Predictability of investment behavior from brain information measured by functional near-infrared spectroscopy: a bayesian neural network model.

In line with previous studies using fMRI and as is apparent from experimental results, cerebral blood flow (oxygenated hemoglobin (oxyHb) concentration) in the medial prefrontal cortex (MPFC) and orbital cortex (OFC) as is observed with fNIRS (functional near-infrared spectroscopy) is presumed to be closely related to reward prediction and risk prediction as part of decision-making under risk. Results of analysis using a predictive model with a three-layer perceptron revealed that changes in the oxyHb concentration in cerebral blood as indicated by fNIRS observation include information to effectively predict investment behavior. This paper indicates that adding oxyHb concentration at the aforementioned sites in the brain as a predictive factor allows prediction of subjects' investment behavior with a considerable degree of precision. This fact indicates that information provided by fNIRS allows valid analysis of investment behavior and it also suggests a wide-ranging practical applicability for this information like investment assistance using fNIRS.