Why do we think? The dynamics of spontaneous thought reveal its functions.

Spontaneous thought-mind wandering, daydreaming, and creative ideation-makes up most of everyday cognition. Is this idle thought, or does it serve an adaptive function? We test two hypotheses about the functions of spontaneous thought: First, spontaneous thought improves memory efficiency. Under this hypothesis, spontaneous thought should prioritize detailed, vivid episodic simulations. Second, spontaneous thought helps us achieve our goals. Under this hypothesis, spontaneous thought should prioritize content relevant to ongoing goal pursuits, or current concerns. We use natural language processing and machine learning to quantify the dynamics of thought in a large sample (N = 3,359) of think aloud data. Results suggest that spontaneous thought both supports memory optimization and keeps us focused on current concerns.

Individual differences in emotion prediction and implications for social success.

The social world requires people to predict others' thoughts, feelings, and actions. People who successfully predict others' emotions experience significant social advantages. What makes a person good at predicting emotions? To predict others' future emotional states, a person must know how one emotion transitions to the next. People learn how emotions transition from at least two sources: (a) internal information, or one's own emotion experiences, and (b) external information, such as the social cues detected in a person's face. Across five studies collected between 2018 and 2020, we find evidence that both sources of information are related to accurate emotion prediction: individuals with atypical personal emotion transitions, difficulty understanding their own emotional experiences, and impaired emotion perception displayed impaired emotion prediction. This ability to predict others' emotions has real-world social implications. Individuals who make accurate emotion predictions have better relationships with their friends and communities and experience less loneliness. In contrast, disruptions in both internal and external information sources explain prediction inaccuracy in individuals with social difficulties, specifically with social communication difficulties common in autism spectrum disorder. These findings provide evidence that successful emotion prediction, which relies on the perception of accurate internal and external data about how emotions transition, may be key to social success. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Neural representations of situations and mental states are composed of sums of representations of the actions they afford.

Human behavior depends on both internal and external factors. Internally, people's mental states motivate and govern their behavior. Externally, one's situation constrains which actions are appropriate or possible. To predict others' behavior, one must understand the influences of mental states and situations on actions. On this basis, we hypothesize that people represent situations and states in terms of associated actions. To test this, we use functional neuroimaging to estimate neural activity patterns associated with situations, mental states, and actions. We compute sums of the action patterns, weighted by how often each action occurs in each situation and state. We find that these summed action patterns reconstructed the corresponding situation and state patterns. These results suggest that neural representations of situations and mental states are composed of sums of their action affordances. Summed action representations thus offer a biological mechanism by which people can predict actions given internal and external factors.

Creativity at rest: Exploring functional network connectivity of creative experts.

The neuroscience of creativity seeks to disentangle the complex brain processes that underpin the generation of novel ideas. Neuroimaging studies of functional connectivity, particularly functional magnetic resonance imaging (fMRI), have revealed individual differences in brain network organization associated with creative ability; however, much of the extant research is limited to laboratory-based divergent thinking measures. To overcome these limitations, we compare functional brain connectivity in a cohort of creative experts (n = 27) and controls (n = 26) and examine links with creative behavior. First, we replicate prior findings showing reduced connectivity in visual cortex related to higher creative performance. Second, we examine whether this result is driven by integrated or segregated connectivity. Third, we examine associations between functional connectivity and vivid distal simulation separately in creative experts and controls. In accordance with past work, our results show reduced connectivity to the primary visual cortex in creative experts at rest. Additionally, we observe a negative association between distal simulation vividness and connectivity to the lateral visual cortex in creative experts. Taken together, these results highlight connectivity profiles of highly creative people and suggest that creative thinking may be related to, though not fully redundant with, the ability to vividly imagine the future.

Egocentric Projection is a Rational Strategy for Accurate Emotion Prediction.

