In 4 Simon experiments the authors examined control over 2 routes of sensorimotor processing: response priming in the unconditional route and response selection via the conditional route. The Simon effect diminished as the frequency of noncorresponding trials increased. Location-based response priming was observed only when the stimulus followed a corresponding event but not after a noncorresponding trial. Therefore, the unconditional route appears to be suppressed whenever the task context indicates priming as potentially disadvantageous. Moreover, the task-irrelevant stimulus location was used for response selection as a function of correspondence probability. Although exact repetitions of stimulus-response sequences caused a marked speed-up of responses, this 3rd mechanism is independent of unconditional route suppression and frequency-based adjustments in the conditional route.

Brain-electric correlates of reading have traditionally been studied with word-by-word presentation, a condition that eliminates important aspects of the normal reading process and precludes direct comparisons between neural activity and oculomotor behavior. In the present study, we investigated effects of word predictability on eye movements (EM) and fixation-related brain potentials (FRPs) during natural sentence reading. Electroencephalogram (EEG) and EM (via video-based eye tracking) were recorded simultaneously while subjects read heterogeneous German sentences, moving their eyes freely over the text. FRPs were time-locked to first-pass reading fixations and analyzed according to the cloze probability of the currently fixated word. We replicated robust effects of word predictability on EMs and the N400 component in FRPs. The data were then used to model the relation among fixation duration, gaze duration, and N400 amplitude, and to trace the time course of EEG effects relative to effects in EM behavior. In an extended Methodological Discussion section, we review 4 technical and data-analytical problems that need to be addressed when FRPs are recorded in free-viewing situations (such as reading, visual search, or scene perception) and propose solutions. Results suggest that EEG recordings during normal vision are feasible and useful to consolidate findings from EEG and eye-tracking studies.

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The emotional content of stimuli influences cognitive performance. In two experiments, we investigated the time course and mechanisms of emotional influences on visual word processing in various tasks by recording event-related brain potentials (ERPs). The stimuli were verbs of positive, negative, and neutral valence. In Experiment 1, where lexical decisions had to be performed on single verbs, both positive and negative verbs were processed more quickly than neutral verbs and elicited a distinct ERP component, starting around 370 msec. In Experiment 2, the verbs were embedded in a semantic context provided by single nouns. Likewise, structural, lexical, and semantic decisions for positive verbs were accelerated, and an ERP effect with a scalp distribution comparable to that in Experiment 1 now started about 200 msec earlier. These effects may signal an automatic allocation of attentional resources to emotionally arousing words, since they were not modulated by different task demands. In contrast, a later ERP effect of emotion was restricted to lexical and semantic decisions and, thus, appears to indicate more elaborated, task-dependent processing of emotional words.

Event-related brain potentials (ERPs) are important research tools because they provide insights into mental processing at high temporal resolution. Their usefulness, however, is limited by the need to average over a large number of trials, sacrificing information about the trial-by-trial variability of latencies or amplitudes of specific ERP components. Here we propose a novel method based on an iteration strategy of the residues of averaged ERPs (RIDE) to separate latency-variable component clusters. The separated component clusters can then serve as templates to estimate latencies in single trials with high precision. By applying RIDE to data from a face-priming experiment, we separate priming effects and show that they are robust against latency shifts and within-condition variability. RIDE is useful for a variety of data sets that show different degrees of variability and temporal overlap between ERP components.