The brain attenuates its responses to self-produced exteroceptions (e.g., we cannot tickle ourselves). Is this phenomenon, known as sensory attenuation, enabled innately, or acquired through learning? Here, our simulation study using a multimodal hierarchical recurrent neural network model, based on variational free-energy minimization, shows that a mechanism for sensory attenuation can develop through learning of two distinct types of sensorimotor experience, involving self-produced or externally produced exteroceptions. For each sensorimotor context, a particular free-energy state emerged through interaction between top-down prediction with precision and bottom-up sensory prediction error from each sensory area. The executive area in the network served as an information hub. Consequently, shifts between the two sensorimotor contexts triggered transitions from one free-energy state to another in the network via executive control, which caused shifts between attenuating and amplifying prediction-error-induced responses in the sensory areas. This study situates emergence of sensory attenuation (or self-other distinction) in development of distinct free-energy states in the dynamic hierarchical neural system.
翻译:大脑可以减弱对自产外消毒的响应(例如,我们无法自我割裂 ) 。 这种现象是被称为感官衰减、本能增强,还是通过学习获得的? 在这里,我们使用基于变异自由能源最小化的多式联运等级经常性神经网络模型进行的模拟研究显示,感官衰减机制可以通过学习两种不同类型的感官机体验来发展,其中涉及自产或外部生成的外生消毒。对于每一种感官环境来说,特定的自由能源状态是通过每个感官地区的自上而下的预测与精确和自上而上的感官预测错误之间的相互作用而出现的。网络执行领域起到信息枢纽的作用。因此,两种感官机环境之间的转变引发了网络中从一个自由能源状态向另一个自由状态的转变,从而导致感官区域自产衰减和增强预测-机源诱发反应之间的转变。 这项研究将感官衰减(或自我区分)感官衰减(或自我区分)在不同的自由神经系统的开发中出现。