Unlocking neural complexity with a robotic key.
Unlocking neural complexity with a robotic key.
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用机器人钥匙解锁神经的复杂性。
DOI：
10.1113/jp271444
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发表时间：
2016
期刊：
影响因子：
--
通讯作者：
Milford,Michael
中科院分区：
文献类型：
--
作者：
Stratton,Peter;Hasselmo,Michael;Milford,Michael
复杂的大脑进化是为了理解现实世界中的复杂环境并与之互动。尽管我们对大脑感知表征的理解取得了重大进展，但我们对大脑如何进行更高级别处理的理解仍然很肤浅。这种脱节是可以理解的，因为感觉输入到感知状态的直接映射很容易观察到，而处理（未知）阶段和中间神经状态之间的映射却不容易观察到。我们认为，在现实世界中测试机器人的高级神经处理理论提供了一条清晰的前进道路，因为（1）神经机器人控制器的复杂性可以根据需要进行分级，避免了即使是当前最简单的活体神经系统中几乎难以处理的复杂性； （2）机器人控制器状态是完全可观察的，避免了从完整完整的大脑中记录的巨大技术挑战； (3) 与计算建模不同，使用机器人时，现实世界可以独立存在，从而避免了在任意细节级别模拟世界的计算困难性。我们建议，拥抱机器人神经控制器和物理世界之间复杂且常常不可预测的闭环交互，将有助于更深入地理解复杂的大脑功能在高级信息处理和行为控制中的作用。
Complex brains evolved in order to comprehend and interact with complex environments in the real world. Despite significant progress in our understanding of perceptual representations in the brain, our understanding of how the brain carries out higher level processing remains largely superficial. This disconnect is understandable, since the direct mapping of sensory inputs to perceptual states is readily observed, while mappings between (unknown) stages of processing and intermediate neural states is not. We argue that testing theories of higher level neural processing on robots in the real world offers a clear path forward, since (1) the complexity of the neural robotic controllers can be staged as necessary, avoiding the almost intractable complexity apparent in even the simplest current living nervous systems; (2) robotic controller states are fully observable, avoiding the enormous technical challenge of recording from complete intact brains; and (3) unlike computational modelling, the real world can stand for itself when using robots, avoiding the computational intractability of simulating the world at an arbitrary level of detail. We suggest that embracing the complex and often unpredictable closed‐loop interactions between robotic neuro‐controllers and the physical world will bring about deeper understanding of the role of complex brain function in the high‐level processing of information and the control of behaviour.