People need to accurately understand and predict others' emotions in order to build and maintain meaningful social connections. However, when they encounter new social partners, people often do not have enough information about them to make accurate inferences. Rather, they often resort to an egocentric heuristic, and make predictions about a target by using their own self-knowledge as a proxy. Is this egocentric heuristic a form of cognitive bias, or is it a rational strategy for real-world social prediction? If egocentrism provides a rational and effective solution to the challenging task of social prediction in naturalistic contexts, we should expect that a) egocentric predictions tend to be more accurate, and b) people rely on self-knowledge to a greater extent when it's more likely to be a good proxy. Using an emotion prediction task and personality measures, we assessed similarity and predictive accuracy between first-year college students and their new acquaintance roommate. Results demonstrated that, when people need to predict an unfamiliar target's emotions, self-knowledge can often effectively approximate knowledge about others, and thus support accurate predictions. Moreover, participants that were typical of the sample, whose self-knowledge can better approximate information about the target, relied more on self-knowledge in their predictions, and thus achieved higher accuracy. These findings suggest that people rationally tune their use of egocentrism based on whether it is likely to pay off. Overall, these findings demonstrate a rational side to a cognitive phenomenon usually framed as a cognitive pitfall, namely egocentric projection, when its natural decision context is taken into consideration.

Simulation does not just inform choice, it changes choice.

Simulation - imagining future events - plays a role in decision-making. In Conviction Narrative Theory, people's emotional responses to their simulations inform their choices. Yet imagining one possible future also increases its plausibility and accessibility relative to other futures. We propose that the act of simulation, in addition to affective evaluation, drives people to choose in accordance with their simulations.

Transition dynamics shape mental state concepts.

People have a unique ability to represent other people's internal thoughts and feelings-their mental states. Mental state knowledge has a rich conceptual structure, organized along key dimensions, such as valence. People use this conceptual structure to guide social interactions. How do people acquire their understanding of this structure? Here we investigate an underexplored contributor to this process: observation of mental state dynamics. Mental states-including both emotions and cognitive states-are not static. Rather, the transitions from one state to another are systematic and predictable. Drawing on prior cognitive science, we hypothesize that these transition dynamics may shape the conceptual structure that people learn to apply to mental states. Across nine behavioral experiments (N = 1,439), we tested whether the transition probabilities between mental states causally shape people's conceptual judgments of those states. In each study, we found that observing frequent transitions between mental states caused people to judge them to be conceptually similar. Computational modeling indicated that people translated mental state dynamics into concepts by embedding the states as points within a geometric space. The closer two states are within this space, the greater the likelihood of transitions between them. In three neural network experiments, we trained artificial neural networks to predict real human mental state dynamics. The networks spontaneously learned the same conceptual dimensions that people use to understand mental states. Together these results indicate that mental state dynamics-and the goal of predicting them-shape the structure of mental state concepts. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Caregiver speech predicts the emergence of children's emotion vocabulary.

Learning about emotions is an important part of children's social and communicative development. How does children's emotion-related vocabulary emerge over development? How may emotion-related information in caregiver input support learning of emotion labels and other emotion-related words? This investigation examined language production and input among English-speaking toddlers (16-30 months) using two datasets: Wordbank (N = 5520; 36% female, 38% male, and 26% unknown gender; 1% Asian, 4% Black, 2% Hispanic, 40% White, 2% others, and 50% unknown ethnicity; collected in North America; dates of data collection unknown) and Child Language Data Exchange System (N = 587; 46% female, 44% male, 9% unknown gender, all unknown ethnicity; collected in North America and the UK; data collection dates, were available between 1962 and 2009). First, we show that toddlers develop the vocabulary to express increasingly wide ranges of emotional information during the first 2 years of life. Computational measures of word valence showed that emotion labels are embedded in a rich network of words with related valence. Second, we show that caregivers leverage these semantic connections in ways that may scaffold children's learning of emotion and mental state labels. This research suggests that young children use the dynamics of language input to construct emotion word meanings, and provides new techniques for defining the quality of infant-directed speech.

