Humans have the subjective impression of a rich perceptual experience, but this perception is riddled with errors that might be produced by top-down expectancies or failures in feature integration. The role of attention in feature integration is still unclear. Some studies support the importance of attention in feature integration (Paul & Schyns, 2003), whereas others suggest that feature integration does not require attention (Humphreys, 2016). Understanding attention as a heterogeneous system, in this study we explored the role of divided (as opposed to focused – Experiment 1) attention, and endogenous-exogenous spatial orienting (Experiments 2 and 3) in feature integration. We also explored the role of feature expectancy, by presenting stimulus features that were completely unexpected to the participants. Results demonstrated that both endogenous and exogenous orienting improved feature integration while divided attention did not. Moreover, a strong and consistent feature expectancy effect was observed, demonstrating perceptual completion when an unexpected perceptual feature was presented in the scene. These results support the feature confirmation account (Humphreys, 2016), which proposes that attention is important for top-down matching of stable representations.

Our environment is constantly overloaded with information, although we cannot consciously process all the stimulation reaching our senses. Current theoretical models are focused on the cognitive and neural processes underlying conscious perception. However, cognitive processes do not occur in an isolated brain but in a complex interaction between the environment, the brain, and the organism. The brain‐body interaction has largely been neglected in the study of conscious perception. The aim of the present study was to explore if heart rate and skin conductance (SC) are modulated by the interaction between phasic alertness and conscious perception. We presented near‐threshold visual stimuli that could be preceded by an alerting tone on 50% of the trials. Behaviorally, phasic alerting improved perceptual sensitivity for detecting a near‐threshold stimulus (along with changes in response criterion). Following the alerting tone, a cardiac deceleration‐acceleration pattern was observed, which was more pronounced when the near‐threshold stimulus was consciously perceived in comparison with unconsciously perceived stimuli. SC results further showed some degree of subliminal processing of unseen stimuli. These results reveal that cardiac activity could be a marker of attention and consciousness interactions, emphasizing the need for taking into account brain‐body interactions for current theoretical models of consciousness.

Our sensory system is able to build a unified perception of the world, which although rich, is limited and inaccurate. Sometimes, features from different objects are erroneously combined. At the neural level, the role of the parietal cortex in feature integration is well-known (Humphreys, 2016; Shafritz et al., 2002). However, the brain dynamics underlying correct and incorrect feature integration are less clear. To explore the temporal dynamics of feature integration, we studied the modulation of different frequency bands in trials in which feature integration was correct or incorrect. Participants responded to the color of a shape target, surrounded by distractors. A calibration procedure ensured that accuracy was around 70% in each participant. To explore the role of expectancy in feature integration, we introduced an unexpected feature to the target in the last blocks of trials. Results demonstrated the contribution of several frequency bands to feature integration both pre- and post-stimulus. During the pre-stimulus period, alpha power was higher for illusions compared to hits. After stimulus onset, alpha, beta, and gamma-band power was reduced for hits compared to illusions. Moreover, gamma power was overall larger during the experiment for participants who were aware of the unexpected target presented during the last blocks of trials (as compared to unaware participants). These results demonstrate that feature integration is a complex process that can go wrong at different stages of information processing and is influenced by top-down expectancies.