Search

In the classic gain/loss framing effect, describing a gamble as a potential gain or loss biases people to make risk-averse or risk-seeking decisions, respectively. The canonical explanation for this effect is that frames differentially modulate emotional processes, which in turn leads to irrational choice behavior. Here, we evaluate the source of framing biases by integrating functional magnetic resonance imaging data from 143 human participants performing a gain/loss framing task with meta-analytic data from >8000 neuroimaging studies. We found that activation during choices consistent with the framing effect were most correlated with activation associated with the resting or default brain, while activation during choices inconsistent with the framing effect was most correlated with the task-engaged brain. Our findings argue against the common interpretation of gain/loss framing as a competition between emotion and control. Instead, our study indicates that this effect results from differential cognitive engagement across decision frames. [ABSTRACT FROM AUTHOR]

Understanding how the brain computes value is a basic question in neuroscience. Although individual studies have driven this progress, meta-analyses provide an opportunity to test hypotheses that require large collections of data. We carry out a meta-analysis of a large set of functional magnetic resonance imaging studies of value computation to address several key questions. First, what is the full set of brain areas that reliably correlate with stimulus values when they need to be computed? Second, is this set of areas organized into dissociable functional networks? Third, is a distinct network of regions involved in the computation of stimulus values at decision and outcome? Finally, are different brain areas involved in the computation of stimulus values for different reward modalities? Our results demonstrate the centrality of ventromedial prefrontal cortex (VMPFC), ventral striatum and posterior cingulate cortex (PCC) in the computation of value across tasks, reward modalities and stages of the decision-making process. We also find evidence of distinct subnetworks of co-activation within VMPFC, one involving central VMPFC and dorsal PCC and another involving more anterior VMPFC, left angular gyrus and ventral PCC. Finally, we identify a posterior-to-anterior gradient of value representations corresponding to concrete-to-abstract rewards. [ABSTRACT FROM PUBLISHER]

Abstract: A core goal for marketers is effective segmentation: partitioning a brand''s or product''s consumer base into distinct and meaningful groups with differing needs. Traditional segmentation data include factors like geographic location, demographics, and shopping history. Yet, research into the cognitive and affective processes underlying consumption decisions shows that these variables can improve the matching of consumers with products beyond traditional demographic and benefit approaches. We propose, using managing a brand as an example, that neuroscience provides a novel way to establish mappings between cognitive processes and traditional marketing data. An improved understanding of the neural mechanisms of decision making will enhance the ability of marketers to effectively market their products. Just as neuroscience can model potential influences on the decision process—including pricing, choice strategy, context, experience, and memory—it can also provide new insights into individual differences in consumption behavior and brand preferences. We outline such a research agenda for incorporating neuroscience data into future attempts to match consumers to brands. [Copyright &y& Elsevier]

Activation in frontopolar cortex (FPC; BA 10) has been associated both with attending to mental states and with integrating multiple mental relations. However, few previous studies have manipulated both of these cognitive processes, precluding a clear functional distinction among regions within FPC. To address this issue, we developed an fMRI task that combined mentalizing and relational integration processes. Participants saw blocks of single words and performed one of three judgments: how pleasant or unpleasant they found each word (Self condition), how a specific friend would evaluate the pleasantness of the word (Other condition), or the difference between their own pleasantness judgment and that of their friend (Relational condition). We found that medial FPC was modulated by Other relative to Self judgments, consistent with a role in mentalizing. Lateral FPC was significantly activated during Relational compared to Self judgements, suggesting that this region is particularly involved in relational integration. The results point to a strong functional dissociation between medial and lateral FPC. In addition, the data demonstrate a role for lateral FPC in the social domain, provided that the task requires the integration of one’s preferences with those of others. [ABSTRACT FROM PUBLISHER]

Abstract: Analyzing distributed patterns of brain activation using multivariate pattern analysis (MVPA) has become a popular approach for using functional magnetic resonance imaging (fMRI) data to predict mental states. While the majority of studies currently build separate classifiers for each participant in the sample, in principle a single classifier can be derived from and tested on data from all participants. These two approaches, within- and cross-participant classification, rely on potentially different sources of variability and thus may provide distinct information about brain function. Here, we used both approaches to identify brain regions that contain information about passively received monetary rewards (i.e., images of currency that influenced participant payment) and social rewards (i.e., images of human faces). Our within-participant analyses implicated regions in the ventral visual processing stream—including fusiform gyrus and primary visual cortex—and ventromedial prefrontal cortex (VMPFC). Two key results indicate these regions may contain statistically discriminable patterns that contain different informational representations. First, cross-participant analyses implicated additional brain regions, including striatum and anterior insula. The cross-participant analyses also revealed systematic changes in predictive power across brain regions, with the pattern of change consistent with the functional properties of regions. Second, individual differences in classifier performance in VMPFC were related to individual differences in preferences between our two reward modalities. We interpret these results as reflecting a distinction between patterns showing participant-specific functional organization and those indicating aspects of brain organization that generalize across individuals. [Copyright &y& Elsevier]