Learning to Act in the Face of Uncertainty

Our brain learns and remembers actions differently based on the level of decision uncertainty

July 3, 2024
(Japanese version released on June 13, 2024)

National Institute of Information and Communications Technology

Abstract

A study published online in the journal Nature Human Behaviour challenges the belief that identical physical actions are governed by the same motor memory, regardless of the decision-making process involved. Researchers from the National Institute of Information and Communications Technology (NICT, President: TOKUDA Hideyuki, Ph.D.) and HONDA R&D Co., Ltd. have discovered that the brain differentiates and stores motor memories based on the level of uncertainty experienced during decision-making.
In a football (soccer) penalty shootout, a player may decide to confidently kick the ball to the right corner upon observing the goalkeeper moving in the opposite direction. Alternatively, the player might make the same kick while being unsure about the goalkeeper’s movement. Although the physical action—kicking the ball to the right—is identical in both scenarios, this new study reveals that the brain tags these actions differently based on the decision uncertainty involved. This discovery suggests that motor memories are not simply repetitions of the same action but are influenced by the cognitive processes leading up to them.
“This was a very surprising finding. This tells us that we cannot treat actions as something totally independent from the cognitive process. Both are combined to make the representation of action,” says HAGURA Nobuhiro, a senior author of the paper.
This research opens up new avenues for developing novel training methods in sports. By associating skill training with various decision-making situations, athletes can enhance their performance by refining their motor memories in context-specific scenarios.
For more information about this study, please visit the Nature Human Behaviour website (https://www.nature.com/articles/s41562-024-01911-x).

Achievements

Figure 1 Setup of the experiment
Figure 2 A: Screen of the experiment,
B: perturbation pattern
[Click picture to enlarge]

In the study, human volunteers decided whether a cloud of dots presented on a screen was moving to the left or to the right. They held a robotic handle in their right hand and moved the handle towards the target in the direction of their decision (see Figure 1, Figure 2A). The uncertainty of the decision was modulated by changing the coherence level of the dots' motion. When all the dots were moving to the left or to the right (100% coherent motion), the certainty of the decision was high. When only a small proportion of the dots were coherently moving and the other dots were moving in random directions, the situation was uncertain. Participants' hand movement to express the decision was pushed by the robotic handle to deviate from the straight path (see Figure 2B), and under this perturbation, participants were instructed to make a straight movement by resisting the force.
In one of the experiments, participants were divided into two groups: the Certain Decision group and the Uncertain Decision group. The Certain Decision group learned to make a straight movement only after deciding on a high dot coherence level motion (100%). The Uncertain Decision group learned the same action, but only after deciding on a low coherence level motion (3%). Although both groups of participants successfully learned to make a straight movement in their respective decision contexts (certain or uncertain) (see Figure 3A), their performance level dropped when they were asked to perform the same movement after decisions with different uncertainty levels (different motion coherence levels) (see Figure 3B). Participants in the Certain group could resist perturbation at the same level as during their practice after a certain decision, but not after an uncertain decision (see Figure 3B; red line). Similarly, participants in the Uncertain group could perform well after an uncertain decision, but not after a certain decision (see Figure 3B; blue line). This indicates that decision and action are not independent; action is learned in association with the decision that led to the action.

Figure 3 A: The amount of force produced to resist the perturbation for both Certain and Uncertain conditions
B: The amount of force produced for different uncertainty levels in both Certain and Uncertain conditions


In the other experiment, different types of perturbation (clockwise (CW) direction and counterclockwise (CCW) direction) were each associated with a different decision uncertainty level (see Figure 4B). If the decision uncertainty level does not differentiate the actions that follow the decision, participants should not be able to learn the two perturbations at the same time, since they would interfere with each other. However, if the decision uncertainty level 'tags' the action, participants should be able to learn the two perturbations simultaneously. Participants were indeed able to learn the two perturbations at the same time (see Figure 4A), demonstrating that the actions following certain and uncertain decisions are treated as different things in the brain.

Figure 4 A: The amount of force produced to resist the perturbation from the opposite direction, each associated with either Certain or Uncertain condition.
B: The pattern of perturbation for each Certain and Uncertain condition.

Future prospects

The researchers believe that this finding may open up new avenues for developing novel training methods in sports. By associating skill training with various decision-making situations, athletes can enhance their performance by refining their motor memories in context-specific scenarios.

Article information

Journal: Nature Human Behaviour
DOI: 10.1038/s41562-024-01911-x
Title: Decision uncertainty as a context for motor memory
Authors: Kisho Ogasa1, Atsushi Yokoi1,2, Gouki Okazawa3, Morimichi Nishigaki4, Masaya Hirashima1,2, Nobuhiro Hagura1,2

1: Center for Information and Neural Networks (CiNet), National Institute of Information and Communications Technology (NICT), Osaka, Japan
2: Graduate School of Frontier Biosciences, Osaka University, Osaka, Japan
3: Institute of Neuroscience, Key Laboratory of Primate Neurobiology, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
4: Innovative Research Excellence, Honda R&D Co. Ltd, Utsunomiya, Japan

Technical Contact

HAGURA Nobuhiro
Brain Networks and Communication Laboratory,
Center for Information and Neural Networks,
Advanced ICT Research Institute

Media Contact

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