Complex behavior typically relies upon many different processes which are related to activity in multiple brain regions. In contrast, neuroimaging analyses typically focus upon isolated processes. Here we present a new approach, combinatorial brain decoding, in which we decode complex behavior by combining the information which we can retrieve from the neural signals about the many different sub-processes. The case in point is visuospatial navigation. We explore the extent to which the route travelled by human subjects (N = 3) in a complex virtual maze can be decoded from activity patterns as measured with functional magnetic resonance imaging. Preliminary analyses suggest that it is difficult to directly decode spatial position from regions known to contain an explicit cognitive map of the environment, such as the hippocampus. Instead, we were able to indirectly derive spatial position from the pattern of activity in visual and motor cortex. The non-spatial representations in these regions reflect processes which are inherent to navigation, such as which stimuli are perceived at which point in time and which motor movement is executed when (e.g., turning left at a crossroad). Highly successful decoding of routes followed through the maze was possible by combining information about multiple aspects of navigation events across time and across multiple cortical regions. This "proof of principle" study highlights how visuospatial navigation is related to the combined activity of multiple brain regions, and establishes combinatorial brain decoding as a means to study complex mental events that involve a dynamic interplay of many cognitive processes.
Keywords: fMRI; motor cortex; objects and faces; pattern classification; visual cortex.