No abstract

Most experimental studies of decision-making have specifically examined situations in which a single less-predictable correct answer exists (externally guided decision-making under uncertainty). Along with such externally guided decision-making, there are instances of decision-making in which no correct answer based on external circumstances is available for the subject (internally guided decision-making). Such decisions are usually made in the context of moral decision-making as well as in preference judgment, where the answer depends on the subject’s own, i.e., internal, preferences rather than on external, i.e., circumstantial, criteria. The neuronal and psychological mechanisms that allow guidance of decisions based on more internally oriented criteria in the absence of external ones remain unclear. This study was undertaken to compare decision-making of these two kinds empirically and theoretically. First, we reviewed studies of decision-making to clarify experimental–operational differences between externally guided and internally guided decision-making. Second, using multi-level kernel density analysis, a whole-brain-based quantitative meta-analysis of neuroimaging studies was performed. Our meta-analysis revealed that the neural network used predominantly for internally guided decision-making differs from that for externally guided decision-making under uncertainty. This result suggests that studying only externally guided decision-making under uncertainty is insufficient to account for decision-making processes in the brain. Finally, based on the review and results of the meta-analysis, we discuss the differences and relations between decision-making of these two types in terms of their operational, neuronal, and theoretical characteristics.

Using appropriate stimuli to evoke emotions is especially important for researching emotion. Psychologists have provided several standardized affective stimulus databases-such as the International Affective Picture System (IAPS) and the Nencki Affective Picture System (NAPS) as visual stimulus databases, as well as the International Affective Digitized Sounds (IADS) and the Montreal Affective Voices as auditory stimulus databases for emotional experiments. However, considering the limitations of the existing auditory stimulus database studies, research using auditory stimuli is relatively limited compared with the studies using visual stimuli. First, the number of sample sounds is limited, making it difficult to equate across emotional conditions and semantic categories. Second, some artificially created materials (music or human voice) may fail to accurately drive the intended emotional processes. Our principal aim was to expand existing auditory affective sample database to sufficiently cover natural sounds. We asked 207 participants to rate 935 sounds (including the sounds from the IADS-2) using the Self-Assessment Manikin (SAM) and three basic-emotion rating scales. The results showed that emotions in sounds can be distinguished on the affective rating scales, and the stability of the evaluations of sounds revealed that we have successfully provided a larger corpus of natural, emotionally evocative auditory stimuli, covering a wide range of semantic categories. Our expanded, standardized sound sample database may promote a wide range of research in auditory systems and the possible interactions with other sensory modalities, encouraging direct reliable comparisons of outcomes from different researchers in the field of psychology.