Before revision: Theories and tools to measure the efficiency of neural codes have been important in understanding neural responses to external stimuli. However, similar principles to describe the efficiency of brain responses to tasks demanding higher-order cognitive processes remain underdeveloped. A key domain to study such efficiency is learning, where patterns of activity across the entire brain provide insight into the principles governing the acquisition of knowledge about objects or concepts. We propose a mathematical framework for studying the efficiency of spatially embedded whole-brain states reflected in functional MRI , and demonstrate its utility in describing how human subjects learn the values of novel objects .
After revision: A fundamental cognitive process is the ability to map objects into meaningful categories depending on the task at hand. Exactly how such mental constructs emerge and what kind of space best embeds this mapping remains incompletely understood. Here we develop tools to quantify the space URLanization of such a mapping, thereby providing a framework for studying the efficiency of spatially embedded whole-brain states reflected in functional MRI , and demonstrate its utility in describing how human subjects learn the values of novel objects .