Experience-Based Decisions and Brain Activity: Three New Gaps and Partial Answers

Experience-based decisions can be defined as decisions emanating from direct or vicarious reinforcements that were received in the past. Typically, in experience-based decision tasks an agent repeatedly makes choices and receives outcomes from the available alternatives, so that choices are based on past experiences, with no explicit description of the payoff distributions from which the outcomes are drawn. The study of experience-based decisions has long roots in the works of mathematical psychologists during the 1950s and 1960s of the last century (e.g., Estes and Burke, 1953; Bush and Mosteller, 1955; Katz, 1964). This type of task has been viewed as a natural continuation of the behaviorist tradition involving animals as subjects, and multiple trials in which feedback is obtained on each trial. During the 1970s and 1980s seminal studies focusing on choices among descriptive gambles began to dominate the field of Judgment and Decision Making, paving the wave for the successful and influential works of Tversky and Kahneman (e.g., Kahneman and Tversky, 1979). Indeed, a review of the decision making literature from 1970 to 1998 conducted by Weber et al. (2004) shows prominent use of description-based tasks over experience-based tasks. Yet the study of experience-based decisions has continued to evolve. Some of the workers in this subfield were neuropsychologists who used experience-based tasks as a natural way to evaluate individual differences owing to these tasks having many choice trials (e.g., Bechara et al., 1994). Others were interested in the complex relations between learning and decision making (Erev and Roth, 1998). An interesting finding that has finally defined the importance of contrasting the two types of tasks – experience-based decisions and description-based decisions, was obtained by Ido Erev and his colleagues. Kahneman and Tversky (1979) showed that individuals overweight small probability events in their decisions from description. For instance, in selecting between an alternative producing $3 for sure or a gamble producing 10% chance to receive $32 (and otherwise zero), most people pick the riskier alternative, behaving as if they give greater weight to the relatively rare event (see Hau et al., 2009). Erev and colleagues have demonstrated a reverse phenomenon in decisions from experience (Barron and Erev, 2003; Hertwig et al., 2004; Yechiam et al., 2005). People tend to experientially select alternatives as if what happens most of the time has more weight than the rare event. Thus, people overweight small probability events in decisions from description while underweighting them in decisions from experience. This has been referred to as the description–experience (D–E) gap (Hertwig et al., 2004). The studies exploring the D–E gap were followed by further investigations examining the divergent and convergent processes in these task types (e.g., Rakow et al., 2008; Barron and Yechiam, 2009; Wu et al., 2011). In parallel to the recent advancements in experience-based decisions within the field of Judgment and Decision Making, there have been numerous studies of this type of decisions in Neuroscience. For example, the feedback-based error-related negativity (fERN; see below; e.g., Gehring and Willoughby, 2002) and the role of non-declarative knowledge in selecting advantageously (Bechara et al., 1997) were found in experience-based decisions. Several studies have explicitly showed that that experience-based tasks result in higher correlation between studied brain variables and over behavior. For example, in Aharon et al.’s (2001) fMRI study, participant evaluated the attractiveness of face images either descriptively or by making choices and receiving feedback. Brain activation levels in the reward circuitry (particularly, the nucleus accumbens) matched the evaluation patterns only in the experiential condition. Similarly, severe damage to the orbitofrontal cortex was found to lead to decision impairments in experience-based tasks, but not in description-based tasks (Leland and Grafman, 2005). Still, many of the investigations of these neuroscientific aspects have borrowed their theoretical underpinning from the study of decisions from description, and have not been guided by relevant theories of experience-based decisions. At the same time, many of the decision making studies of experience-based tasks have taken place without awareness of the relevant brain studies using this paradigm. In an attempt to highlight the necessity of integrating the two bodies of research (JDM and neuroscience studies), we present three dissociations (or “gaps”) between brain activation patterns and behavioral choices in these tasks. The majority of this paper is devoted to describing the three gaps in order to encourage further research. Additionally, we also suggest some directions for exploring and explaining these inconsistencies.