Abstract
Prediction is essential for the efficiency of many cognitive processes; however, this process is not always perfect. Predictive coding theory suggests that the brain generates and updates a prediction to respond to an upcoming event. Although an electrophysiological index of prediction, the stimulus preceding negativity (SPN), has been reported, it remains unknown whether the SPN reflects the prediction accuracy, or whether it is associated with the prediction error, which corresponds to a mismatch between a prediction and an actual input. Thus, the present study aimed to investigate this question using electroencephalography (EEG). Participants were asked to predict the original pictures from pictures that had undergone different levels of pixelation. The SPN amplitude was affected by the level of pixelation and correlated with the subjective evaluation of the prediction accuracy. Furthermore, late positive components (LPC) were negatively correlated with SPN. These results suggest that the amplitude of SPN reflects the prediction accuracy; more accurate prediction increases the SPN and reduces the prediction error, resulting in reduced LPC amplitudes.
Highlights
Prediction of future events plays an important role in everyday life; we often predict situations to organize our behavior in preparation for the effects of those events
Since it is known that unpredicted stimuli cause larger late positive components (LPC), such as P300 or late positive potential (LPP; Delplanque et al, 2005; Gole et al, 2012; Chennu et al, 2013; Lin et al, 2015; Yang et al, 2019), the secondary aim of the present study was to clarify how prediction accuracy affects post-prediction neural responses
The correlation between the brain potential at the C2 electrode and Q1/Q2 score showed a positive correlation (Figure 4B; Q1: r = −0.25, t94 = −2.48, p = 0.030; Q2: r = −0.28, t94 = −2.79, p = 0.012). These results indicate that the stimulus preceding negativity (SPN) amplitudes at F2 and C2 were associated with confidence in the prediction (Q1) and accuracy of prediction (Q2)
Summary
Prediction of future events plays an important role in everyday life; we often predict situations to organize our behavior in preparation for the effects of those events. When we drive a car and reach an intersection, we predict whether someone may run out into the street. Owing to the prediction process, the car can be stopped to prevent an accident. Psychological studies have shown that such predictions are beneficial for perceiving future stimuli that meet these predictions (Oliva and Torralba, 2007; Pinto et al, 2015; Stein and Peelen, 2015). The neural dynamics underlying prediction have frequently been studied using electroencephalography (EEG) with an S1–S2 paradigm, which comprises the presentation of a cue (S1) followed by a target stimulus (S2). EEG studies have shown that the brain
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