Distractions may change our perceptions of reality

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We live in a world of distractions.

We multitask our way through our days.

We wear watches that alert us to text messages. We carry phones that buzz with breaking news.

You might even be reading this story because you got distracted.

A new study suggests that distractions – those pesky interruptions that pull us away from our goals – might change our perception of what’s real, making us believe we saw something different from what we actually saw.

Even more troubling, the study suggests people might not realize their perception has changed – to the contrary, they might feel great confidence in what they think they saw.

“We wanted to find out what happens if you’re trying to pay attention to one thing and something else interferes,” said Julie Golomb, senior author and associate professor of psychology at The Ohio State University.

“Our visual environment contains way too many things for us to process in a given moment, so how do we reconcile those pressures?”

The results, published online recently in the Journal of Experimental Psychology: Human Perception and Performance, indicate that, sometimes, we don’t.

Results showed that people sometimes confused the color of an object they were supposed to remember with one that was a distraction.

Others overcompensated and thought the color they were supposed to remember was even more different from the distraction object than it actually was.

“It implies that there are deeper consequences of having your attention drawn away that might actually change what you are perceiving,” said Golomb, who is director of Ohio State’s Vision and Cognitive Neuroscience Laboratory.

“It showed us that we clearly don’t understand the full implications of distraction.”

To evaluate how distraction interacts with reality, the researchers showed study participants four different-colored squares on a computer screen.

The researchers asked participants to focus on one specific square.

But sometimes a bright distractor appeared around a different square, pulling the participant’s attention away, even briefly, from the original square of focus.

The researchers then showed study participants a color wheel containing the entire color spectrum and asked them to click on the wheel where the color most closely matched the color of the original square.

Participants then highlighted a range of the color wheel to indicate how confident they were in their choice.

Highlighting a narrow range indicated great confidence; highlighting a wider range indicated less confidence.

The results showed that the distraction color “bled” into the focus color in one of two ways: Either people thought the focus square was the color of the distraction square, or they overcompensated, choosing a hue of the focus color that was farther away on the color wheel from the distraction color.

For example, if the focus square was green and the distraction color orange, participants clicked in the blue-green area of the wheel – close to the original color, but farther away from the distraction color, as if to overcompensate.

Even more striking, the results showed participants were just as confident when they clicked on the distraction color as when they selected the correct color.

“It means that, on average, those two types of responses were associated with the same confidence range size,” Golomb said. “On the trials where they reported the distractor color, they didn’t seem aware that it was an error.”

A new study suggests that distractions might change our perception of what’s real, making us believe we saw something different from what we actually saw.

This study included 26 participants. Additional research is already underway at Ohio State to attempt to answer more questions about the ways in which distractions interact with reality.

“It raises an interesting consequence for memory – could it be that, if distraction happens with the right timing, you might adopt elements from the distraction into the thing you think you remember?

Could it mean that some of our memory errors might be because we perceived something wrong in the first place?” said Jiageng Chen, lead author and graduate student researcher at Ohio State’s Vision and Cognitive Neuroscience Laboratory. “We don’t know yet, but it is an interesting area for future study.”

Funding: Andrew Leber, an associate professor of psychology at Ohio State, is also co-author of this research, which was funded by grants from the National Institutes of Health and the National Science Foundation.


In this series of behavioural experiments we investigated the effect of distraction on the maintenance of acoustic scene information in short-term memory.

Stimuli are artificial acoustic ‘scenes’ composed of several (up to twelve) concurrent tone-pip streams (‘sources’). A gap (1000 ms) is inserted partway through the ‘scene’; Changes in the form of an appearance of a new source or disappearance of an existing source, occur after the gap in 50% of the trials.

Listeners were instructed to monitor the unfolding ‘soundscapes’ for these events. Distraction was measured by presenting distractor stimuli during the gap. Experiments 1 and 2 used a dual task design where listeners were required to perform a task with varying attentional demands (‘High Demand’ vs. ‘Low Demand’) on brief auditory (Experiment 1a) or visual (Experiment 1b) signals presented during the gap.

Experiments 2 and 3 required participants to ignore distractor sounds and focus on the change detection task.

Our results demonstrate that the maintenance of scene information in short-term memory is influenced by the availability of attentional and/or processing resources during the gap, and that this dependence appears to be modality specific. We also show that these processes are susceptible to bottom up driven distraction even in situations when the distractors are not novel, but occur on each trial.

