[language] [Fwd: [evol-psych] Infants Build Knowledge of Their Visual World on Statistics]

H.M. Hubey hubeyh at mail.montclair.edu
Wed Nov 27 03:34:46 UTC 2002


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-------- Original Message --------
Subject: [evol-psych] Infants Build Knowledge of Their Visual World on
Statistics
Date: Tue, 26 Nov 2002 10:56:20 -0600
From: Ian Pitchford <ian.pitchford at scientist.com>
Reply-To: Ian Pitchford <ian.pitchford at scientist.com>
Organization: http://human-nature.com/
To: evolutionary-psychology at yahoogroups.com



CONTACT: Jonathan Sherwood (585) 273-4726
November 25, 2002

Infants Build Knowledge of Their Visual World on Statistics

Baby's first look at the world is likely a dizzying array of shapes and motion
that are meaningless to a newborn, but researchers at the University of
Rochester have now shown that babies use relationships between objects to build
an understanding of the world. By noting how often objects appear together,
infants can efficiently take in more knowledge than if they were to simply see
the same shapes individually, says the paper published in the current issue of
Proceedings of the National Academy of Sciences.

Roughly 100 babies, all about nine months of age, watched a series of shapes
such as squares, circles, and arrows appearing together on a screen while
researchers watched the babies' attention. József Fiser postdoctoral fellow and
Richard N. Aslin, professor of brain and cognitive sciences, wanted to see if
the nine-month-olds would pay more attention to the pairs of shapes that
occurred most often in a crowded scene.

"It's long been assumed that we use relationships among parts of scenes to
learn which parts form whole objects, but the idea has never been tested, nor
was it clear how early this ability develops," says Fiser. "This research shows
that building a concept of the world by recognizing relationships among shapes
in images is possibly innate, and a very essential ability in babies."

To plumb the minds of infants, Fiser and Aslin had to first devise an
experiment that would test an infant's interest-a notoriously difficult
enterprise given that babies are poor communicators of their thoughts. Fiser
and Aslin first tested their experiment on college students, asking them to sit
in a secluded room and watch a video screen for 10 to 15 minutes. The students
watched groups of six shapes appear on the screen for a second or two before
being replaced by a new set. The students were then asked to pick out pairs of
shapes that they saw together most often in the previous series. Most students
balked, saying they couldn't remember the frequency of pairs from the hundreds
of scenes they'd just watched. But when pressed to pick out pairs, the students
usually picked shapes that did indeed occur most often together in the series.
"This was strong evidence that students had an ability to sense and
automatically extract relationships visually," says Fiser.

The next step was to see if nine-month-olds would display this same ability.
The babies sat on a parent's lap in the room while the shapes appeared three at
a time on a screen in front of them. After a pause, the shapes appeared again
in pairs, and the researchers timed how long the infant stared at each pair.
Fiser and Aslin wanted to know if they'd stare longer at the pairs that
appeared more often together in the first series, or stare for a shorter time,
or whether there was no correlation at all.

When the results of the 72 babies (the rest were dismissed because they
wouldn't cooperate with the pursuit of science) were tallied, a clear
correlation emerged. The babies paid more attention when two shapes that had
been paired in the first series were shown again together. The infants were
using a sort of subconscious statistical analysis of the shapes to pick out
those that were familiar, just as the students did.

"In order to make sense of the unknown you must be able to learn new things and
represent them to yourself in an efficient way," says Fiser. "You don't want a
mechanism that will tell you that leaves are always found on cars just because
you happened to see a leaf on a car once. You want a mechanism that will tell
you that cars can exist without leaves and vice versa, while at the same time
telling you that cars always come with wheels, for instance."

If a baby sees a leaf on a car, she would build a relationship between the two,
perhaps calling the combination a "leafcar." But she might then see several
cars without leaves on them and so the concept of leafcar is weakened as she
unconsciously realizes that statistically, the concept of leafcar is more and
more useless. Noting that every car she sees has wheels, however, becomes
statistically more and more useful as it is reinforced with every new car she
sees. This relationship-identification is important because the baby can build
her knowledge base on it. When she sees a wheelbarrow, she'll unconsciously
note that while all cars have wheels, not all wheels have cars, and a new
concept of wheels will begin to emerge. In this way, the frequency of
relationships, and the predictability between visual objects allows her to
build knowledge on knowledge in a hierarchical manner.

Fiser and Aslin are working on understanding more aspects of what innate ways
we have of dealing with the visual world, including studying the very basis of
the experiments themselves-why children pay attention at all. Fiser believes
that simpler tests essentially bore infants, so the babies pay more attention
to new stimuli. In more complex tests, however, it appears that babies tend to
focus on those events that are familiar because they are trying to make sense
of the scene and are using familiar sights to understand relationships and thus
build their knowledge. Fiser hopes to elucidate this distinction further to
shed more light on how our brain learns to encode the visual environment around
us.

This research was funded by the National Science Foundation.
http://www.rochester.edu/pr/News/NewsReleases/scitech/fiser-infant.html




News in Brain and Behavioural Sciences - Issue 78 - 23rd November, 2002
http://human-nature.com/nibbs/issue78.html

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--
M. Hubey
-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o
The only difference between humans and machines is that humans
can be created by unskilled labor. Arthur C. Clarke

/\/\/\/\//\/\/\/\/\/\/ http://www.csam.montclair.edu/~hubey



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