闭合多感觉交互的循环：多感觉因果推理和重新校准的神经结构
Closing the loop on multisensory interactions: A neural architecture for multisensory causal inference and recalibration
摘要：
当大脑接收来自多个感觉系统的输入时，它面临着这样一个问题：是否应该将这些输入组合起来处理，就好像它们来自同一个事件，或者分开处理，就好像它们来自不同的事件。此外，它还必须有一种机制，通过这种机制，它可以保持感官输入的校准，以保持其内部表征的准确性。我们已经开发出一个神经网络架构，能够i）近似最佳的多感官空间整合，基于贝叶斯因果推理，和ii）重新校准的空间编码的感觉系统。该架构是基于背侧处理层次结构的特征，包括单感觉神经元的空间调谐特性和多感觉神经元上不同感觉输入的收敛。此外，我们提出，这些unisensory和多感觉神经元发挥双重作用，i）编码空间位置作为单独或综合的估计和ii）积累证据的独立性或相关性的多感觉刺激。我们进一步提出，自上而下的反馈连接跨越背侧通路发挥关键的作用，在重新校准空间编码的水平，早期unisensory皮质。我们提出的架构提供了一些人类电生理和神经成像结果的可能解释，并产生可测试的预测神经生理学与行为。
英文摘要：
When the brain receives input from multiple sensory systems, it is faced with the question of whether it is appropriate to process the inputs in combination, as if they originated from the same event, or separately, as if they originated from distinct events. Furthermore, it must also have a mechanism through which it can keep sensory inputs calibrated to maintain the accuracy of its internal representations. We have developed a neural network architecture capable of i) approximating optimal multisensory spatial integration, based on Bayesian causal inference, and ii) recalibrating the spatial encoding of sensory systems. The architecture is based on features of the dorsal processing hierarchy, including the spatial tuning properties of unisensory neurons and the convergence of different sensory inputs onto multisensory neurons. Furthermore, we propose that these unisensory and multisensory neurons play dual roles in i) encoding spatial location as separate or integrated estimates and ii) accumulating evidence for the independence or relatedness of multisensory stimuli. We further propose that top-down feedback connections spanning the dorsal pathway play key a role in recalibrating spatial encoding at the level of early unisensory cortices. Our proposed architecture provides possible explanations for a number of human electrophysiological and neuroimaging results and generates testable predictions linking neurophysiology with behaviour.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
