If A > B, and B > C, it follows logically that A > C. The process of reaching that conclusion is called transitive inference (TI). Several mechanisms have been offered to explain transitive performance. Scanning models claim that the list is scanned from the ends of the list inward until a match is found. Positional discrimination models claim that positional uncertainty accounts for accuracy and reaction time patterns. In Experiment 1, we trained rhesus monkeys (Macaca mulatta) and humans (Homo sapiens) on adjacent pairs (e.g., AB, BC, CD, DE, EF) and tested them with previously untrained nonadjacent pairs (e.g., BD). In Experiment 2, we trained a second list and tested with nonadjacent pairs selected between lists (e.g., B from List 1, D from List 2). We then introduced associative competition between adjacent items in Experiment 3 by training 2 items per position (e.g., B₁C₁, B₂C₂) before testing with untrained nonadjacent items. In all 3 experiments, humans and monkeys showed distance effects in which accuracy increased, and reaction time decreased, as the distance between items in each pair increased (e.g., BD vs. BE). In Experiment 4, we trained adjacent pairs with separate 9- and 5-item lists. We then tested with nonadjacent pairs selected between lists to determine whether list items were chosen according to their absolute position (e.g., D, 5-item list > E, 9-item list), or their relative position (e.g., D, 5-item list < E, 9-item list). Both monkeys' and humans' choices were most consistent with a relative positional organization.
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http://dx.doi.org/10.1037/a0021572 | DOI Listing |
J Mol Med (Berl)
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