Change detection performance is systematically linked with the, independently determined, perceptual salience of the distractor sound. The findings also demonstrate that the present task may be a useful objective means for determining relative perceptual salience.

A key issue in our pursuit to understand listening in crowded environments involves uncovering how perceptual encoding of the auditory scene is affected by interference from distracting events or from listeners’ competing perceptual goals.

Distraction reflects a basic function of the perceptual system – a mechanism that enables potentially relevant events, outside of the current focus of attention, to penetrate perception (Lavie, 2010Parmentier, 2014).

The key questions relate to what determines which unattended sounds will capture attention, and how the process of attentional capture affects the perceptual representation of other elements in the scene (Stothart et al., 2015Mentis et al., 2016).

In hearing, distraction has often been studied using paradigms which involve embedding task relevant and task irrelevant sound features within a single sound stream and measuring the extent to which performance (usually quantified by response time; RT) is affected by irrelevant feature changes (e.g. Schröger and Wolff, 1998Schröger et al., 2000Roeber et al., 2003Horváth et al., 2011Boll and Berti, 2009; for a review see Dalton and Hughes, 2014Frings et al., 2014).

Here we study distraction in the context of a change detection paradigm. Change detection is a core capacity of hearing (Demany et al., 2010Cervantes Constantino et al., 2012).

The auditory system is widely assumed to serve as an ‘early warning system’ which continuously scans the unfolding acoustic scene for behaviourally-relevant events (e.g. those that could indicate the approach of predators or prey) even when attention is focused elsewhere.

A change detection task is therefore a pertinent and ecologically relevant means by which to probe listeners’ susceptibility to distraction and its effects on auditory scene analysis.

Stimuli are artificial acoustic ‘scenes’ composed of several (up to twelve) concurrent sound-sources (auditory objects), each consisting of a sequence of tone pips characterized by a unique frequency and rate. Listeners are instructed to monitor the unfolding ‘soundscapes’ for occasional changes manifested as the appearance or disappearance of a source.

In a previous series of experiments (Cervantes Constantino et al., 2012), we demonstrated that these stimuli are perceived as a composite ‘sound-scape’ in which individual streams can be perceptually segregated and selectively attended to, and are therefore good models for the challenges encountered in natural listening situations.

This paradigm has been extensively used in our laboratory for probing the ability to detect changes in crowded acoustic environments (Cervantes Constantino et al., 2012Sohoglu and Chait, 2016Southwell et al., in press). Here we use a variant of the basic stimulus that incorporates a 1000 ms silent gap inserted partway through the scene, with changes (50% of the trials) occurring immediately thereafter (See Fig. 1). Distraction is quantified by measuring change detection performance as a function of the properties of an interfering signal presented during the gap. The behavioural relevance of the signal is varied across experiments.

The gap models scene interruptions which listeners regularly experience in the environment. Such disturbances may occur as a result of energetic masking, acoustic occlusion, or movement of the listener. To maintain continuity of our perceptual experience, the auditory system must rely on a memory store which retains scene information over short durations (Demany et al., 2010). The susceptibility of these mechanisms to distraction and processing load is at the centre of the present work. Presumably, to detect the scene changes, listeners must encode and preserve the pre-gap scene in short-term memory and compare this representation to the signals presented after the interruption (see also Nolden et al., 2013aNolden et al., 2013b). Stimuli presented during the gap may disrupt this process by capturing attention away from the maintained signal (Zimmermann et al., 2016Parmentier, 2014) or by depleting the computational resources required for maintenance. To uncover these effects, the experiments below measured how change detection performance is affected by limited availability of attentional resources during the gap or by the presence of a (task irrelevant) distractor.

Our results demonstrate that the maintenance of scene information in short-term memory is affected by the (un) availability of attentional resources during the gap, and that this dependence appears to be modality specific. We also show that these processes are susceptible to bottom-up driven distraction even in situations when the distractors are not novel, but occur regularly on each trial. The extent of the disruption is systematically linked with the, independently determined, perceptual salience of the distractor.


Source:
Ohio State University
Media Contacts:
Laura Arenschield – Ohio State University
Image Source:
The image is credited to Ohio State University.

Original Research: Closed access
“Attentional capture alters feature perception”. Chen, Jiageng; Leber, Andrew B.; & Golomb, Julie D.
Journal of Experimental Psychology: Human Perception and Performance doi:10.1037/xhp0000681

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