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The emulation theory of representation: Motor control, imagery, and perception

机译:表示的仿真理论:运动控制,图像和感知

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The emulation theory of representation is developed and explored as a framework that can revealingly synthesize a wide variety of representational functions of the brain. The framework is based on constructs from control theory (forward models) and signal processing (Kalman filters). The idea is that in addition to simply engaging with the body and environment, the brain constructs neural circuits that act as models of the body and environment. During overt sensorimotor engagement, these models are driven by efference copies in parallel with the body and environment, in order to provide expectations of the sensory feedback, and to enhance and process sensory information. These models can also be run off-line in order to produce imagery, estimate outcomes of different actions, and evaluate and develop motor plans. The framework is initially developed within the context of motor control, where it has been shown that inner models running in parallel with the body can reduce the effects of feedback delay problems. The same mechanisms can account for motor imagery as the off-line driving of the emulator via efference copies. The framework is extended to account for visual imagery as the off-line driving of an emulator of the motor-visual loop. I also show how such systems can provide for amodal spatial imagery. Perception, including visual perception, results from such models being used to form expectations of, and to interpret, sensory input. 1 close by briefly outlining other cognitive functions that might also be synthesized within this framework, including reasoning, theory of mind phenomena, and language.
机译:表示的仿真理论是作为框架开发和探索的,可以揭示大脑的各种表示功能。该框架基于控制理论(正向模型)和信号处理(卡尔曼滤波器)的构造。这个想法是,除了简单地与身体和环境互动之外,大脑还可以构建神经回路,充当人体和环境的模型。在公开的感觉运动参与过程中,这些模型由与人体和环境平行的引用副本驱动,以提供对感觉反馈的期望,并增强和处理感觉信息。这些模型也可以离线运行,以生成图像,估计不同动作的结果以及评估和制定运动计划。该框架最初是在电机控制的背景下开发的,该研究表明,与人体平行运行的内部模型可以减少反馈延迟问题的影响。相同的机制可以通过仿制副本将电机图像解释为仿真器的离线驱动。该框架已扩展为将视觉图像作为电机视觉回路仿真器的离线驱动来考虑。我还将展示此类系统如何提供无模态空间图像。包括视觉感知在内的感知是这些模型的结果,这些模型被用来形成对感觉输入的期望并对其进行解释。 1通过简要概述在此框架内也可以综合的其他认知功能来结束,包括推理,心理现象理论和语言。

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