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SPATIAL AWARENESS DEMO
20 juni 2008
detection of self motion sensing body orientation in space visual perception in earth-centric coordinates
VESTIBULAR SENSORS
canals
otoliths
CANALS DETECT ROTATION
high-pass filter
insensitive to constant velocity rotation
nerve fibers code head velocity
CONSTANT ROTATION IN DARKNESS
• rotation percept decays
• after stop, percept of rotation in opposite direction
• reflects cupular mechanics
OTOLITHS
sensitive to tilt and translation
OTOLITH SIGNAL IS AMBIGUOUS
hair cells cannot distinguish tilt and translation
SPATIAL ORIENTATION ILLUSION
pilot is upright, but feels tilted
AMBIGUITY PROBLEM
otolith signal may have various causes:
• translation (a)• force of gravity due to tilt (g)• combination of a and g
How can the brain resolve this ambiguity ?
inverse problem
CANAL- OTOLITH INTERACTION MODEL
• canals detect rotation during tilt changes
• their signal helps to decompose otolith signal
Angelaki et al. (1999)
CANAL–OTOLITH INTERACTION MODEL
basic principle:- tilt stimulates otoliths AND canals- translation stimulates only otoliths
Merfeld and Zupan (2002) J. Neurophysiology
tilt angle
linear acceleration
angular velocity
OVAR
Vingerhoets et al. (2006) J. Neurophysiol.
Vingerhoets et al. (2007) J. Neurophysiol.
TESTING THE MODEL
THE ACTUAL MOTION
- rotation about tilted axis
- in darkness
- constant velocity
MODEL PREDICTIONS
rotation signal decays gradually
wrong interpretation otolith signal: illusory translation percept
SCHEMATIC SUMMARY OF RESULTS
confirms prediction
rotation percept
translation percept
Actual motion:
Percept:
TRANSLATION AND ROTATION PERCEPT DATA
rotation percept
translation percept
SPATIAL PERCEPTION IN STATIC TILT
SENSING THE DIRECTION OF GRAVITY
Two different tasks:
1. Set line to vertical (SVV)
2. Estimate your body tilt (SBT)
Van Beuzekom & Van Gisbergen (2000) J. Neurophysiol.
Van Beuzekom et al. (2001) Vision Res.
Kaptein & Van Gisbergen (2004, 2005) J. Neurophysiol.
De Vrijer et al. (2008) J. Neurophysiol.
experiments in darkness
ACCURACY vs PRECISION
Accuracy:
How close is the response to the true value?
Precision:
How reproducible is the response?
darts analogy:
ACCURACY AND PRECISION IN LINE TASK (SVV)
accuracy
precision
De Vrijer et al. (2008) J. Neurophysiol.
De Vrijer et al. (2008) in progress
ACCURACY IN LINE TASK
due to underestimation of body tilt?
NO UNDERESTIMATION OF BODY TILT
SVV SBT
• Subjects know quite well how they are tilted (SBT)
• Yet, their line settings undercompensate for tilt (SVV)
Van Beuzekom et al. (2001) Vision Res.
Kaptein and Van Gisbergen (2004) J. Neurophysiol.
PRECISION IN LINE TASK
is scatter in SVV simply reflection of noise in body tilt signal?
De Vrijer et al. (2008) J. Neurophysiol.
De Vrijer et al. (2008) in progress
SVV LESS NOISY THAN SBT
De Vrijer et al. in progress
psychometric experiments at 0o and 90o tilt:
SVV LESS NOISY THAN SBT
SUMMARY SBT AND SVV DATA
Two paradoxical findings:
1. subject knows tilt angle, yet makes biased line settings
2. more certain about line setting than about body tilt
estimate body tilt (SBT) adjust line to vertical (SVV)
SBT DATA SHOW:
• An unbiased head tilt signal is available
• Noise increases with tilt angle
SIGNALS REQUIRED FOR SPATIAL VISION
retinal signal
to compute line in space (Ls), brain must combine info about line orientation on retina (LR) and head tilt (HS)
head-tilt signal
SIMPLY USING RAW TILT SIGNAL …
would not explain SVV bias !!spatial vision would be accurate, but noisy
raw tilt signal
A BAYESIAN PERSPECTIVE
IDEAL OBSERVER MODEL
IDEAL OBSERVER STRATEGY
1) Use sensory data: noisy tilt signal suggests range of possible tilt angles (likelihood)
2) Use prior knowledge: we know that large tilt angles are very uncommon (prior)
3) Most likely tilt angle (posterior) is product of likelihood and prior
Eggert (1998) PhD Thesis, Munich
MacNeilage et al. (2007) Exp. Brain Res.
De Vrijer et al. (2008) J. Neurophysiol.
IDEAL OBSERVER STRATEGY
Tilt prior has 2 effects on SVV:
• Less noise
• Bias at large tilt
WHY WOULD THIS MAKE SENSE?
1) Less noise in spatial vision
2) Downside: bias at large tilts
3) Average performance improves (large tilts are rare)
DEMO
BIAS EFFECT INCREASES WITH TILT
no bias
De Vrijer et al. (2008) J. Neurophysiology
no bias
small bias
small bias
large bias
large bias
MODEL PARAMETERS
1) head tilt noise level in upright
2) increase of head tilt noise with tilt
3) prior width
4) eye torsion amplitude
MODEL FITS: SVV ACCURACY
MODEL FITS: SVV ACCURACY
< 0
MODEL EXPLANATION OF NOISE LEVELS:SVV vs SBT PRECISION
• SVV is less noisy than the SBT (remarkable, but explained by model)
• SBT becomes more noisy at larger tilt (supports model assumption)
• SBT noise levels compatible with head-tilt fit results
CONCLUSION
Accuracy-precision trade-off in spatial vision:
• Bayesian strategy reduces noise at small tilts
• causes systematic errors at large tilts
ACTIVE-TILT RESULTS ARE SIMILAR
body tilt estimates are quite accurate
but large errors in line task
line task body tilt estimate
Van Beuzekom et al. (2001) Vision Res.
psychometrische curvevan 0o tilt percept
proefpersoon wordt vaak in allerlei standen rond 0o gekanteld
beoordeelt elke stand als links of rechts
geen scherpe drempel door ruis in tiltsignaal
Ruis tiltsignaal bij 00
psychometrische kromme
ruis in tiltsignaal
Ruis tiltsignaal bij 0 en 90o
meer ruis bij 90o
Ruis tiltsignaal bij 0 en 90o
resultaten 5 proefpersonen
meer ruis bij 90o
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