Sparse Deep Predictive Coding captures contour integration capabilities of the early visual system

Understand

Both neurophysiological and psychophysical experiments have pointed out the crucial role of recurrent and feedback connections to process context-dependent information in the early visual cortex.

• While numerous models have accounted for feedback effects at either neural or representational level, none of them were able to bind those two levels of analysis.
• Is it possible to describe feedback effects at both levels using the same model? We answer this question by combining Predictive Coding (PC) and Sparse Coding (SC) into a hierarchical and convolutional framework.
• In this Sparse Deep Predictive Coding (SDPC) model, the SC component models the internal recurrent processing within each layer, and the PC component describes the interactions between layers using feedforward and feedback connections.