Effective decision-making can be predicted by measuring pupil size, according to a new study by the Leiden University.

The researchers said that spontaneous, moment-to-moment fluctuations in pupil size can be used to determine how a person will be solving a particular task. For example: a larger pupil size was associated with poorer task performance and least consistent in decisions.

For the study, the researchers measured pupil size before the commencement of a visual choice-based task and observed each of the 26 participants' subsequent performance. The task asked participants the direction of a cloud of dots. These results were then combined with a mathematical model that showed how people make decisions.

The researchers found that pupil size is a good indicator of a person's state of responsiveness that in turn reveals the variability of their decisions. For example: larger pupils are linked with increased responsiveness. When we are hyper-responsive, the decision making appears to be less reliable and more likely leads to undesirable outcomes.

These findings can help to enhance decision-making to attain better outcomes.

"We are constantly required to make decisions about the world we live in. Researchers have long known that the accuracy and reliability of such everyday decision making can be tremendously variable for different people at different times, but we understand quite little about where this variability comes from. In this study, we show that how precise and reliable a person is in making a straightforward decision about motion can be predicted by simply measuring their pupil size," Researcher Peter Murphy said in a press release.

"This finding suggests that the reliability with which an individual will make an upcoming decision is at least partly determined by pupil-linked 'arousal' or alertness, and furthermore, can potentially be deciphered on the fly. This new information could prove valuable for future research aimed at enhancing the precision of decision making in real time."

The finding is published in Journal PLOS Computational Biology.