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Recent studies have shown that, instead, of a dichotomy between parallel and serial search strategies, in many instances we see a combination of both search strategies utilized. Consequently, computational models and theoretical accounts of visual search processing have evolved from traditional serial-parallel descriptions to a continuum from ‘efficient’ to ‘inefficient’ search. One of the findings, consistent with this blurring of the serial–parallel distinction, is that concurrent spoken linguistic input influences the efficiency of visual search. In our first experiment we replicate those findings using a between-subjects design. Next, we utilize a localist attractor network to simulate the results from the first experiment, and then employ the network to make quantitative predictions about the influence of subtle timing differences of real-time language processing on visual search. These model predictions are then tested and …