Merfeld D M, Zupan L H
Department of Otology and Laryngology, Jenks Vestibular Physiology Laboratory, Massachusetts Eye and Ear Infirmary, Harvard Medical School, 243 Charles Street, Boston, MA 02114, USA.
J Neurophysiol. 2002 Feb;87(2):819-33. doi: 10.1152/jn.00485.2001.
All linear accelerometers measure gravitoinertial force, which is the sum of gravitational force (tilt) and inertial force due to linear acceleration (translation). Neural strategies must exist to elicit tilt and translation responses from this ambiguous cue. To investigate these neural processes, we developed a model of human responses and simulated a number of motion paradigms used to investigate this tilt/translation ambiguity. In this model, the separation of GIF into neural estimates of gravity and linear acceleration is accomplished via an internal model made up of three principal components: 1) the influence of rotational cues (e.g., semicircular canals) on the neural representation of gravity, 2) the resolution of gravitoinertial force into neural representations of gravity and linear acceleration, and 3) the neural representation of the dynamics of the semicircular canals. By combining these simple hypotheses within the internal model framework, the model mimics human responses to a number of different paradigms, ranging from simple paradigms, like roll tilt, to complex paradigms, like postrotational tilt and centrifugation. It is important to note that the exact same mechanisms can explain responses induced by simple movements as well as by more complex paradigms; no additional elements or hypotheses are needed to match the data obtained during more complex paradigms. Therefore these modeled response characteristics are consistent with available data and with the hypothesis that the nervous system uses internal models to estimate tilt and translation in the presence of ambiguous sensory cues.
所有线性加速度计都测量重力惯性力,它是重力(倾斜)和线性加速度(平移)引起的惯性力之和。必然存在神经策略来从这个模糊的线索中引发倾斜和平移反应。为了研究这些神经过程,我们开发了一个人类反应模型,并模拟了一些用于研究这种倾斜/平移模糊性的运动范式。在这个模型中,通过一个由三个主要成分组成的内部模型,将重力惯性力分离为对重力和线性加速度的神经估计:1)旋转线索(例如,半规管)对重力神经表征的影响,2)将重力惯性力分解为重力和线性加速度的神经表征,以及3)半规管动力学的神经表征。通过在内部模型框架内结合这些简单假设,该模型模仿了人类对许多不同范式的反应,从简单范式,如侧倾倾斜,到复杂范式,如旋转后倾斜和离心运动。需要注意的是,完全相同的机制可以解释由简单运动以及更复杂范式引起的反应;不需要额外的元素或假设来匹配在更复杂范式中获得的数据。因此,这些模拟的反应特征与现有数据一致,并且与神经系统在存在模糊感官线索时使用内部模型来估计倾斜和平移的假设一致。