Figure 1. Experimental Setup. (A) An example of the first few steps of a graph traversal defined by a walk on the graph. Top: Each node is uniquely associated with a key combination, and the sequence of key combinations is determined by a walk on the graph. Bottom: A series of trials are presented to the participant. The red squares indicate which keys to press on that trial. Colored arrows illustrate the edge from the graph at top being traversed. However, the participant only is shown the five squares. (B) The mapping between fingers and keys, and average reaction times for each key press. Top: A schematic of the mapping between visual stimuli (squares) and response effectors (fingers). Bottom: The average reaction time (RT) for each key or pair of keys across all data. The diagonal elements of the matrix represent trials in which a single key was pressed, and the off-diagonal elements of the matrix represent trials in which a pair of keys was pressed. (C) The three graph structures that we examine in this study. From left to right, we show a modular graph, a lattice graph, and a random graph with N = 15 nodes connected by E = 30 edges. a series of cycles, each of which visited every node on the graph exactly once. Each cycle was randomly generated starting from a node adjacent from the endpoint of the previous cycle. Graphs: We compared learning rates across 3 different graph topologies, each consisting of 15 nodes and 30 edges: a modular graph, a lattice graph, and a random graph (Fig.1C). Briefly, 5/29 H J K L Space A C 721 859 1074 1073 964 765 897 1043 1094 804 946 1181 847 1036 809 L K H J Space Finger 1 RT (ms) H K J L Space B 1200 950 700 Trial Node 3 1 4 3 5 1 2 3 4 5 . . . . . . 5 1 4 2 3