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Effective decision-making requires consideration of costs and benefits. Previous studies have implicated orbitofrontal cortex (OFC), dorsolateral prefrontal cortex (DLPFC), and anterior cingulate cortex (ACC) in cost-benefit decision-making. Yet controversy remains about whether different decision costs are encoded by different brain areas, and whether single neurons integrate costs and benefits to derive a subjective value estimate for each choice alternative. To address these issues, we trained four subjects to perform delay-and effort-based cost-benefit decisions and recorded neuronal activity in OFC, ACC, DLPFC, and the cingulate motor area (CMA). Although some neurons, mainly in ACC, did exhibit integrated value signals as if performing cost-benefit computations, they were relatively few in number. Instead, the majority of neurons in all areas encoded the decision type; that is whether the subject was required to perform a delay-or effort-based decision. OFC and DLPFC neurons tended to show the largest changes in firing rate for delay-but not effort-based decisions; whereas, the reverse was true for CMA neurons. Only ACC contained neurons modulated by both effort-and delay-based decisions. These findings challenge the idea that OFC calculates an abstract value signal to guide decision-making. Instead, our results suggest that an important function of single PFC neurons is to categorize sensory stimuli based on the consequences predicted by those stimuli.

Activity in prefrontal cortex (PFC) has been richly described using economic models of choice. Yet such descriptions fail to capture the dynamics of decision formation. Describing dynamic neural processes has proven challenging due to the problem of indexing the internal state of PFC and its trial-by-trial variation. Using primate neurophysiology and human magnetoencephalography, we here recover a single-trial index of PFC internal states from multiple simultaneously recorded PFC subregions. This index can explain the origins of neural representations of economic variables in PFC. It describes the relationship between neural dynamics and behaviour in both human and monkey PFC, directly bridging between human neuroimaging data and underlying neuronal activity. Moreover, it reveals a functionally dissociable interaction between orbitofrontal cortex, anterior cingulate cortex and dorsolateral PFC in guiding cost-benefit decisions. We cast our observations in terms of a recurrent neural network model of choice, providing formal links to mechanistic dynamical accounts of decision-making.DOI: http://dx.doi.org/10.7554/eLife.11945.001

We assessed the reliability and validity of the Multidimensional Health Locus of Control Scale (MHLC scale) in a rural Japanese community. The study subjects were 2388 men and 2454 women aged 40-79 years, who completed a questionnaire regarding socio-demographics, healthrelated behavior, such as smoking and drinking, and the MHLC. The Cronbach α of the MHLC scale, which is an indicator of the internal consistency of the scale, was within the range 0.62-0.76. Elderly subjects, women, and subjects with fewer years of education showed more "external" belief, which is generally consistent with previous reports from overseas. Subjects with adverse health behavior, such as smoking and excess drinking, also had more "external" belief. These results indicate that the MHLC scale has sufficient reliability and validity among the Japanese population. Use of the MHLC scale should help to provide a better understanding of health belief among Japanese, and development of health education programs to prevent lifestylerelated disease.health locus of control; health behavior; validity; reliability