Feedforward and feedback frequency-dependent interactions in a large-scale laminar network of the primate cortex
Interactions between top-down and bottom-up processes in the cerebral cortex hold the key to understanding predictive coding, executive control and a gamut of other brain functions. The underlying circuit mechanism, however, remains poorly understood and represents a major challenge in neuroscience. In the present work we tackled this problem using a large-scale computational model of the primate cortex constrained by new directed and weighted connectivity data. In our model, the interplay between feedforward and feedback signaling depends on the cortical laminar structure and involves complex dynamics across multiple (intra-laminar, inter-laminar, inter-areal and whole cortex) scales. The model was tested by reproducing, and shedding insights into, a wide range of neurophysiological findings about frequency-dependent interactions between visual cortical areas: feedforward pathways are associated with enhanced gamma (30-70 Hz) oscillations, whereas feedback projections selectively modulate alpha/low beta (8-15 Hz) oscillations. We found that in order for the model to account for the experimental observations, the feedback projection needs to predominantly target infragranular layers in a target area, which leads to a proposed circuit substrate for predictive coding. The model reproduces a functional hierarchy based on frequency-dependent Granger causality analysis of inter-areal signaling, as reported in recent monkey and human experiments. Taken together, this work highlights the importance of multi-scale approaches and provides a modeling platform for studies of large-scale brain circuit dynamics and functions.