感的建模 MST 细胞群处理的，从而对光流的特定模式产生选择性。我们的结果表明，所提出的计算模型能够描述实验证据，并且可用于预测仅视野的某些部分可见的条件下速度感知的预期偏差。