Reminder:
The CEU Department of Cognitive Science cordially invites you to a talk
(as part of its Departmental Colloquium series)
by
Marc O. Ernst (Bielefeld University, Germany)
Date: Wednesday, Oct 22, 2014 - 17:00 - 18:30
Location: Department of Cognitive Science, CEU, Frankel Leó út 30-34.,
Room G15
Title:
From Multisensory Perception to Sensorimotor Behaviour:
A Probabilistic
Approach
Abstract:
The human brain uses multiple sources of sensory information together
with prior knowledge about the statistical regularities of the world in
order to generate the most appropriate action. However, there is
uncertainty due to noise and ambiguity in the sensory information.
Furthermore, sensory information as well as prior knowledge may be
imprecise and possibly inaccurate for the current action context.
Therefore, a decision for choosing some action can only be taken
probabilistically. Bayesian Decision Theory, which I will review here in
this talk, provides a suitable probabilistic framework to come up with
ideal observer models, against which human perception and performance
can be compared. Besides an introduction to this general framework, I
will talk about two of our recent studies in more detail, which are
examples of the application of this framework to multisensory perception
and action. The first study deals with the decision process, which
signals to combine. Sometimes there are seemingly arbitrary association
between multisensory signals such as, for example, sound frequency and
spatial elevation. This goes so far that even in most natural languages
the spatial labels -high- and -low- are used for particular sound
frequencies. We recently showed (Parise et al., PNAS, 2014) the reason
for this association to be found in the statistics of the natural
environment where high frequency sounds are more likely to originate
from a higher spatial elevation and vices versa. The second study (van
Dam, Ernst, PLoS One, 2013) investigates the knowledge we have about the
errors we make when executing actions. This is important because it is
the knowledge about such errors that shapes sensorimotor learning. We
show that we have a surprisingly detailed understanding of even the
random errors we make and that we can use this knowledge in a
statistically optimal way for the correction of the errors. I will end
my talk with a discussion about the benefits and the limits of this
framework.
We're looking forward to see you there (Frankel Leo u. 30-34) !
Cognitive Science Events at CEU:
http://cognitivescience.ceu.hu/events
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