Mechanisms underlying cortical activity during value-guided choice

• Published in: Nature neuroscience Vol. 15; no. 3; pp. 470 - 476
• Main Authors: Hunt, Laurence T, Kolling, Nils, Soltani, Alireza, Woolrich, Mark W, Rushworth, Matthew F S, Behrens, Timothy E J
• Format: Journal Article
• Language: English
• Published: New York Nature Publishing Group US 01-03-2012; Nature Publishing Group
• Subjects: 631/378/116/1925; 631/378/2649/1409; Animal Genetics and Genomics; Behavioral Sciences; Biological Techniques; Biomedical and Life Sciences; Biomedicine; Biophysics; Brain; Brain Mapping; Cerebral cortex; Cerebral Cortex - physiology; Choice Behavior - physiology; Contingent Negative Variation; Decision making; Evoked Potentials, Visual; Female; Humans; Image Processing, Computer-Assisted; Judgment - physiology; Linear Models; Magnetic Resonance Imaging; Magnetoencephalography; Male; Models, Neurological; Neural Pathways; Neurobiology; Neurosciences; Photic Stimulation; Physiological aspects; Predictive Value of Tests; Psychomotor Performance; Reaction Time; United Kingdom; United Kingdom > UK
• ISSN: 1097-6256; 1546-1726
• DOI: 10.1038/nn.3017

This study uses a combination of computational modeling and magnetoencephalography to track activity while people make decisions, and finds that prefrontal and parietal cortex activity is consistent with mutual inhibition between competing options during decision-making. This activity is likely to represent a mechanism for the comparison of values while making choices.
When choosing between two options, correlates of their value are represented in neural activity throughout the brain. Whether these representations reflect activity that is fundamental to the computational process of value comparison, as opposed to other computations covarying with value, is unknown. We investigated activity in a biophysically plausible network model that transforms inputs relating to value into categorical choices. A set of characteristic time-varying signals emerged that reflect value comparison. We tested these model predictions using magnetoencephalography data recorded from human subjects performing value-guided decisions. Parietal and prefrontal signals matched closely with model predictions. These results provide a mechanistic explanation of neural signals recorded during value-guided choice and a means of distinguishing computational roles of different cortical regions whose activity covaries with value.