The spatial embedding of the cortical connectome reflects the fact that the probability of connectivity is determined by interareal distance, which determines the spatial embedding of the cerebral cortex thereby having a profound impact on the cortical connectome across primates and rodents. Further exploring the spatial embedding of the cortex in the non-human primate will allow improving our understanding of inter-areal connectivity. To further this aim we are developing technology allowing combining MRI imaging and tract tracing in macaque in order to create template surface connectivity maps that will facilitate major advances with respect to existing connectomes. Further, we are developing a machine leaning approaches to predict connections, that will enable us to propose complete graphs of the interareal cortical graph. With our CONNECTOMICS platform in SBRI Lyon and its mirror platform at ION Shanghai we have considerably expanded our inter-areal data base. This will enable us to pursue the following Objectives: (i) Generating a novel area-based connectivity data base. We shall use surface mapping and template to propose flexible data base that can adapt to changing criteria of cortical areas. With outside funding we are developing a comprehensive multimodal macaque atlas that will incorporate spatial transcriptomics. We shall incorporate the connectivity data into this atlas and examine the network properties of the data; (ii) To make progress in cortical connectomics we need to go beyond connectomes based on cortical areas. We will developing super dense inter-areal connectivity maps. A triangulated surface template mesh will used to create 350-500µm2 regions of interest (ROIs) on surface mapped connectivity. Theoretically, these so-defined ROIs will have strength-distance relations that are considerably more sharply defined, and predictability greatly enhanced. ROI clustering analysis will allow us to examine the contribution of quantitative connectivity measures along with spatial transcriptomics to areal identity and establish an edge-complete graph of the cortex; (ii) Explore visuospatial patterning of the cortical connectome. Numerous connectomes assume the fovea as a proxy for the early visual areas. However, because connectivity in the cortex obeys a strict distance rule, peripheral representations of the cortex connect very differently from that of the fovea. Multiple injections of retrograde tracers in retinal subdivisions of early visual areas show eccentricity-specific feedback connectivity profiles from extensive regions of the cortex. We shall complement this connectivity with the connectivity from (i) above to address the visuospatial patterning exploiting graph theoretic measures to better understand information flow in the macaque connectome.