The integration of event-related potential (ERP) and functional magnetic resonance imaging (fMRI) helps to obtain and study neural networks with high temporal and spatial resolution. EEG/fMRI data proves that in the visual tristimulus oddball paradigm, two P300 potentials (P3a and P3b) induced by target stimulation and novel stimulation are detected at the frontal-middle (Fz), center (Cz), and mid-apical (Pz) electrodes. Previous studies have shown that P3a and P3b have different spatial distributions of brain activation, but it is unclear whether they have the same neural mechanism. The purpose of this study is to determine the neuropsychological mechanisms of P3a and P3b, as well as the spatiotemporal differences in neurodynamics between the two ERP subcomponents. In a group of 25 subjects, P300 ERP induced by target stimulation and novel stimulation can be detected at the Fz, Cz, and Pz electrodes. At Cz and Fz, compared with P3b related to the target stimulus, the P3a related to the novel stimulus has a higher amplitude and the waveform declines more slowly. But at Pz, P3b has a higher amplitude than P3a. P3a appeared earlier than P3b at Cz and Fz, but the opposite phenomenon was observed at the Pz electrode. The activated brain regions of P3a included the left frontal-parietal lobe region, left anterior wedge lobe region, and right insula, while the target-driven P3b was significantly associated with BOLD changes in the bilateral fusiform gyrus, the left frontal region, and the bilateral insula. The results showed that the integration of the spatial and temporal information of the two imaging modes, namely, ERP and fMRI, proves the existence of the different brain function processes of the two P300 subcomponents. Through the analysis of the composition of P300, the results further proved that the top-down and bottom-up processing processes have played a role in the occurrence of attention capture. It is just that the modulation effects of the two processing mechanisms are different in different tasks. Therefore, it should be noted that the captured neural mechanism is not a single top-down or bottom-up processing process but should be the result of the interaction between the two.

Several diseases are characterized by cognitive instability, which is amplified in the conditions of sleep deprivation (SD). Cognitive instability in SD can be examined by the number of lapses on the psychomotor vigilance test (PVT), which is considered to be a gold standard in the field. However, the number of PVT lapses widely range according to inter-individual differences, from apparent cognitive resistance to severe cognitive impairment. In this study, tract-based spatial statistical analyses with multiple diffusion tensor imaging-derived characteristics (i.e., fractional anisotropy (FA), mean diffusivity, radial diffusivity, and axial diffusivity) were employed to investigate the relationships between the number of PVT lapses and the diffusion characteristics. A hierarchical linear regression model was then used to assess the contributions of tract-specific FA values in predicting PVT lapses. Finally, dichotomized analysis was used to investigate white matter (WM) differences between resilient and vulnerable groups. Our results showed significant negative correlations between numbers of PVT lapses and FA in multiple WM tracts, with the FA variations in the superior longitudinal fasciculus and splenium of the corpus callosum accounting for nearly 37.5% of individual variability in PVT lapses. In addition, dichotomized analyses indicated that the resilient participants exhibited significantly higher FA values compared with the vulnerable participants. Together, these findings suggest that cognitive instability after SD was closely associated with individual differences in WM integrity.