Complementary congruent and opposite neurons achieve concurrent multisensory integration and segregation
Complementary congruent and opposite neurons achieve concurrent multisensory integration and segregation
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作者：
Zhang, Wen-Hao;Wang, He;Wu, Si
我们的大脑通过利用多感官线索来提取关于外部刺激的各个方面的信息来感知世界。来自同一刺激的感觉线索应该被整合以改善感知，否则应该被分离以区分不同的刺激。然而，在现实中，大脑面临着在事先不知道感官线索来源的情况下识别刺激的挑战。为了应对这一挑战，我们建议大脑与互补神经元同时进行整合和分离。研究了通过视觉和前庭线索对航向的推断，我们开发了一个网络模型，该模型具有两个相互作用的视觉前庭区域。在每个模块中，有两组神经元，它们在每个感觉线索下的调谐要么一致，要么相反。我们发现，一致的神经元实现整合，而相反的神经元计算线索差异信息隔离，两组神经元之间的相互作用实现了有效的多感官信息处理。
Our brain perceives the world by exploiting multisensory cues to extract information about various aspects of external stimuli. The sensory cues from the same stimulus should be integrated to improve perception, and otherwise segregated to distinguish different stimuli. In reality, however, the brain faces the challenge of recognizing stimuli without knowing in advance the sources of sensory cues. To address this challenge, we propose that the brain conducts integration and segregation concurrently with complementary neurons. Studying the inference of heading-direction via visual and vestibular cues, we develop a network model with two reciprocally connected modules modeling interacting visual-vestibular areas. In each module, there are two groups of neurons whose tunings under each sensory cue are either congruent or opposite. We show that congruent neurons implement integration, while opposite neurons compute cue disparity information for segregation, and the interplay between two groups of neurons achieves efficient multisensory information processing.