Sen. Res. Fellow Jaan Aru, Institute of Computer Science, University of Tartu
Dr. Michael Gaebler, Max Planck Institute for Human Cognitive and Brain Sciences (Germany)
Dr. Jakub Limanowski, Technische Universität Dresden (Germany)
Which computational principles guide our thinking and behaviour? Although we know the anatomy of the brain in great detail, we are still lacking a clear understanding about the algorithms implemented in the brain. Over the last decade an unifying theory about brain functioning has become dominant among researchers, called the free energy principle. It tries to explain both perception and action by claiming that the brain always tries to minimize surprising situations using active inference.
To test active inference, we studied if the brain pays less attention to the visual consequences of its own predicted limb movements. This means that other objects in the same area of field of view where the limb is moving should also be harder to spot for the person. We asked people to move their hand in front of their eyes while wearing a head-mounted display, but turned the precisely tracked hand virtually invisible so the hand itself would not visually interfere with the experiment. This allowed us to measure if people reacted more slowly or perceived worse the objects shown exactly behind the invisible hand. During the research we also developed open source virtual reality software and guidelines for future studies.
Our results showed effects of longer reaction time and lower contrast perception when the test objects appeared behind the participants invisible virtual hand. These results fit well with the active inference framework of the free energy principle. These findings give us further insights on the computations of the human brain, but are also useful for medicine, robotics and artificial intelligence. Also, the notion of being less able to perceive the consequences of our own actions has value for the design of pro-environmental sustainable behaviours.