The only assumptions for mapping the connectivity of the NFBs are that each RGC-AC NFB segment is connected to at least 1 other RGC-AC NFB segment and that the final NFB segment is the most nasal column of the NFB regions. Otherwise, no assumptions are made about the location, trajectory, shape, or path of the RGC-AC NFB segments. For each NFB region, we located the path of neighboring NFB regions (ie, RGC-AC segments) that had the highest cumulative correlation among all possible RGC-AC paths. The most nasal regions were excluded from this computation. We use an A graph search method17 that is capable of finding an optimal path with the minimum “cost” (highest r2 value) from a starting node to one of the ending nodes. Each region of the NFB grid represents a “node” in the graph; starting nodes were node (x, y) (1 ≤ x ≤ 11, 1 ≤ y ≤ 10), and ending nodes were node (x, y) (x = 12, 1 ≤ y ≤ 10). Using arcs, a graph was constructed by connecting node (x, y) with nodes (x + 1, y − 2), (x + 1, y − 1), (x + 1, y), (x + 1, y + 1), and (x + 1, y + 2) (1 ≤ x ≤ 11; 1 ≤ y − 2, y − 1, y, y + 1, y + 2 ≤ 10). The cost of each edge in the graph was calculated as follows: Cost (a, b) = 1 − r2(a, b), where r2(a, b) is the Pearson product moment correlation coefficient of the regional mean NFL thickness between nodes a and b. The connectivity map is created by displaying the minimum cost path for each NFL region as a line, with the color corresponding to the magnitude of the r2 value.