What the neuroscience of Rock-Paper-Scissors reveals about winning and losing

In the high-stakes world of business negotiations, sports, or even a simple game between friends, the goal is often the same: to anticipate an opponent’s move while keeping your own unpredictable. What goes on inside our brains during these moments of competition? And is there a detectable difference in the neural activity of those who win versus those who lose?

A team of researchers set out to investigate these questions using a familiar contest: the game of Rock-Paper-Scissors. Their study, published in the journal Social Cognitive and Affective Neuroscience, explored the brain activity of competing players in real time. The investigation revealed a pattern suggesting that players who lost were more likely to have their brains hang on to information from previous rounds.

The inquiry was led by a group of scientists, including Denise Moerel and Manuel Varlet, at the MARCS Institute for Brain, Behaviour and Development at Western Sydney University. Their work addresses a gap in the field of social neuroscience. While many studies have examined brain activity during cooperative tasks, far less is known about the neural processes that occur during competition.

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Cooperation and competition present the brain with different challenges. To cooperate effectively, it helps to be predictable, allowing partners to anticipate actions and coordinate. In many competitive scenarios, the opposite is true. Success often depends on being unpredictable to gain an advantage over an opponent.

To observe the brain during a live social interaction, the team used a technique called hyperscanning. This method involves simultaneously recording brain activity from two or more people as they interact. The researchers specifically used electroencephalography, known as EEG, which employs a cap fitted with sensors to measure the brain’s electrical signals with high temporal precision.

The Rock-Paper-Scissors game served as an ideal model for their investigation. While it appears simple, the optimal strategy is to be completely random, making your moves impossible for an opponent to guess. Past research has shown, however, that humans are not very good at generating random behavior. People tend to fall into patterns or biases, such as favoring one choice over others.

With these concepts in place, the researchers designed an experiment to see what information the brain encodes during the game. They wanted to know if they could detect a player’s chosen move, their opponent’s move, or even information from past rounds simply by looking at their EEG signals.

The investigation involved 62 participants, who were organized into 31 pairs. Each person sat in a separate room, viewing a computer screen and wearing an EEG cap. The pairs played a total of 480 rounds of computerized Rock-Paper-Scissors against each other.

Each round of the game was broken into three distinct phases. First was the Decision phase, a two-second window where players were prompted to decide on their move. Next came the Response phase, another two-second period when they physically selected Rock, Paper, or Scissors on the screen. Last was the Feedback phase, which lasted for one second and showed both players’ choices and the outcome of the round.

While the participants played, the researchers collected their behavioral choices and their continuous EEG data. The first part of the analysis looked at the players’ behavior. As expected, the participants did not play randomly. The data showed a distinct bias toward choosing Rock, which was the most selected option for over half of the players. Scissors was the least favorite choice.

The analysis also confirmed that players’ moves were somewhat predictable. Using a computational model, the researchers found they could guess a player’s next move with an accuracy greater than pure chance would allow. This indicated that players were, consciously or not, following patterns.

Next, the team turned to the brain data. They used a machine learning technique known as decoding. This method involves training a computer algorithm, called a classifier, to recognize patterns in the EEG data associated with specific events. For example, they trained the algorithm to see if it could distinguish the brain activity for a “Rock” decision from that of a “Paper” or “Scissors” decision.

The decoding analysis produced several findings. The algorithm was able to identify a player’s own choice from their brain activity. This signal appeared even during the Decision phase, before the player had physically made their selection. This suggests the technology was tracking the decision as it was forming in the brain.

The researchers also tried to decode the opponent’s choice from a player’s brain signals during the Decision and Response phases. They found no evidence that players could predict their opponent’s next move. The decoding accuracy was at chance level, indicating that what the other player was about to do was not represented in their opponent’s brain activity.

A different picture emerged when the researchers analyzed the data based on who ultimately won or lost the entire 480-game match. For this analysis, they labeled each participant in a pair as either the overall “winner” or “loser.” Both winners’ and losers’ brains showed clear signals corresponding to their own decision in the current round.

The key difference appeared when the researchers looked for information about past rounds. The analysis revealed that the brains of losers contained information about what they themselves had played in the previous round. Their brains also encoded what their opponent had played in the prior game. This neural information was present during the Decision phase of the current round.

For the group of winners, this pattern was absent. The algorithm could not detect strong signals related to the previous round’s events in their brain activity. The results point to a distinction in how the brains of winners and losers processed information from the past. The losers’ brains appeared to retain this information, while the winners’ brains did not.

The scope of this research was focused on a simple, repetitive game. As the authors noted in an article for The Conversation, “rock, paper, scissors is one of the simplest games we could use – it made for a good starting point for this research.” The controlled setting allowed them to isolate specific neural signals related to decision-making.

For those in business, the findings offer a thought-provoking parallel. While strategic memory is often beneficial, this study raises the possibility that in certain competitive contexts, dwelling on past outcomes could be counterproductive. The authors suggest, “A good takeaway here is that people who stop overanalysing the past may have a better chance at winning in the future.”

This work opens up new avenues for future studies. The researchers suggest that the next steps could involve moving into competitive settings where tracking past decisions is a more integral part of the strategy. This could include more complex games or simulated business negotiations. New questions arise from these findings. For instance, would the same neural patterns appear in cooperative tasks where remembering a partner’s previous actions is essential for success?

The study contributes to a broader understanding of human social interaction. “Our brains are bad at being unpredictable,” the authors write at The Conversation. “This is a good thing in most social contexts and could help us during cooperation. However, during competition, this can hinder us.” By isolating the neural markers of competitive decision-making, this research provides a new lens through which to view the complex dance of strategy, memory, and performance.