Selective attention controls the distribution of our visual system's limited processing resources to stimuli in the visual field. Two independent parameters of visual selection can be quantified by modeling an individual's performance in a partial-report task based on the computational theory of visual attention (TVA): (i) top–down control α, the relative attentional weighting of relevant over irrelevant stimuli, and (ii) spatial bias w λ , the relative attentional weighting of stimuli in the left versus right hemifield. In this study, we found that visual event-related electroencephalographic lateralizations marked interindividual differences in these two functions. First, individuals with better top–down control showed higher amplitudes of the posterior contralateral negativity than individuals with poorer top–down control. Second, differences in spatial bias were reflected in asymmetries in earlier visual event-related lateralizations depending on the hemifield position of targets; specifically, individuals showed a positivity contralateral to targets presented in their prioritized hemifield and a negativity contralateral to targets presented in their nonprioritized hemifield. Thus, our findings demonstrate that two functionally different aspects of attentional weighting quantified in the respective TVA parameters are reflected in two different neurophysiological measures: The observer-dependent spatial bias influences selection by a bottom–up processing advantage of stimuli appearing in the prioritized hemifield. By contrast, task-related target selection governed by top–down control involves active enhancement of target, and/or suppression of distractor, processing. These results confirm basic assumptions of the TVA framework, complement the functional interpretation of event-related lateralization components in selective attention studies, and are of relevance for the development of neurocognitive attentional assessment procedures.

The redundant-signals effect (RSE) refers to a speed-up of RT when the response is triggered by two, rather than just one, response-relevant target elements. Although there is agreement that in the visual modality RSEs observed with dimensionally redundant signals originating from the same location are generated by coactive processing architectures, there has been a debate as to the exact stage(s)—preattentive versus postselective—of processing at which coactivation arises. To determine the origin(s) of redundancy gains in visual pop-out search, the present study combined mental chronometry with electrophysiological markers that reflect purely preattentive perceptual (posterior-contralateral negativity [PCN]), preattentive and postselective perceptual plus response selection-related (stimulus-locked lateralized readiness potential [LRP]), or purely response production-related processes (response-locked LRP). As expected, there was an RSE on target detection RTs, with evidence for coactivation. At the electrophysiological level, this pattern was mirrored by an RSE in PCN latencies, whereas stimulus-locked LRP latencies showed no RSE over and above the PCN effect. Also, there was no RSE on the response-locked LRPs. This pattern demonstrates a major contribution of preattentive perceptual processing stages to the RSE in visual pop-out search, consistent with parallel-coactive coding of target signals in multiple visual dimensions [Müller, H. J., Heller, D., & Ziegler, J. Visual search for singleton feature targets within and across feature dimensions. Perception & Psychophysics, 57, 1–17, 1995].

Processing of a given target is facilitated when it is defined within the same (e.g., visual–visual), compared to a different (e.g., tactile–visual), perceptual modality as on the previous trial [Spence, C., Nicholls, M., & Driver, J. The cost of expecting events in the wrong sensory modality. Perception & Psychophysics, 63, 330–336, 2001]. The present study was designed to identify electrocortical (EEG) correlates underlying this “modality shift effect.” Participants had to discriminate (via foot pedal responses) the modality of the target stimulus, visual versus tactile (Experiment 1), or respond based on the target-defining features (Experiment 2). Thus, modality changes were associated with response changes in Experiment 1, but dissociated in Experiment 2. Both experiments confirmed previous behavioral findings with slower discrimination times for modality change, relative to repetition, trials. Independently of the target-defining modality, spatial stimulus characteristics, and the motor response, this effect was mirrored by enhanced amplitudes of the anterior N1 component. These findings are explained in terms of a generalized “modality-weighting” account, which extends the “dimension-weighting” account proposed by Found and Müller [Searching for unknown feature targets on more than one dimension: Investigating a “dimension-weighting” account. Perception & Psychophysics, 58, 88–101, 1996] for the visual modality. On this account, the anterior N1 enhancement is assumed to reflect the detection of a modality change and initiation of the readjustment of attentional weight-setting from the old to the new target-defining modality in order to optimize target detection.