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First, we found that human participants associate semantically related words more easily than unrelated words; this advantage increased linearly with repeated co\u2010occurrence. Second, we developed a computational model, SEMANT, suggesting a possible mechanism for this semantic\u2010episodic interaction. In SEMANT, episodic associations are implemented through lateral connections between nodes in a pre\u2010existent self\u2010organized map of word semantics. These connections are strengthened at each instance of concomitant activation, proportionally with the amount of the overlapping activity waves of activated nodes. 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