Jeffery Kate J, Page Hector J I, Stringer Simon M
Institute of Behavioural Neuroscience, Department of Experimental Psychology, University College London, 26 Bedford Way, London, WC1H 0AP, UK.
Oxford Centre for Theoretical Neuroscience and Artificial Intelligence, Department of Experimental Psychology, University of Oxford, South Parks Road, Oxford, OX1 3UD, UK.
J Physiol. 2016 Nov 15;594(22):6527-6534. doi: 10.1113/JP272945. Epub 2016 Oct 5.
Maintaining a sense of direction requires combining information from static environmental landmarks with dynamic information about self-motion. This is accomplished by the head direction system, whose neurons - head direction cells - encode specific head directions. When the brain integrates information in sensory domains, this process is almost always 'optimal' - that is, inputs are weighted according to their reliability. Evidence suggests cue combination by head direction cells may also be optimal. The simplicity of the head direction signal, together with the detailed knowledge we have about the anatomy and physiology of the underlying circuit, therefore makes this system a tractable model with which to discover how optimal cue combination occurs at a neural level. In the head direction system, cue interactions are thought to occur on an attractor network of interacting head direction neurons, but attractor dynamics predict a winner-take-all decision between cues, rather than optimal combination. However, optimal cue combination in an attractor could be achieved via plasticity in the feedforward connections from external sensory cues (i.e. the landmarks) onto the ring attractor. Short-term plasticity would allow rapid re-weighting that adjusts the final state of the network in accordance with cue reliability (reflected in the connection strengths), while longer term plasticity would allow long-term learning about this reliability. Although these principles were derived to model the head direction system, they could potentially serve to explain optimal cue combination in other sensory systems more generally.
维持方向感需要将来自静态环境地标信息与关于自身运动的动态信息相结合。这是由头部方向系统完成的，其神经元——头部方向细胞——编码特定的头部方向。当大脑整合感觉领域的信息时，这个过程几乎总是“最优的”——也就是说，根据输入的可靠性对其进行加权。有证据表明，头部方向细胞进行的线索整合也可能是最优的。头部方向信号的简单性，以及我们对其基础神经回路的解剖学和生理学的详细了解，因此使这个系统成为一个易于处理的模型，通过它可以发现最优线索整合是如何在神经层面发生的。在头部方向系统中，线索交互作用被认为发生在相互作用的头部方向神经元的吸引子网络上，但吸引子动力学预测线索之间会有一个胜者全得的决策，而不是最优组合。然而，吸引子中的最优线索组合可以通过从外部感觉线索（即地标）到环形吸引子的前馈连接中的可塑性来实现。短期可塑性将允许快速重新加权，根据线索可靠性（反映在连接强度中）调整网络的最终状态，而长期可塑性将允许对这种可靠性进行长期学习。尽管这些原理是为模拟头部方向系统而推导出来的，但它们可能更普遍地有助于解释其他感觉系统中的最优线索组合。
