Neuronal correlates of a virtual-reality-based passive sensory P300 network

Abstract

P300, a positive event-related potential (ERP) evoked at around 300 ms after stimulus, can be elicited using an active or passive oddball paradigm. Active P300 requires a person's intentional response, whereas passive P300 does not require an intentional response. Passive P300 has been used in incommunicative patients for consciousness detection and brain computer interface. Active and passive P300 differ in amplitude, but not in latency or scalp distribution. However, no study has addressed the mechanism underlying the production of passive P300. In particular, it remains unclear whether the passive P300 shares an identical active P300 generating network architecture when no response is required. This study aims to explore the hierarchical network of passive sensory P300 production using dynamic causal modelling (DCM) for ERP and a novel virtual reality (VR)-based passive oddball paradigm. Moreover, we investigated the causal relationship of this passive P300 network and the changes in connection strength to address the possible functional roles. A classical ERP analysis was performed to verify that the proposed VR-based game can reliably elicit passive P300. The DCM results suggested that the passive and active P300 share the same parietal-frontal neural network for attentional control and, underlying the passive network, the feed-forward modulation is stronger than the feed-back one. The functional role of this forward modulation may indicate the delivery of sensory information, automatic detection of differences, and stimulus-driven attentional processes involved in performing this passive task. To our best knowledge, this is the first study to address the passive P300 network. The results of this study may provide a reference for future clinical studies on addressing the network alternations under pathological states of incommunicative patients. However, caution is required when comparing patients' analytic results with this study. For example, the task presented here is not applicable to incommunicative patients.

Figure 1. The architectures of the plausible model pairs.

(SI : primary sensory area; SII : secondary sensor area; ACC : Anterior cingulate cortex; TPJ: Temporoparietal junction; IPL : Inferior parietal lobule; PMA : Premotor area;DLPFC: Dorsolateral prefrontal cortex).

Figure 2. The time courses of the mean SEPs under standard (dash line) and rare (solid line) conditions at C3 and the mean topographic maps at the individual peak of P50, N80 and P200.

Figure 3. The time courses of the ERP at Fz, Cz and Pz averaged across subjects (left) and the mean topographic map at the individual peak of P300, normalized to the individual-specific maximum and minimum (right).

Figure 4. The statistic result revealed by the Post-hoc paired t-test on the P300 amplitude.

(*: P<0.001, **: P<0.05).

Figure 5. The result of BMS at the single subject level under FFX.

Figure 6. BMS results at the group level under FFX (a) and RFX (b) both confirmed that Model 6 is the most likely model hierarchy among tested models.

Figure 7. The models for testing the mechanism of the task-related modulation.

Figure 8. The BMS results of task-dependent modulations under FFX at the single subject level (a) and under RFX at the group level (b).

Figure 9. The BMS result of model families.