ABSTRACT
The complex connectivity structure unique to the brain network is believed to underlie its robust and efficient coding capability. One of many unique features of the mammalian cortico-thalamic network is its hierarchical organization. I will discuss functional implications of the hierarchical structure of mammalian cortical network in the framework of predictive coding. Specifically, I will focus on a hierarchical predictive coding model of visual cortex to understand how robust encoding of noisy visual stimuli emerges, and further discuss distinct computations carried out by layer-specific feedforward and feedback connections in the cortical hierarchy. In the second part of the talk, I will discuss how various visual stimuli shape the complexity of functional networks of neural activity by analyzing their network properties.