by Adam Hadhazy, Princeton University
By
having thousands of people play the visual equivalent of the "telephone
game," where errors accumulate as a message is passed on, Princeton
researchers have gathered new insights into the human visual system.
In
a recent study, the researchers explored the distortions that bias our
memory regarding the locations of objects and details within a scene.
These distortions creep in because our visual system cannot process the
torrent of information constantly pouring in as we view the world around
us. Our brains accordingly boil things down to focus on only the most
important bits.
"We
have this illusion that the world just impinges on us, and we are
something like a camera that records everything around us. But that's
actually not true," said Thomas A. Langlois, the study's lead author and
a postdoctoral researcher in the lab of Tom Griffiths, a Professor of
Psychology and Computer Science at Princeton. "We in fact have very
limited perceptual resources and we cannot record every detail. So we
have to constantly interpret the world around us by bringing in a lot of
prior beliefs and knowledge to fill in the blanks."
The
study revealed how people are prone to distort spatial information
based on their shared expectations about a scene. The findings buck
conventional theories that people simply fill in the blanks in their visual memory by
skewing recall towards the center of objects; instead, people tend to
biasedly recall points appearing near the vertices (where angles meet)
of geometric shapes, for instance, as well as on the eyes and noses of
faces, to give just two examples.
"In
this study, we demonstrated an experimental technique that reveals the
shared, prior beliefs people bring that are hidden from view but are an
essential part of how vision works," said Griffiths, the senior author
of the study published in the Proceedings of the National Academy of Sciences.
The
telephone-like game revealed these patterns of encoding visual memory
by tasking participants with recalling the location of a red dot one
second after it disappeared from an image on a computer screen. Due to
imperfect human spatial memory, participants were slightly off in their
recollection of the exact location of that first dot. These imperfect
answers then served as the locations for second dots, seen by a new
round of participants unaware of the original dots' locations. The
second set of participants likewise introduced some error in their
recall response, with their response then serving as the stimuli for a
third round of participants, and on into a fourth round, and so on.
Just
like in the telephone game, the original message (or location of the
dot, in this case) became increasingly garbled, but in a way that
reflected the distortions people commonly make. For instance, if
Participant 1 recalled a dot closer to a triangle corner than it
actually was, Participant 2 was also likely to misremember the dot as
being even closer to the corner, and so on, such that after enough
rounds, the location of the dot settled into the corner.
"Remarkably,
what you see is that people tend to produce the same kinds of errors,"
said Langlois. "You see the recall errors start to migrate towards these
landmarks and eventually converge as you go through many iterations."
Most
studies that have previously tried to get to the root of visuospatial
memory bias have had small numbers of participants go through single
iterations or rounds of a recall challenge. Those results varied wildly
from person to person, leading to averages being drawn that painted the
middle of objects as apparent magnets of skewed recall.
The
Princeton-led study, however, recruited a huge pool of
participants—9,202 in all—via the Amazon Mechanical Turk crowdsourcing
platform. In total, those participants ran through 20 iterations of 85
separate dot placement experiments. The massive amount of collected data
newly showed that the visual system more selectively and efficiently
allocates the encoding of memory with variable precision across objects
in space—for instance, toward certain landmarks—rather than with the
fixed encoding precision assumed based on prior studies.
From
these findings, the research team proposed what they call an efficient
encoding model. The model holds that because of the brain's finite
resources ultimately limiting our ability to store all regions of a
visual scene in memory with equal accuracy, there is an optimal
trade-off between memory-encoding resources and precision. "We encode
different regions of space with changing degrees of precision and
accuracy," said Langlois.
As
a future research angle, Langlois would like to examine people's
visuospatial memory biases in three-dimensional spaces such as virtual
reality environments, instead of the merely two-dimensional screens used
in the current study.
By
offering new insights into how people visually process information, the
findings might help in the design of more effective user interfaces for
computers and other devices. Another application area, Langlois said,
is enhancing the performance of machines that interact with humans. The
robots' programming could benefit from a greater understanding of the
inferences people make about a visual environment when navigating it.
"There
is a lot more we hope to learn through using this telephone game
technique about the hidden beliefs that shape our perception from moment
to moment," said Langlois.