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Poster

Learning to Fuse Unrelated Cues

MPG-Autoren
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Ernst,  MO
Max Planck Institute for Biological Cybernetics, Max Planck Society;
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Zitation

Jäkel, F., & Ernst, M. (2003). Learning to Fuse Unrelated Cues. Poster presented at 6. Tübinger Wahrnehmungskonferenz (TWK 2003), Tübingen, Germany.


Zitierlink: https://hdl.handle.net/11858/00-001M-0000-0013-DD18-A
Zusammenfassung
Fusion of dierent cues can improve the reliability of perceptual estimates. E.g., a more accurate size estimate can be achieved when visual and haptic size information is used
in combination (Ernst Banks, 2002, Nature, 429-433). To combine dierent cues the
observer has to know which cues belong together (i.e., the correspondence problem has
to be solved). Here we examine whether subjects can learn to fuse two arbitrary cues
based on their statistical co-occurence. To this end, we trained 6 subjects for about
an hour with highly correlated stimuli that are usually uncorrelated, the luminance of
an object (visual cue) and its stiness (haptic cue). To test for learning, we measured
subjects' discrimination performances before (pre-test) and after (post-test) training.
The discrimination task had two intermixed conditions: One condition in which the cues
were consistent with the correlation during training (congruent) and another condition
in which they were anti-correlated (incongruent). If training had an eect we would
predict that the stimuli with congruent cues elicit an improvement in discrimination
performance relative to the incongruent condition, because if the cues were truly fused
after training the variance of the combined estimate should be lower. In agreement
with our prediction we found a signicant interaction between pre- and post-test for
the two congruent and incongruent conditions (F[1,5]=20,3; p<0.01). This indicates
that subjects indeed picked up the correlation in the training phase and fused the two
cues. We conclude that fusion of cues can be learned on a relatively short time-frame
based on the statistics of their co-occurrence.