Download presentation
Presentation is loading. Please wait.
Published byPatrick Andrews Modified over 9 years ago
1
Vestibular contributions to visual stability Ronald Kaptein & Jan van Gisbergen Colloquium MBFYS, 7 november 2005
2
Visual stability Introduction maintaining a roughly veridical percept of allocentric visual orientations despite changes in head orientation.
3
Visual stability Introduction Different sources of information: Visual Somatosensory Auditory Proprioceptive Vestibular
4
Visual stability Introduction – visual stability
5
Visual stability 1 2 Introduction – visual stability ?
6
Subjective visual vertical Sudden transition at large tilt: Introduction - SVV
7
Subjective visual vertical Introduction - SVV Errors in subjective visual vertical Errors in subjective body tilt -=cw -=ccw
8
Subjective visual vertical Introduction - SVV
9
Subjective visual vertical Introduction - SVV * Kaptein & Van Gisbergen, J Neurophysiol, 2004 * Kaptein & Van Gisbergen, J Neurophysiol, 2005
10
1 2 Vestibular processing Introduction
11
Vestibular system Introduction Canals + Otoliths
12
Semicircular canals Introduction Limitations: poor response to constant-velocity and low-frequency rotations (i.e a high-pass filter)
13
Otoliths Introduction Limitations: cannot discriminate between tilt and translation (ambiguity problem)
14
Otoliths Introduction Ambiguity problem: Neural strategies for otolith disambiguation: Frequency segregation model Canal-otolith interaction model
15
Frequency-segregation model Introduction Based on the constant nature of gravity and the transient nature of acceleration
16
Canal-otolith interaction model Introduction Head tilt leads to a canal signal, head acceleration does not
17
Questions Introduction How good is visual stability during head rotations in the dark? What is the role of canal and otolith signals in this process? How can the processing of canal and otolith signals be modeled?
18
METHODS Methods – Task 1
19
Vestibular rotation Methods G Upright: canals+otoliths Supine: canals only Sinusoidal rotation Amplitude: 15° Frequencies: 0.05, 0.1, 0.2 & 0.4 Hz
20
TASK 1 Results
21
Task 1 Methods While rotating, subjects judged the peak-peak sway of various luminous lines which counter rotated relative to the head, at different amplitudes.
22
Task 1 Methods Not enough counter rotation: Too much counter rotation:
23
Task 1 Methods Updating gain (G): the amount of counter rotation necessary for perceptual spatial stability, expressed as a fraction of head-rotation amplitude. G=0 : No updating (Head-fixed line is perceived as stable in space) G=1 : Perfect updating
24
RESULTS 1 Methods – Task 1
25
Raw data task 1 Results – Task 1 1 subject, upright
26
Results – Task 1 Updating gain no updating perfect updating
27
DISCUSSION 1 Discussion – Task 1
28
2 Interpretation task 1 Discussion – Task 1
29
Interpretation task 1 Discussion – Task 1
30
Interpretation task 1 Discussion – Task 1
31
updating gain: otoliths+canals canals Otolith & canal contributions Discussion – Task 1
32
Otolith & canal contributions canals otoliths improvement in upright, due to gravity, is low- pass: Discussion – Task 1
33
canal-otolith interaction frequency segregation Can current models explain our results? Not straightforward: both models predict low-pass characteristics in upright condition. Discussion – Task 1
34
Linear-summation model for rotational updating Discussion – Task 1
35
Linear-summation model Interaction model: Filter model: Discussion – Task 1
36
Fits of linear-summation model upright supine upright supine Interaction model Filter model R 2 adj =0.72R 2 adj =0.82 Discussion – Task 1
37
TASK 2 Methods – Task 2
38
Task 2 Methods – Task 2 While rotating, subjects judged the side-to-side displacement of various LEDs which were stable relative to the head or stable in space.
39
Task 2 Methods – Task 2
40
Task 2 Updating gain (G): the amount of counter rotation necessary for perceptual spatial stability, expressed as a fraction of head-rotation amplitude. Perceived translation (T): the perceived spatial displacement of an LED situated on the rotation axis. Methods – Task 2
41
RESULTS 2 Results – Task 2
42
Raw data task 2 Results – Task 2 1 subject, upright
43
Results – Task 2 Updating gain no updating perfect updating
44
Results – Task 2 Perceived translation
45
DISCUSSION 2 Discussion – Task 2
46
GIF Resolution
47
Further processing necessary Discussion – Task 2
48
Translation predictions using perfect integration Discussion – Task 2 Canal-otolith interaction Frequency segregation
49
Discussion – Task 2 Translation predictions using leaky integration
50
CONCLUSIONS Conclusion
51
Conclusions Q: How good is visual stability during head rotations in the dark? A: Compensation for rotation is only partial but better for higher frequencies. Small illusionary translation percepts in upright condition at highest frequencies. Conclusion
52
Conclusions Q: What is the role of canal and otolith signals in maintaining visual stability? A: Both otoliths and canals contribute to rotational updating. Illusionary translation percept is otolith driven Conclusion
53
Conclusions Q: How can the processing of canal and otolith signals be modeled? A: Rotation: Linear summation of canal and otolith cues. Translation: Double leaky integration of internal estimate of acceleration. We are not yet able to discriminate between the two disambiguation schemes Conclusion
54
Questions? Conclusion
Similar presentations
© 2025 SlidePlayer.com. Inc.
All rights reserved.