Perception and memory: Slaves of our context

It was once thought that what we perceive is a straightforward reflection of a stable reality. So, we see a circle to be a certain size because it is a certain size. A quick glance at illusions such as the Ebbinghaus illusion and the Rubik’s cube color illusion clearly show that this is not the case: what we perceive is importantly dependent on context—try and perceive the orange circles below as being the same size. They are identical in size, but most people cannot readily “see” them that way.

Source: Wikimedia

This intuition of stability also pervades how many people think of preferences and memories. For example, it is reasonable to assume that how much you prefer a certain color to another one will remain the same if asked on Tuesday vs Wednesday. In the case of memories, we often assume that our ability to remember something or someone is largely independent of context. For example, if I can recognize a co-worker in her office, I might (quite reasonably) assume that I’ll be able to recognize her at the gym. And yet, as with the case of perception, these intuitions appear to be mistaken.

Two papers recently published in Psychonomic Bulletin & Review nicely demonstrate the problems with such intuitions.

Color preferences and context

A now-substantial body of evidence indicates that people’s color preferences are broadly predictable from the combined preferences for all the objects and entities associated with that color. Basically, the reason why people like blue and hate brown is that there are more “good” things that are blue than there are “good” things that are brown.

Armed with this theory (the ecological valence theory), researchers Schloss and Palmer examined whether people’s allegiance to a political party predicted their color preferences. Did Republicans prefer red more than Democrats?

Participants ranked each of the colors shown in the figure below according to how much they liked it. The colors were shown one at a time and participants used a slider labeled “not at all” to “very much” to rate each color. Among the 16 colors were “Republican-red” and “Democratic-blue.” (As the authors point out, these color-color designations are actually relatively recent. Apparently, during the 1984 election, the election map referred to pro-Reagan regions as the “suburban swimming pool”, displaying them in blue).

Importantly, nothing about the color-preference questionnaire hinted that it had anything to do with politics. Questions about political affiliation always came after the completely neutrally-worded color-preference task.

The results showed that there was no difference in preference for Republican-red among Democrats and Republicans and, if anything, Republicans liked Democratic-blue more than Democrats did! But the authors noticed something curious. Some of the original data was collected on November 2, 2010—Election Day. And on Election Day, people’s color preferences shifted quite dramatically. In particular, Democrats’ preference for red decreased and their preference for blue increased. The authors waited until the 2012 election to collect more data and observed a similar pattern: Preferences for party-consistent colors were found, but only on Election Day. These results nicely demonstrate the flexible, context-dependent nature of what are usually considered stable preferences.

Memory and context

It has long been known that memory is context sensitive: in one famous study from the 1970s, scuba divers learned lists of words either on dry land or underwater and recalled them in the same or the other environment. Lists learned underwater were best recalled underwater, and vice versa.

new paper by Deffler, Brown and Marsh pushed this examination of context one step farther. Rather than examining how memories can be accessed in different contexts, this study tested whether different contexts affected how familiar a given face seemed to participants.

The basic procedure was simple. Participants viewed scenes of famous landmarks, novel nondescript scenes, and plain colors. Half a second later a face appeared. Participants then simply indicated how familiar the face seemed to them. The procedure is summarized in the figure below:

The faces ranged from familiar celebrities to unfamiliar (yearbook pictures of complete strangers). Not surprisingly, some of the strangers’ faces appeared familiar to some participants. The question was whether this (random) feeling of familiarity was greater when the face was presented alongside a familiar location (e.g., the Washington Monument or the Eiffel Tower) rather than next to an unfamiliar location. This was indeed the case. The familiarity of the location seemed to “bleed through,” making unfamiliar faces more familiar. Surprisingly, the effect persisted (indeed, became stronger) when participants were asked to rate the familiarity of the location and the face separately. Making these two judgments did not help participants separate the two possible sources of familiarity.

As with perception and preferences, our sense of the familiarity of a never-before-seen face was influenced by the context in which it appeared.

Results such as these are important in showing that our intuitions of stability and context-invariance (what Daniel Casasanto and I called “conceptual change blindness”) may be illusions, deriving from the often predictable environment and context in which we live, rather than genuinely stable internal representations. In an nutshell, much of human behavior and cognition is driven by context, and more often than not we remain unaware of how much we are creatures of context.

Author

  • Gary Lupyan’s primary research interest is understanding how language shapes the human mind. To what extent is human cognition, actually language augmented cognition? To answer this question, Gary uses a wide variety of techniques that attempt to manipulate linguistic variables and observe the consequences of these manipulations on putatively nonlinguistic behavior. Gary’s methods include lab-based and crowdsourced behavioral studies, neural network modeling, statistical corpus analyses, and neurostimulation techniques such as transcranial direct current stimulation (tDCS) and transcranial magnetic stimulation (TMS). In addition to understanding effects of language on cognition and perception, Gary is deeply interested in what environmental circumstances led to the emergence of language. Language marked a major transition in the history of life by providing a secondary information transmission medium—culture—and its evolution was, as far as we know, a singular event in the history of life on earth. Gary attended Carnegie Mellon for graduate school, working with Jay McClelland, followed by postdoctoral work in cognitive neuroscience at Cornell University and University of Pennsylvania. Since 2010 he has been an assistant professor of psychology at University of Wisconsin-Madison.

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