Yet, we note that the purpose of our research is not to explicitly describe relationships between emotions and specific ERP components. Indeed, these relationships may be non-specific to valence and contingent on simultaneous appraisal processes (Hajcak et al.,2006; Grandjean and Schere, 2008). In our work, we instead draw a distinction between emotions and feelings, which we view as less specific though related to emotion (and sometimes interrelated components of emotion), that represent ongoing monitoring of internal processes (for similar views, see Pribram, 1970; Scherer, 2004). We argue that process-induced fluency feelings, as measured by event-related potentials, might be utilized as sources of
information in the non-preference related buying task described in this paper. Notwithstanding, we emphasize emotional effects through our simultaneous focus on trait math anxiety. In the consumer behavior literature, Raghunathan et al. (2006) have demonstrated that anxiety leads to a risk-reduction buying mentality. Brand et al. (2006) argue that optimal decision making under risk is characterized by “both cognitive strategies as well as biasing emotional signals” (p. 1273). Thus, despite our non-predictions related to emotions and specific ERP components, we would predict that High MA renders consumers more susceptible to incorporating feeling-related information into their choice making. In this
sense, we expect that High MA consumers will demonstrate more buy versus non-buy differences as measured by ERPs than Low MA consumers.