Modelling of Cognitive Processes, Technical University of Berlin, Berlin, Germany.
Bernstein Center for Computational Neuroscience, Berlin, Germany.
Elife. 2022 Apr 20;11:e76096. doi: 10.7554/eLife.76096.
Sensory systems reliably process incoming stimuli in spite of changes in context. Most recent models accredit this context invariance to an extraction of increasingly complex sensory features in hierarchical feedforward networks. Here, we study how context-invariant representations can be established by feedback rather than feedforward processing. We show that feedforward neural networks modulated by feedback can dynamically generate invariant sensory representations. The required feedback can be implemented as a slow and spatially diffuse gain modulation. The invariance is not present on the level of individual neurons, but emerges only on the population level. Mechanistically, the feedback modulation dynamically reorients the manifold of neural activity and thereby maintains an invariant neural subspace in spite of contextual variations. Our results highlight the importance of population-level analyses for understanding the role of feedback in flexible sensory processing.
感觉系统能够可靠地处理传入的刺激，而不受上下文变化的影响。最近的模型将这种上下文不变性归因于在分层前馈网络中提取越来越复杂的感觉特征。在这里，我们研究了如何通过反馈而不是前馈处理来建立上下文不变的表示。我们表明，受反馈调制的前馈神经网络可以动态生成不变的感觉表示。所需的反馈可以作为缓慢和空间扩散的增益调制来实现。不变性不存在于单个神经元的水平上，而是仅在群体水平上出现。从机制上讲，反馈调制动态地重新定向神经活动的流形，从而在上下文变化的情况下保持不变的神经子空间。我们的结果强调了群体水平分析对于理解反馈在灵活的感觉处理中的作用的重要性。
