Kimberlee D’Ardenne, Ph.D.

Kimberlee D’Ardenne Ph.D.

Quilted Science

Distracted Decisions

Less really is more, especially when it comes to how the brain makes decisions.

Posted Feb 25, 2014

The negative impact distractions—such as having many options to decide between or the use of electronic media—have on cognitive functions is supported by converging evidence from psychology, sociology and neuroscience research.  

A recent study in Nature Neuroscience provides insight into neuronal mechanisms underlying decision-making deficits caused by distraction. 

To examine how having multiple options affects decision-making, researchers from Oxford compared simulations from a biophysical model with fMRI recordings in humans. The researchers programmed the biophysical model (Figure 1a) to complete the same task as the human participants undergoing fMRI.

The task required selection of one of two rectangles, with the goal being to choose the rectangle that earned you the most amount of money.  Rectangle color and orientation encoded the amount of monetary reward.  For example, a blue rectangle tilted at 45 degrees might earn you the most money while a green rectangle tilted at 15 degrees gave less money.

Sometimes during the experiment, a third rectangle appeared. This third rectangle was a “distractor” because though it had a reward value associated with it, it was never actually available to be chosen (Figure 2a). Just the presence of this distractor rectangle worsened decisions made by both human participants and by the biophysical model.

Distraction impeding decision-making is understandable. When that third rectangle shows up, you pay some attention to it, and even though you know you cannot choose it, you still compare its value to the options you can choose. You might think that the larger the value of the distractor, the more it affected decisions. But the interesting, and unexpected, twist in this study is the exact opposite effect: the lower the value of the distractor, the more it impacted decision-making.

Model simulations suggested a role for a specific class of neuron, an interneuron, in explaining why a low value distractor had a greater impact than a large value distractor.  Interneurons connect other neurons together into circuits. In a simple brain circuit, some neurons collect incoming information and other neurons output signals that guide behavior. Interneurons are involved in the computations between the input and output stages.  

In this experiment, the activity level of one group of neurons expresses the reward value of the first rectangle and another group of neurons encodes the reward value of the second rectangle. The circuit compares the activity levels of the two groups of neurons. Whichever rectangle has greater neuronal activity would be chosen. Interneurons are thought to inhibit the outcome pathways for the non-selected option.

Model simulations showed that low value distractors led to less interneuron activity. Simulated neural activity encoding the suboptimal choice (lesser value) was so similar to neural activity encoding the optimal choice, the circuit could not correctly identify the higher value option.

fMRI revealed responses similar to model simulations in one brain area, the ventromedial prefrontal cortex. A function of the ventromedial prefrontal cortex seems to be encoding the difference in value between two choices (like the two rectangles).  In agreement with the model simulation results, activity in ventromedial prefrontal cortex decreased as the distractor value decreased (Figure 4a). Also, activity measured from ventromedial prefrontal cortex correlated with the kinds of decisions participants made (Figure 5b and 5c). The ventromedial prefrontal cortex does not work in isolation (few brain areas do), and distraction has widespread effects on the brain. 

Distractions are an unavoidable part of life. (I encountered quite a few distractions while writing this post!) Understanding how distractions affect the brain, enabling suboptimal decisions and other cognitive deficits, is the first step in identifying compensating strategies.

About the Authors

Kimberlee D’Ardenne, Ph.D.

Kimberlee D’Ardenne, Ph.D. is a neuroscientist by training, science writer by choice.

Rachael Grazioplene

Rachael Grazioplene is a graduate student in Psychology at the University of Minnesota. Her research is focused on individual differences and behavioral genetics.

Daniel Hawes

Daniel R. Hawes is a social psychologist stuck in an applied economist's body.

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