The promises and pitfalls of functional magnetic resonance imaging hyperscanning for social interaction research.

Social neuroscience combines tools and perspectives from social psychology and neuroscience to understand how people interact with their social world. Here we discuss a relatively new method-hyperscanning-to study real-time, interactive social interactions using functional magnetic resonance imaging (fMRI). We highlight three contributions that fMRI hyperscanning makes to the study of the social mind: (1) Naturalism: it shifts the focus from tightly-controlled stimuli to more naturalistic social interactions; (2) Multi-person Dynamics: it shifts the focus from individuals as the unit of analysis to dyads and groups; and (3) Neural Resolution: fMRI hyperscanning captures high-resolution neural patterns and dynamics across the whole brain, unlike other neuroimaging hyperscanning methods (e.g., electroencephalogram, functional near-infrared spectroscopy). Finally, we describe the practical considerations and challenges that fMRI hyperscanning researchers must navigate. We hope researchers will harness this powerful new paradigm to address pressing questions in today's society.

The 3d Mind Model characterizes how people understand mental states across modern and historical cultures.

Humans rely on social interaction to achieve many important goals. These interactions rely in turn on people's capacity to understand others' mental states: their thoughts and feelings. Do different cultures understand minds in different ways, or do widely shared principles describe how different cultures understand mental states? Extensive data suggest that the mind organizes mental state concepts using the 3d Mind Model, composed of the psychological dimensions: rationality (vs. emotionality), social impact (states which affect others more vs. less), and valence (positive vs. negative states). However, this evidence comes primarily from English-speaking individuals in the United States. Here we investigated mental state representation in 57 contemporary countries, using 163 million English language tweets; in 17 languages, using billions of words of text from internet webpages; and across more than 2000 years of history, using curated texts from four historical societies. We quantified mental state meaning by analyzing the text produced by each culture using word embeddings. We then tested whether the 3d Mind Model could explain which mental states were similar in meaning within each culture. We found that the 3d Mind Model significantly explained mental state meaning in every country, language, and historical society that we examined. These results suggest that rationality, social impact, and valence form a generalizable conceptual backbone for mental state representation.

Accurate emotion prediction in dyads and groups and its potential social benefits.

Emotion dynamics vary considerably from individual to individual and from group to group. Successful social interactions require people to track this moving target in order to anticipate the thoughts, feelings, and actions of others. In two studies, we test whether people track others' emotional idiosyncrasies to make accurate, target-specific emotion predictions. In both studies, participants predicted the emotion transitions of a specific target-either a close friend (Study 1) or a first-year college roommate (Study 2)-as well as an average group member. Results demonstrate that people can make highly accurate predictions both for specific individuals and specific groups. Accurate predictions rely on target-specific knowledge; new community members were able to make accurate predictions at zero-acquaintance, but accuracy increased over time as individuals accrued specialized knowledge. Results also suggest that accurate emotion prediction is associated with social success in both individual and communal relationships and that such a relation might emerge over time. Overall, our studies suggest that people accurately make individualized predictions of others' emotion transitions and that doing so fulfills a meaningful function in the social world. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Six dimensions describe action understanding: The ACT-FASTaxonomy.

Humans engage in a wide variety of different actions and activities. These range from simple motor actions like reaching for an object, to complex activities like governing a nation. Navigating everyday life requires people to make sense of this diversity of actions. We suggest that the mind simplifies this complex domain by attending primarily to the most essential features of actions. Using a parsimonious set of action dimensions, the mind can organize action knowledge in a low-dimensional representational space. In seven studies, we derive and validate such an action taxonomy. Study 1 uses large-scale text analyses to generate and test potential action dimensions. Study 2 validates interpretable labels for these dimensions. Studies 3-5 demonstrate that these dimensions can explain human judgments about actions. We perform model selection on data from these studies to arrive at the optimal set of six psychological dimensions, together forming the Abstraction, Creation, Tradition, Food, Animacy, Spiritualism Taxonomy (ACT-FAST). Study 6 demonstrates that ACT-FAST can predict socially relevant qualities of actions, including how, when, where, why, and by whom they are performed. Finally, Study 7 shows that ACT-FAST can explain action-related patterns of brain activity using naturalistic functional MRI (MRI). Together, these studies reveal the dimensional structure the mind applies to organize action concepts. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Mask exposure during COVID-19 changes emotional face processing.

