Fig 1.
Figure from Seth et al. [3] that illustrates the fundamental architecture of the IPCM model.
“Both agency and presence components comprise state and error units; state units generate control signals (Aout, Pout) and make predictions [Apred, Ppred, Apred(p)] about the consequent incoming signals (Ain, Pin); error units compare predictions with afferents, generating error signals [Aerr, Perr, Aerr(p)].
Table 1.
The UCL presence questionnaire [73], the custom items assessing spatial, social and self-presence and the second question (Q2) from Egan and colleagues [74].
Fig 2.
Screenshots taken from the user’s perspective in the VE.
The experience presented a surreal journey in a Venetian gondola. Figure b) shows a starry sky mirrored in a lake on which the gondola is floating. Figures a, c and d) show the gondola at various stages of the journey. The full experience is a VR version of a mini-opera by Cory Strassburger and Alain Vasquez [92]. It is available free from the Oculus Store [90].
Fig 3.
Visual representation of the study procedure in chronological order.
Fig 4.
Interaction between openness and happiness scores when predicting presence.
The blue line represents the best linear fit to presence scores for the low openness group. The blue circles represent that data points for the low openness group. The red line represents the best linear fit to presence scores for the medium openness group. The red squares represent the data points for the medium openness group. The green line represents the best linear fit to presence scores for the high openness group. The green triangles represent the data points for the high openness group. R2 values for the different levels of openness can be found in the legend.
Table 2.
Table showing the regression results for the presence measures.
Fig 5.
Graphs at the top show mean scores of presence as measured by Q2 for participants who overestimated, estimated correctly and underestimated levels of relaxation, happiness and fear.
Graphs at the bottom represent mean distributions of the gaussian psychometric functions for presence, as measured by Q2 for relaxation, happiness and fear. The solid blue line represents the line of best fit for these data points. It represents the normal distribution fitted to the data as predicted by the IPCM. The dashed blue line represents the actual peak in presence and the black dashed line represents the peak in presence as hypothesized by the IPCM.
Fig 6.
Graphical representation of the revised IPCM model, as informed by the regression results.
The left row presents the three emotions tested. The middle row presents the types of presence that were verified and interactions between factors impacting overall presence. The right column presents the BFI [72] personality traits tested. Arrows signify significant interactions and items that are in grey did not show any significant impact on presence measures.