The notion that the mammalian cortex is hierarchically organized, by function, is an enduring (Felleman, Siegle) and powerful idea in systems neuroscience. Importantly, this concept of "hierarchy" is (recent network REF) used in multiple, and sometimes contradictory, ways. The ways it is commonly used are: 1. 2. 3. For example, anatomy (Mihalas, Harris) supports a hierarchical clustering, but not the notion of strict hierarchy. We take first the notion of strict visual hierarchy, and explore the effect of "non-hierarchical" interaction by removing heirarchical *edges* while preserving node activity that can underlie other, non-hierarchical edges (see Klingenstein application). Such an approach would suggest the following hypothesis: Inactivation of bottleneck nodes to an area (e.g. AM), whether ouput (PM) or bottleneck edges (V1-AM) will fully suppress the output of the visual system dependent on activity in that area. To test this, it is required that: 1. the output behavior depend on the area (see Glickfeld lab data, but also Histed lab data). 2. The inputs and output edges can be independently controlled. 3. Using our behavioral and physiological platform, we are assessing the adherence of mamallian visual activity to this organization (topography). Several alternative hypothesis are concurrently being explored, including models of statistical hierarchy and "flat" or non-hierarchical / distributed computation.