Magnitude and time course of illusory translation perception during off-vertical

axis rotation

Rens VingerhoetsPieter Medendorp

Jan Van Gisbergen

Contents

• Introduction- Sensors- Off-vertical axis rotation- Models

• Methods• Results

- Verbal estimates- Psychophysical data

• Model implications• Conclusions

Contents

Sensory signals involved in spatial orientation:

• Visual Cues• Semicircular canals• Otoliths• Somatosensory cues

Introduction - Sensors

Introduction - Sensors

The semi-circular canals

• Sensitive to angular acceleration• High-pass filter

Introduction - Sensors

The otoliths

• Sensitive to acceleration caused by:– Gravity– Inertial acceleration

Off-Vertical Axis RotationVertical Axis Rotation

Introduction

What is off-vertical axis rotation (OVAR)?

What is off-vertical axis rotation (OVAR)?

• Rotation in yaw about an axis that is tilted relative to the direction of gravity.

Stimulation of both otoliths and canals

Introduction

Left Ear Down (LED) Right Ear Down (RED)Nose Up (NU) Nose Down (ND)

What causes this percept?

Left Ear Down (LED) Right Ear Down (RED)Nose Up (NU) Nose Down (ND)

Introduction

What happens during OVAR?

Otolith signal from tilt interpreted as translation?

LED

ND

NU

RED

ND

LEDRED

NU

R

Introduction – Otolith Disambiguation

Neural strategy for otolith disambiguation:

Filter hypothesis

Acceleration

Introduction – Otolith Disambiguation

Neural strategy for otolith disambiguation:

Canal-Otolith interaction

Acceleration

Rotation

Introduction – research question

Do these models apply to self-motion perception during OVAR?

To check this quantitative data is required

Methods

Experimental setup

Picture of vestibular chair

Methods

Experimental setup • 6 subjects • 2 series (only clockwise rotation)

- Tilt series: 0, 15 and 30 deg tilt at 30 deg/s- Speed series: 20, 30, 40 and 50 deg/s at 15 deg tilt

• Each experimental condition consisted of 18-20 runs of 180 s each

• Subjects indicated verbally when cone illusion started

• Subjects reported the perceived radius

• Self-motion percept quantified with laser method

Experiment

Laser method

v

• Screen and motorized laser on board of the chair

• Every NU and ND phase projection of moving laser dot

• Subject indicated with a toggle switch if the dot was moving too fast/slow in direction opposite to perceived selfmotion

• ‘Matching velocity’ obtained using two methods:

- 0-110 s: Adaptive staircase over runs

- 110-180 s: Method of constant stimuli

Results I

Verbal Estimates

Results I – Verbal estimates

Reported cone illusion latencies

Results I – Verbal Estimates

Estimated Radii

Results II

Time course

Results II – Staircase Data

Staircase data from tilt series

NU

ND

Results II – Staircase Data

Staircase data from tilt series

NU

ND

Results II – Staircase Data

Staircase data from tilt series

NU

ND

Results II – Staircase Data

Staircase data from speed series

NU

ND

Results II – Staircase Data

Summary staircase data

• Stereotyped exponential decay to zero in 30-60 s in zero-tilt condition

• During OVAR short exponential decay followed by bifurcation into two opposite velocity levels

• Results in agreement with anecdotal reports• Bifurcation depends on tilt angle• Bifurcation depends on rotation speed

Results III

Decomposition of response curves

Results III - Decomposition

Decomposition of response curves

• Two processes (R & T) underlie self-motion perception.

• R follows the same time course in both phases (NU & ND)

• T has opposite sign in both phases

• Hence, matching velocity is: VNU = R +T VND = R – T

• Consequently:R = (VND + VNU)/2T = (VNU - VND)/2

LEDRED

NU

ND

TR +

TR +

Results III - Decomposition

Decomposition data from tilt series

R

T

Results III - Decomposition

Decomposition data from tilt series

R

T

Results III - Decomposition

Decomposition data from tilt series

R

T

Results III - Decomposition

Decomposition data from speed series

R

T

Results III - Decomposition

Summary decomposition data

• R component shows exponential decay to zero independent of tilt angle and rotation speed

• T component starts at zero and gradually climbs to an asymptotic level.

• T component increase not always starts right after rotation onset• Asympotic value of T component depends on tilt angle and

rotation speed.

Results III - Decomposition

Fit to decomposition data

Rotation component:

R(t) = A * exp(-t/TR)

Translation component:

T(t) = 0 if t < T

T(t) = B * (1 – exp((-t-T)/TT) if t > T

Results III - Decomposition

Examples of fit

Results III - Decomposition

Fit parameters show us:

R component R(t) = A * exp(-t/TR)

• TR is constant across experimental conditions

• Initial amplitude (A) of R component increases with increasing rotation speed

T component

T(t) = 0 if t < T

T(t) = B * (1 – exp((-t-T)/TT)

• Incorporating a delay (T ) is essential

• Inter-subject differences for delay and TT

• Translation percept (B) increases both with tilt angle and rotation speed.

Results IV

Constant stimuli data

Results IV – Constant Stimuli

Constant stimuli data from tilt series

NU

ND

Results IV – Constant Stimuli

Constant stimuli data from speed series

NU

ND

Results IV – Constant Stimuli

Summary constant stimuli data

• Observations from staircase data confirmed:- Increase of matching velocity with tilt angle- Increase of matching velocity with rotation speed

• Width of psychometric curve increases with rotation speed

Models

Models

Model predictions

Canal-otolith interaction Filtering

30o/s and 15o tilt

Models

Model predictions

30o/s and 15o tilt

Canal-Otolith

Models

Model predictions

30o/s and 15o tilt

Canal-Otolith

Filter

Models

Model predictions

30o/s and 15o tilt

Data

Canal-Otolith

Filter

Models cannot account for observed time course

Models

Model predictions

15o tilt

Data

Canal-Otolith

Filter

Models predict too large translations

Conclusions

• We have developed a method that is able to capture the motion percepts that occur during OVAR

•Contemporary model hypotheses such as canal-otolith interaction and frequency segregation cannot explain our results

Conclusions

The End

Canal-otolith interaction model

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+ -++

+

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Body Dynamics Sensory Dynamics

S scc (s)

S oto (s)

S scc (s)

S oto (s)

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Model of Body Dynamics

Model of Sensory Dynamics

Merfeld