Mood As Cumulative Expectation Mismatch: A Test of Theory Based on Data from Non-verbal Cognitive Bias Tests - Raoult, Camille M. C.; Moser, Julia; Gygax, Lorenz (Frontiers in Psychology, 2017)
Affective states are known to influence behavior and cognitive processes. To assess mood (moderately long-term affective states), the cognitive judgement bias test was developed and has been widely used in various animal species. However, little is known about how mood changes, how mood can be experimentally manipulated, and how mood then feeds back into cognitive judgement. A recent theory argues that mood reflects the cumulative impact of differences between obtained outcomes and expectations. Here expectations refer to an established context. Situations in which an established context fails to match an outcome are then perceived as mismatches of expectation and outcome. We take advantage of the large number of studies published on nonverbal cognitive bias tests in recent years (95 studies with a total of 162 independent tests) to test whether cumulative mismatch could indeed have led to the observed mood changes. Based on a criteria list, we assessed whether mismatch had occurred with the experimental procedure used to induce mood (mood induction mismatch), or in the context of the nonverbal cognitive bias procedure (testing mismatch). For the mood induction mismatch, we scored the mismatch between the subjects’ potential expectations and the manipulations conducted for inducing mood whereas, for the testing mismatch, we scored mismatches that may have occurred during the actual testing. We then investigated whether these two types of mismatch can predict the actual outcome of the cognitive bias study. The present evaluation shows that mood induction mismatch cannot well predict the success of a cognitive bias test. On the other hand, testing mismatch can modulate or even inverse the expected outcome. We think, cognitive bias studies should more specifically aim at creating expectation mismatch while inducing mood states to test the cumulative mismatch theory more properly. Furthermore, testing mismatch should be avoided as much as possible because it can reverse the affective state of animals as measured in a cognitive judgement bias paradigm.