| Literature DB >> 28432328 |
Laurence R Harris1, Kenzo Sakurai2,3,4, William H A Beaudot3,4.
Abstract
Vestibular-somatosensory interactions are pervasive in the brain but it remains unclear why. Here we explore the contribution of tactile flow to processing self-motion. We assessed two aspects of self-motion: timing and speed. Participants sat on an oscillating swing and either kept their hands on their laps or rested them lightly on an earth-stationary surface. They viewed a grating oscillating at the same frequency as their motion and judged its phase or, in a separate experiment, its speed relative to their perceived motion. Participants required the phase to precede body movement (with or without tactile flow) or tactile flow by ~5° (44 ms) to appear earth-stationary. Speed judgments were 4-10% faster when motion was from tactile flow, either alone or with body motion, compared to body motion alone (where speed judgments were accurate). By comparing response variances we conclude that phase and speed judgments do not reflect optimal integration of tactile flow with other cues to body motion: instead tactile flow dominates perceived self-motion - acting as an emergency override. This may explain why even minimal tactile cues are so helpful in promoting stability and suggests that providing artificial tactile cues might be a powerful aid to perceiving self-motion.Entities:
Mesh:
Year: 2017 PMID: 28432328 PMCID: PMC5430733 DOI: 10.1038/s41598-017-01111-w
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.379
Figure 1Frequency at which participants chose “same phase” plotted as a function of the phase difference between the visual stimulus and either the body motion only (A), tactile flow only (B), or combined conditions (C). Each participant’s performance is shown, with best-fit Gaussians fitted to the means plotted as a thick line through each data set. The experimental conditions are shown as insets. For the body motion only condition the observer sat on a moving swing in darkness. For the tactile flow only condition the observer held their fingertips lightly over a moving surface. For the combined condition observers oscillated on the moving swing with their fingertips lightly touching an earth-stationary surface. The mean phase with equivalent time delay (D) and standard deviation (STD) (E) of the fits to each participant’s data is shown along with the prediction of the maximum likelihood estimation (MLE) model (yellow bars). Error bars are standard errors. Horizontal lines with asterisks indicate statistically significant differences. * p < 0.05, **p < 0.01, ***p < 0.001.
The parameters of the best fit Gaussians for all conditions.
| Phase judgments | Body | Tactile | Body + tactile | Prediction |
|---|---|---|---|---|
| Phase Match | −5.9° ± 3.4° | −3.9° ± 1.2° | −5.9° ± 1.6° | −3.9° ± 1.2° |
| Standard Deviation | 21.9° ± 1.6° | 13.2° ± 1.0° | 14.7° ± 1.3° | 11.0° ± 0.7° |
| Variance | 503 ± 76 deg2 | 185 ± 31 deg2 | 231 ± 37 deg2 | 124 ± 16 deg2 |
The numbers are the averages of the fits to each individual’s data. Standard errors are given.
Figure 2Speed judgments of the peak velocity of body, tactile or combined motion plotted as a function of the ratio of the visual speed to swing’s speed. Data are shown for each participant with a best-fit sigmoid fitted to the means for body motion only (A), tactile flow only (B), and both (C). Sigmoids were fit to each participant’s data and the mean increase in the points of subjective equality (PSE) at which the visual movement matched the experienced motion (D) and standard deviations (E) are plotted with standard errors and compared to the predictions of the optimum integration model (yellow bars). Horizontal lines with asterisks indicate statistically significant differences. * p < 0.05, **p < 0.01, ***p < 0.001.
PSEs and STDs of the ratio of visual speed to body, tactile, or combined motion needed for them to be judged as equal.
| Speed judgments relative to 100% | Body | Tactile | Body + tactile | Prediction |
|---|---|---|---|---|
| PSE (%) | −1.4 ± 1.6 | 3.4 ± 2.7 | 9.7 ± 2.4 | 1.7 ± 1.7 |
| STD (%) | 10.3 ± 1.6 | 12.9 ± 1.7 | 13.1 ± 1.3 | 7.2 ± 0.9 |
Values are the averages of the fits to each individual participant’s data with standard errors.
Figure 3Shows the predicted speed match for each participant based on the optimum integration model fit for each participant (red symbols). The black symbols are the predicted combined speed based on an unconstrained weighted sum model. The solid line has a slope of unity, which would indicate a perfect prediction.