Prediction and unconscious attention operate synergistically to facilitate stimulus processing: An fMRI study

Neuroscientific Evidence for Processing Without Awareness

The extent to which we are affected by perceptual input of which we are unaware is widely debated. By measuring neural responses to sensory stimulation, neuroscientific data could complement behavioral results with valuable evidence. Here we review neuroscientific findings of processing of high-level information, as well as interactions with attention and memory. Although the results are mixed, we find initial support for processing object categories and words, possibly to the semantic level, as well as emotional expressions. Robust neural evidence for face individuation and integration of sentences or scenes is lacking. Attention affects the processing of stimuli that are not consciously perceived, and such stimuli may exogenously but not endogenously capture attention when relevant, and be maintained in memory over time. Sources of inconsistency in the literature include variability in control for awareness as well as individual differences, calling for future studies that adopt stricter measures of awareness and probe multiple processes within subjects.

Emotional prediction: An ALE meta-analysis and MACM analysis

The prediction of emotion has been explored in a variety of functional brain imaging and neurophysiological studies. However, an overall picture of the areas involved this process remains unexploited. Here, we quantitatively summarized the published literature on emotional prediction using activation likelihood estimation (ALE) in functional magnetic resonance imaging (fMRI). Furthermore, the current study employed a meta-analytic connectivity modeling (MACM) to map the meta-analytic coactivation maps of regions of interest (ROIs). Our ALE analysis revealed significant convergent activations in some vital brain areas involved in emotional prediction, including the dorsolateral prefrontal cortex (DLPFC), ventrolateral prefrontal cortex (VLPFC), orbitofrontal cortex (OFC) and medial prefrontal cortex (MPFC). For the MACM analysis, we identified that the DLPFC, VLPFC and OFC were the core areas in the coactivation network of emotional prediction. Overall, the results of ALE and MACM indicated that prefrontal brain areas play critical roles in emotional prediction.

The Impact of Top-Down Prediction on Emotional Face Processing in Social Anxiety

There is evidence that people with social anxiety show abnormal processing of emotional faces. To investigate the impact of top-down prediction on emotional face processing in social anxiety, brain responses of participants with high and low social anxiety (LSA) were recorded, while they performed a variation of the emotional task, using high temporal resolution event-related potential techniques. Behaviorally, we reported an effect of prediction with higher accuracy for predictable than unpredictable faces. Furthermore, we found that participants with high social anxiety (HSA), but not with LSA, recognized angry faces more accurately than happy faces. For the P100 and P200 components, HSA participants showed enhanced brain activity for angry faces compared to happy faces, suggesting a hypervigilance to angry faces. Importantly, HSA participants exhibited larger N170 amplitudes in the right hemisphere electrodes than LSA participants when they observed unpredictable angry faces, but not when the angry faces were predictable. This probably reflects the top-down prediction improving the deficiency at building a holistic face representation in HSA participants.