Whether finding your way through an unfamiliar neighborhood to a friend's house or deciding on a political candidate, your brain is adept at adapting.
It can make decisions based on incomplete information and update those decisions based on new information.
The nature of such sophisticated decision making in the cerebral cortex, which is responsible for high-level processing, has been "poorly studied and little understood," according to Wako Yoshida and Shin Ishii of the Nara Institute of Science and Technology. Now, however, in an article in Neuron, they describe experiments that enabled them to tease apart how different regions of the cerebral cortex process uncertain information and integrate it into decision making.
In particular, their aim was to analyze subjects' navigation through a virtual maze, to explore how different cortical regions function in solving "partially observable decision-making problems."
"In navigation tasks, such as that investigated here, an individual must constantly maintain an estimate as to his/her current location as a guide for deciding the next turn," they wrote, "but in the absence of incontrovertible a priori information, this estimate is best represented by the subject's belief. As information is acquired through observation, this belief may become increasingly convincing or alternatively may be discarded in favor of a new one. This is an intuitive way of making estimations that are appropriate for many real-world behaviors, adopted also by a wide variety of intelligent machines.," they wrote.
In their experiments, the researchers first taught volunteer subjects the layout of a computer-generated 3D "wire-frame" maze. Then, while the subjects' brains were being scanned using functional magnetic resonance, the researchers "placed" the subjects in different parts of the maze and analyzed activation of cerebral cortical regions as the subjects made a series of decisions to navigate their way to a specified goal. Functional MRI involves using harmless magnetic fields and radio waves to image blood flow in brain regions, which reflects activity.
Importantly, Yoshida and Ishii used sophisticated statistical probabilistic analysis of the subjects' movements to overcome a major obstacle to such studies. That obstacle is that the beliefs of the subjects during the experiment could not be determined unequivocally; thus, those beliefs could not be correlated with brain function.