Coming to Mind
Identifying important individual- and country-level predictors of conspiracy theorizing: A machine learning analysis
Karen Douglas et al.
European Journal of Social Psychology, forthcoming
Abstract:
Psychological research on the predictors of conspiracy theorizing -- explaining important social and political events or circumstances as secret plots by malevolent groups -- has flourished in recent years. However, research has typically examined only a small number of predictors in one, or a small number of, national contexts. Such approaches make it difficult to examine the relative importance of predictors, and risk overlooking some potentially relevant variables altogether. To overcome this limitation, the present study used machine learning to rank-order the importance of 115 individual- and country-level variables in predicting conspiracy theorizing. Data were collected from 56,072 respondents across 28 countries during the early weeks of the COVID-19 pandemic. Echoing previous findings, important predictors at the individual level included societal discontent, paranoia, and personal struggle. Contrary to prior research, important country-level predictors included indicators of political stability and effective government COVID response, which suggests that conspiracy theorizing may thrive in relatively well-functioning democracies.
Emotion regulation efficacy beliefs: The outsized impact of base rates
Kit Double et al.
Emotion, forthcoming
Abstract:
To regulate others' emotions effectively we must learn about the efficacy of our regulation attempts. Deciding whether we made someone else feel better involves a causal judgment about the effect of our intervention on their emotional state. The current study examined whether, like other causal judgments, beliefs about emotion regulation efficacy are disproportionately affected by base rates. In two experiments, we showed that participants' perceived efficacy at helping a target regulate their emotions was more influenced by the target's average emotion levels than the relative effect of regulating versus not regulating the target's emotion. This led participants to conclude that they were helpful both when they were not (Experiment 1) and even when they made the target feel worse (Experiment 2). These findings suggest that our beliefs about the effectiveness of other-directed emotion regulation are notably biased by the average level of emotion expressed by the regulation target.
Instructed motivational states bias reinforcement learning and memory formation
Alyssa Sinclair, Yuxi Wang & Alison Adcock
Proceedings of the National Academy of Sciences, 1 August 2023
Abstract:
Motivation influences goals, decisions, and memory formation. Imperative motivation links urgent goals to actions, narrowing the focus of attention and memory. Conversely, interrogative motivation integrates goals over time and space, supporting rich memory encoding for flexible future use. We manipulated motivational states via cover stories for a reinforcement learning task: The imperative group imagined executing a museum heist, whereas the interrogative group imagined planning a future heist. Participants repeatedly chose among four doors, representing different museum rooms, to sample trial-unique paintings with variable rewards (later converted to bonus payments). The next day, participants performed a surprise memory test. Crucially, only the cover stories differed between the imperative and interrogative groups; the reinforcement learning task was identical, and all participants had the same expectations about how and when bonus payments would be awarded. In an initial sample and a preregistered replication, we demonstrated that imperative motivation increased exploitation during reinforcement learning. Conversely, interrogative motivation increased directed (but not random) exploration, despite the cost to participants' earnings. At test, the interrogative group was more accurate at recognizing paintings and recalling associated values. In the interrogative group, higher value paintings were more likely to be remembered; imperative motivation disrupted this effect of reward modulating memory. Overall, we demonstrate that a prelearning motivational manipulation can bias learning and memory, bearing implications for education, behavior change, clinical interventions, and communication.
Excluded and Ashamed: Shame Proneness Interacts with Social Exclusion and Testosterone Reactivity to Predict Behavioral Aggression
Lindsay Bochon, Brian Bird & Neil Watson
Psychoneuroendocrinology, forthcoming
Abstract:
Exclusion from social relationships is a painful experience that may threaten an individual's status and dominance. The steroid hormone testosterone, which fluctuates rapidly in response to such threats, may be implicated in subsequent behavioral action (e.g., aggressive or prosocial responses) that aims to protect or enhance one's status after exclusion. Past research, however, indicates that the link between acute changes in testosterone and behavior depend on context-relevant individual dispositions. In the context of social exclusion, an individual's level of shame proneness -- characterized by a tendency to experience shame and to react submissively -- is theoretically relevant to the testosterone-induced aggression relationship but has yet to be examined empirically. Here, men (n =167) were randomly assigned to be socially included or excluded in the virtual ball-tossing game, Cyberball, after which aggressive behavior was examined using the Point Subtraction Aggression Paradigm (PSAP). Testosterone reactivity was measured via salivary hormone samples collected pre- and post-game. Moderated multiple regression analyses were run to examine the extent to which testosterone reactivity and shame proneness moderated the effect of Cyberball condition on aggression. Results revealed a significant two-way interaction between Cyberball condition and testosterone reactivity, as well as a three-way interaction including shame proneness. For individuals low in shame proneness, exclusion was associated with higher post-cyberball aggression among those who experienced a rise in testosterone but was associated with lower post-cyberball aggression among those who experienced a decrease in testosterone. For individuals high in shame proneness, however, exclusion did not meaningfully affect aggressive responses, regardless of whether they experienced an increase or decrease in testosterone. These findings extend our understanding of the moderating roles of context and disposition on the neuroendocrinology of aggression in social interaction.
Behavioral signatures of face perception emerge in deep neural networks optimized for face recognition
Katharina Dobs et al.
Proceedings of the National Academy of Sciences, 8 August 2023
Abstract:
Human face recognition is highly accurate and exhibits a number of distinctive and well-documented behavioral "signatures" such as the use of a characteristic representational space, the disproportionate performance cost when stimuli are presented upside down, and the drop in accuracy for faces from races the participant is less familiar with. These and other phenomena have long been taken as evidence that face recognition is "special". But why does human face perception exhibit these properties in the first place? Here, we use deep convolutional neural networks (CNNs) to test the hypothesis that all of these signatures of human face perception result from optimization for the task of face recognition. Indeed, as predicted by this hypothesis, these phenomena are all found in CNNs trained on face recognition, but not in CNNs trained on object recognition, even when additionally trained to detect faces while matching the amount of face experience. To test whether these signatures are in principle specific to faces, we optimized a CNN on car discrimination and tested it on upright and inverted car images. As we found for face perception, the car-trained network showed a drop in performance for inverted vs. upright cars. Similarly, CNNs trained on inverted faces produced an inverted face inversion effect. These findings show that the behavioral signatures of human face perception reflect and are well explained as the result of optimization for the task of face recognition, and that the nature of the computations underlying this task may not be so special after all.