Synergistic Processing of Visual Contours across Cortical Layers in V1 and V2

Visual cortical areas are interconnected via layer-specific feedforward and feedback projections. Such intricate connections are thought to be essential for parsing complex visual images, but the synergy among different layers in different cortical areas remains unclear. By simultaneously mapping neuronal activities across cortical depths in V1 and V2 of behaving monkeys, we identified spatiotemporally dissociable processes for grouping contour fragments and segregating background components. These processes generated and amplified contour signals within specific layers in V1 and V2. Contour-related inter-areal interactions, measured as Granger causality, were also dominant between these cortical layers within a time window when the contour signals were rapidly augmented. The grouping process became much faster for isolated contour elements compared with visual contours embedded in a complex background. Our results delineate the mode whereby image components are grouped and segmented through synergistic inter-laminar and inter-areal processes that are dynamically adjusted during interpretation of sensory inputs. By simultaneously mapping neuronal activities across cortical layers in monkey V1 and V2, Chen et al. show how image components are grouped and segregated through inter-areal and inter-laminar interactions, highlighting the dynamics and complexity of multilayered information processing.