**Knowing in advance what to look for speeds up search, but how this knowledge guides search is poorly understood. The little available evidence suggests that previewing the target produces larger reductions in search times for harder searches. To investigate this issue further, we performed seven experiments in which subjects searched for an oddball target after previewing the target, distracter, or an unrelated square. Consistent with previous studies, harder searches showed bigger reductions in search time for an informative preview. However, the same data replotted using the reciprocal of search time showed a remarkably different result: The informative preview showed a fixed additive increase in reciprocal search time across all searches regardless of difficulty. This is a nontrivial outcome because it cannot be explained using a simple relationship between search times in the informative and uninformative preview conditions. We interpret our findings by proposing that the reciprocal of search time reflects the strength of an underlying accumulating signal related to the distinctiveness or salience of the target over the distracters and that preview additively increases this signal for all searches. This in turn implies that the top-down signals related to target preview and bottom-up signals related to target-distracter salience sum linearly.**

*Across all experiments, we obtained essentially the same result: Although harder searches showed larger decreases in search time when the target was previewed, the same data replotted in terms of 1/RT showed a fixed offset across all searches. This is a nontrivial result because it cannot be explained by a simple transformation of search times*. For instance, if RTu and RTi denote the search time in the unrelated and informative priming conditions, then halving all the unrelated preview search times (RTi = RTu/2) would cause a doubling of the reciprocal search times (1/RTi = 2/RTu) but not a fixed offset. Across all experiments, we also quantitatively evaluated these two models by comparing their residual error and found that the 1/RT offset model has a consistently smaller error compared to the RT scaling model. In Experiment 9, we show through simulations that these results can be explained by an additive but not multiplicative increase in distinctiveness even after taking into account fixed effects such as motor response latency. Taken together, our results show that previewing a target or a distractor additively increases the underlying dissimilarity signal in visual search.

^{16}C

_{2}= 120 pairs). For each pair of images (A, B), subjects performed eight correct trials (four with A as target, which comprised two trials with A on the left and two with A on the right, and four with B as target). Thus, for each priming condition (target preview and unrelated preview) there were 120 × 8 = 960 trials, resulting in a total of 1,920 correct trials. These trials appeared in random order.

*regress*).

*p*= 0.98, chi-squared test). Thus, there was no significant tendency for some searches to be consistently benefited by preview across independent sets of trials. In other words, the target preview benefit is present in some pairs but not others due to random noise and not because some pairs show a consistent preview benefit compared to others. In any case, the constant offset in 1/RT was present in both searches with significant preview benefit and across all searches (Tables 1 and 2).

*p*< 0.00005, paired

*t*test). Although this could, in principle, reflect differences between subjects, it is unlikely because search times in the two experiments in the unrelated preview conditions were strongly correlated (

*r*= 0.94,

*p*< 0.00005 across 120 searches).

*r*= 0.72,

*p*< 0.00005). We conclude that confirming the absence of a previewed target in an array of distractors is driven by the dissimilarity between the previewed target and the distractors.

*n*= 18) and hard searches (

*n*= 15). We can see that the hard searches are benefited more by target preview, but again, the same data plotted using 1/RT show a fixed preview benefit (Figure 7A, B).

*σ*= 0.033). A response was recorded when the accumulator level reached a value of one. The standard deviation of the Gaussian noise was chosen to match the linear relationship between mean and standard deviation observed in the real data in Experiment 1 (

*σ*

_{RT}= 0.75

*μ*

_{RT}− 0.24, where

*σ*

_{RT}and

*μ*

_{RT}are the standard deviation and mean of the observed RTs across subjects and trials). For the unrelated preview condition, we chose a total of 120 values of bottom-up saliences (ranging from 0.0025 to 0.01 in equal steps) and created 72 simulated search times for each search pair (corresponding to nine subjects with eight trials each as in Experiment 1). For the target preview condition, we incremented all bottom-up salience values in the unrelated preview condition by a fixed value of 0.00045 (this value was chosen to match the observed slope of 0.79 between target and unrelated priming RT in Experiment 1; see Figure 2A).

*r*= 0.99,

*p*< 0.00005; Figure 11B). We conclude that 1/RT provides an unbiased estimate of the underlying salience signal even for a stochastic accumulator at least within the range relevant to the observed data.

*r*= 0.98,

*p*< 0.00005; Figure 11C). But importantly, when the same data was replotted using 1/RT, we observed a clear constant offset (best-fitting slope = 0.98 with [0.94, 1.01] as the 95% confidence interval; offset = 0.11 with [0.07, 0.16] as the 95% confidence interval; Figure 11D). We conclude that a fixed increase in 1/RT due to target preview can be observed due to an additive gain in bottom-up salience even for a stochastic accumulator process.

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