Concern-based Cohesion: Unveiling a Hidden Dimension of Cohesion Measurement
UNVEILING THE HIDDEN SENSE
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Transcript of UNVEILING THE HIDDEN SENSE
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UNVEILING THE HIDDEN SENSE
Farewell lectureMay 30, 2008
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VESTIBULAR CONTRIBUTION TO SPATIAL AWARENESS
detection of self motion sensing body orientation in space visual perception in earth-centric coordinates
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SCOPE
Vestibular sensors
Spatial orientation in dynamic conditions
Spatial vision in tilted observers
Bayesian model
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VESTIBULAR SENSORS
canals
otoliths
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CANALS DETECT ROTATION
high-pass filter
insensitive to constant velocity rotation
nerve fibers code head velocity
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CONSTANT ROTATION IN DARKNESS
• rotation percept decays
• after stop, percept of rotation in opposite direction
• reflects cupular mechanics
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OTOLITHS
sensitive to tilt and translation
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OTOLITH SIGNAL IS AMBIGUOUS
hair cells cannot distinguish tilt and translation
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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
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CANAL- OTOLITH INTERACTION MODEL
• canals detect rotation during tilt changes
• their signal helps to decompose otolith signal
Angelaki et al. (1999)
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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
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percepts during rotation about a tilted axis
(OVAR)
Vingerhoets et al. (2006) J. Neurophysiol.
Vingerhoets et al. (2007) J. Neurophysiol.
TESTING THE MODEL
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THE ACTUAL MOTION
- rotation about tilted axis
- in darkness
- constant velocity
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MODEL PREDICTIONS
rotation signal decays gradually
wrong interpretation otolith signal: illusory translation percept
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SCHEMATIC SUMMARY OF RESULTS
confirms prediction
rotation percept
translation percept
Actual motion:
Percept:
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TRANSLATION AND ROTATION PERCEPT DATA
rotation percept
translation percept
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SPATIAL PERCEPTION IN STATIC TILT
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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
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ACCURACY vs PRECISION
Accuracy:
How close is the response to the true value?
Precision:
How reproducible is the response?
darts analogy:
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ACCURACY AND PRECISION IN LINE TASK (SVV)
accuracy
precision
De Vrijer et al. (2008) J. Neurophysiol.
De Vrijer et al. (2008) in progress
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ACCURACY IN LINE TASK
due to underestimation of body tilt?
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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.
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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
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SVV LESS NOISY THAN SBT
De Vrijer et al. in progress
psychometric experiments at 0o and 90o tilt:
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SVV LESS NOISY THAN SBT
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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)
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SBT DATA SHOW:
• An unbiased head tilt signal is available
• Noise increases with tilt angle
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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
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SIMPLY USING RAW TILT SIGNAL …
would not explain SVV bias !!spatial vision would be accurate, but noisy
raw tilt signal
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A BAYESIAN PERSPECTIVE
IDEAL OBSERVER MODEL
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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.
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IDEAL OBSERVER STRATEGY
Tilt prior has 2 effects on SVV:
• Less noise
• Bias at large tilt
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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)
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DEMO
BIAS EFFECT INCREASES WITH TILT
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no bias
De Vrijer et al. (2008) J. Neurophysiology
no bias
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small bias
small bias
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large bias
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large bias
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MODEL PARAMETERS
1) head tilt noise level in upright
2) increase of head tilt noise with tilt
3) prior width
4) eye torsion amplitude
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MODEL FITS: SVV ACCURACY
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MODEL FITS: SVV ACCURACY
< 0
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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
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CONCLUSION
Accuracy-precision trade-off in spatial vision:
• Bayesian strategy reduces noise at small tilts
• causes systematic errors at large tilts
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ACKNOWLEDGMENTS
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COWORKERS OCULOMOTOR CONTROL
David Robinson
Stan Gielen
Fenno Ottes
John van Opstal
Arend Smit
André Minken
Karin Krommenhoek
Bart Melis
Vivek Chaturvedi
Lo Bour
DIck Stegeman
Klaus Kopec
Hubert Misslisch
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COWORKERS SPATIAL AWARENESS
Anton Van Beuzekom
Ronald Kaptein
Rens Vingerhoets
Stan Van Pelt
Maaike De Vrijer
Pieter Medendorp
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TECHNICAL SUPPORT
Ger van Lingen
Victor Langeveld
Günter Windau
Hans Kleijnen
Ton van Dreumel
Stijn Martens
Wil Corbeek, Harrie van Brakel,
Arno Engels, Jaap Nieboer (TD-FNWI)
Fred Philipsen, Theo Arts (CDL)
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FOR THIS SYMPOSIUM:
THE SPEAKERS:
Dora Angelaki
Bernhard Hess
Daniel Merfeld
Casper Erkelens
Wolfgang Becker
Jos Eggermont
THE ORGANIZERS:
Pieter Medendorp
John van Opstal
Stan Gielen
Margiet van Pelt
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FOR MORAL SUPPORT
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THANK YOU FOR COMING !!
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THANK YOU FOR COMING !!