Decoding the Neural Substrates of Reward-Related Decision Making with Functional MRI

• Published in: Proceedings of the National Academy of Sciences - PNAS Vol. 104; no. 4; pp. 1377 - 1382
• Main Authors: Hampton, Alan N., O'Doherty, John P.
• Format: Journal Article
• Language: English
• Published: United States National Academy of Sciences 23.01.2007; National Acad Sciences
• Subjects: Adult; Basal ganglia; Behavioral neuroscience; Biological Sciences; Brain; Brain - physiology; cortex; Decision making; Experimentation; Female; Humans; Learning; Magnetic Resonance Imaging; Male; Mental stimulation; Motivation; Multivariate analysis; Neurology; Neurons; NMR; Nuclear magnetic resonance; Prefrontal cortex; Reward; Signal encoding
• ISSN: 0027-8424; 1091-6490; 1091-6490
• DOI: 10.1073/pnas.0606297104

Although previous studies have implicated a diverse set of brain regions in reward-related decision making, it is not yet known which of these regions contain information that directly reflects a decision. Here, we measured brain activity using functional MRI in a group of subjects while they performed a simple reward-based decision-making task: probabilistic reversal-learning. We recorded brain activity from nine distinct regions of interest previously implicated in decision making and separated out local spatially distributed signals in each region from global differences in signal. Using a multivariate analysis approach, we determined the extent to which global and local signals could be used to decode subjects' subsequent behavioral choice, based on their brain activity on the preceding trial. We found that subjects' decisions could be decoded to a high level of accuracy on the basis of both local and global signals even before they were required to make a choice, and even before they knew which physical action would be required. Furthermore, the combined signals from three specific brain areas (anterior cingulate cortex, medial prefrontal cortex, and ventral striatum) were found to provide all of the information sufficient to decode subjects' decisions out of all of the regions we studied. These findings implicate a specific network of regions in encoding information relevant to subsequent behavioral choice.