| Literature DB >> 27485049 |
Antonella Maselli1,2, Konstantina Kilteni1, Joan López-Moliner3,4, Mel Slater1,4,5,6.
Abstract
Experimental work on body ownership illusions showed how simple multisensory manipulation can generate the illusory experience of an artificial limb as being part of the own-body. This work highlighted how own-body perception relies on a plastic brain representation emerging from multisensory integration. The flexibility of this representation is reflected in the short-term modulations of physiological states and perceptual processing observed during these illusions. Here, we explore the impact of ownership illusions on the temporal dimension of multisensory integration. We show that, during the illusion, the temporal window for integrating touch on the physical body with touch seen on a virtual body representation, increases with respect to integration with visual events seen close but separated from the virtual body. We show that this effect is mediated by the ownership illusion. Crucially, the temporal window for visuotactile integration was positively correlated with participants' scores rating the illusory experience of owning the virtual body and touching the object seen in contact with it. Our results corroborate the recently proposed causal inference mechanism for illusory body ownership. As a novelty, they show that the ensuing illusory causal binding between stimuli from the real and fake body relaxes constraints for the integration of bodily signals.Entities:
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Year: 2016 PMID: 27485049 PMCID: PMC4971486 DOI: 10.1038/srep30628
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.379
Figure 1Experimental setup.
(A) Participants performed a visuotactile Temporal Order Judgment (TOJ) task, while wearing head-mounted display. (B) Piezoelectric motor used to deliver vibrotactile stimuli. The visual stimulus was a 50 ms rotation of a virtual geared-wheel: the geared-wheel was seen (C) in contact with the virtual finger (Exp. 1: Touch condition; Exp. 2: Body condition), (D) separated from the virtual finger (Exp. 1: No-Touch condition) or (E) touching a wooden stick (Exp. 2: Stick condition). The 3D graphics elements were designed with Autodesk® 3ds Max® and controlled through the Unity® software platform.
Questionnaire items.
| Tag | Questionnaire Item |
|---|---|
| During the temporal order judgment task I felt as if the | |
| During the temporal order judgment task I felt as if my right index finger was touching the virtual wheel | |
| During the temporal order judgment task I felt as if the rotation of the virtual wheel produced the tactile stimuli on my finger | |
| I felt as if the | |
| I felt as if I had two right hands |
The Table lists the six items presented to participants at the end of each experimental session. The items were presented in a randomized order across participants and experimental conditions. Participants had to indicate their level of agreement with each of the statement, on a Likert scale from −3 to 3. The text in parentheses was used to replace the italic text in the Stick condition in Experiment 2.
Figure 2Results from Experiment 1.
(A) Boxplot showing the distribution of JND estimates from individual fits in the two experimental conditions; JND estimates from single subjects are overplotted as scatter points. (B) Boxplot showing the distribution of JND differences in the two conditions (ΔJND = JND − JND), estimated from individual fits; ΔJND for single subjects are overplotted as scatter points. For 10 out 14 participants the JND was higher in the Touch condition. The mean value of individual ΔJND was 46.6 ms. (C) JNDs estimates (n = 14) from Genelized Linear Mixed Model (Bootstrap method) were equal to 127 ms and 155 ms in the No-Touch and Touch conditions respectively. Vertical bars represent the 95% CI estimated with the bootstrap method67. GLMM analysis revealed a significant difference in across conditions (p < 0.0001).
Questionnaire Results.
| Item | p-value | PSdep | |||
|---|---|---|---|---|---|
| 2 (1) | 2 (1.5) | 0 (0.75) | 0.48 | 0.53 | |
| 1.5 (4.5) | −3 (1) | 2.5 (3.75) | 0.002 | 0.96 | |
| 1 (2) | −0.5 (4.5) | 1 (3) | 0.06 | 0.75 | |
| 3 (1) | 3 (1) | 0 (0.75) | 0.78 | 0.46 | |
| −3 (1.75) | −3 (0) | 0 (0.75) | 0.10 | 0.64 | |
| 2 (1) | −2 (3) | 3 (4) | 0.005 | 0.84 | |
| 1.5 (3) | −2 (3.75) | 1.5 (3) | 0.01 | 0.79 | |
| 1 (1.75) | 1 (3.5) | 0 (1.75) | 0.12 | 0.61 | |
| 3 (1) | −3 (1.75) | 5 (2) | 0.001 | 0.06 | |
| −3 (0) | −3 (0) | 0 (0) | 0.58 | 0.50 | |
The Table lists the median scores assigned to each questionnaire item across participants, together with the associated inter quartile range (IQR) in parentheses, for each condition of the two experiments (columns 2 and 3). Column 3 gives the median (IQR) values of the differences among scores given in the two experimental conditions by each subjects. Columns 4 and 5 give the p-values from Matched-Paired Wilcoxon test and the associated effect size in terms of probability of superiority for dependent measures (PSdep).
Figure 3Results from Experiment 2.
(A) Boxplot showing the distribution of JND difference in the two conditions (ΔJN = JND − JND), estimated from individual fits; ΔJND for single subjects are overplotted as scatter points. For 11 out of 14 participants the JND was higher in the Body condition. The mean value of individual ΔJND was 16.3 ms. (B) JNDs estimates (n = 14) were equal to 127 ms and 155 ms in the Stick and Body conditions respectively. Vertical bars represent the 95% CI estimated with the bootstrap method67. GLMM analysis revealed a significant difference across conditions (p = 0.011). (C) JND estimates from individual fits are plotted as a function of subjective scores given to the “Ownership” (left panel), “Touch” (central panel), and “Cause” (right panel) questionnaire items (full statements listed in Table 1), together with the robust linear fits and associated 95% CIs. Spearman correlation analysis revealed significant positive correlations for the three cases.