Guest Editorial Neuroeconomics: A Neural Engineering Perspective

Abstract

HE question of how we make, and how we should make, judgments and decisions has occupied thinkers for many centuries, with different disciplines approaching the problem with characteristically different techniques. A very recent approach, known as neuroeconomics, has the goal to integrate ideas from the fields of psychology, neuroscience, and economics in an effort to specify more accurate models of choice and decision. This special issue of “Neuroeconomics: Modeling and imaging the brain activity during economic transactions” is trying to include both the state-of-technique papers on the methodologies and models that it can be used in this field on humans. The scenario that comes out from the series of papers chosen from active authors in this new area of science is really interesting. From one side, there is the development of methodologies that allows estimate the brain activity during decision making tasks by using hemodynamic [1] or electromagnetic modalities [2], [3]. On the other side, there are contributions about theoretical [4] and practical aspects [5] of the application of neural engineering to the neuroeconomics. In particular, the paper of Grosenik et al. [1] faced with the attempt to classify sensory inputs in order to directly predict the behavioral output, by using the hemodynamic information related to the brain activity. They applied different machine learning algorithms to previously acquired data to examine the ability of functional magnetic resonance imaging (fMRI) activation in three regions—the nucleus accumbens (NAcc), medial prefrontal cortex (MPFC), and insula—to predict purchasing. Their goal was to improve spatiotemporal interpretability as well as classification accuracy. The use of electroencephalographic data was instead promoted in the context of prediction of particular memorization of TV advertising in the paper of Astolfi et al. [2]. There, the signs of brain activity related to the observation of TV ads were detected by using advanced statistical techniques. The techniques presented here shed new light on all thecortical networksandtheir behavior duringthememorization of TV commercials. Such techniques could also be relevant in neuroeconomics and neuromarketing for the investigation of the neural substrates subserving other decision making and recognition task. The use of EEG technology was also promoted in the paper of Bordaud et al. [3] for the study of the correlates of the brain electrical activity related to the exploratory behavior. In fact, decision making in an uncertain environment arises a conflict between two opposing needs: gathering infor