Faces are one of the key ways that we obtain social information about others. They allow people to identify individuals, understand conversational cues, and make judgements about others' mental states. When the COVID-19 pandemic hit the United States, widespread mask-wearing practices were implemented, causing a shift in the way Americans typically interact. This introduction of masks into social exchanges posed a potential challenge-how would people make these important inferences about others when a large source of information was no longer available? We conducted two studies that investigated the impact of mask exposure on emotion perception. In particular, we measured how participants used facial landmarks (visual cues) and the expressed valence and arousal (affective cues), to make similarity judgements about pairs of emotion faces. Study 1 found that in August 2020, participants with higher levels of mask exposure used cues from the eyes to a greater extent when judging emotion similarity than participants with less mask exposure. Study 2 measured participants' emotion perception in both April and September 2020 -before and after widespread mask adoption-in the same group of participants to examine changes in the use of facial cues over time. Results revealed an overall increase in the use of visual cues from April to September. Further, as mask exposure increased, people with the most social interaction showed the largest increase in the use of visual facial cues. These results provide evidence that a shift has occurred in how people process faces such that the more people are interacting with others that are wearing masks, the more they have learned to focus on visual cues from the eye area of the face.

Clarifying the link between music and social bonding by measuring prosociality in context.

To corroborate the music and social bonding hypothesis, we propose that future investigations isolate specific components of social bonding and consider the influence of context. We deconstruct and operationalize social bonding through the lens of social psychology and provide examples of specific measures that can be used to assess how the link between music and sociality varies by context.

The representational structure of mental states generalizes across target people and stimulus modalities.

Each individual experiences mental states in their own idiosyncratic way, yet perceivers can accurately understand a huge variety of states across unique individuals. How do they accomplish this feat? Do people think about their own anger in the same ways as another person's anger? Is reading about someone's anxiety the same as seeing it? Here, we test the hypothesis that a common conceptual core unites mental state representations across contexts. Across three studies, participants judged the mental states of multiple targets, including a generic other, the self, a socially close other, and a socially distant other. Participants viewed mental state stimuli in multiple modalities, including written scenarios and images. Using representational similarity analysis, we found that brain regions associated with social cognition expressed stable neural representations of mental states across both targets and modalities. Together, these results suggest that people use stable models of mental states across different people and contexts.

The people around you are inside your head: Social context shapes spontaneous thought.

Humans are highly social. We spend most of our time interacting with the social world, and we spend most of our thoughts thinking about the social world. Are we social beings by default, or is our sociality a response to the social world? On the one hand, fundamental social needs may drive social behavior. According to this account, social thoughts fulfill social needs when the environment is insufficiently social. On the other hand, spontaneous thoughts may process incoming information. According to this account, social thoughts reflect the social information in the environment. To arbitrate between these possibilities, we assessed the content of spontaneous thought during mind wandering in three social contexts: solitude (Study 1), social presence (Study 2), and social interaction (Study 3). Additionally, in Study 1, we used functional neuroimaging to measure neural activity while participants considered social and nonsocial targets. Results consistently showed that spontaneous thought reflects the sociality of the world around us: Solitude decreased spontaneous social thought and decreased neural activity in the mentalizing network when thinking about a close friend. Social presence did not change spontaneous social thought. Social interaction increased spontaneous social thought. Finally, individual differences analyses (Study 4) showed that people in more social environments have more social thoughts. Together, the results show a pattern of increasing social thought in increasingly social environments. The predominance of social content in spontaneous thought can thus be explained by the predominance of social content in the world around us, rather than our innate, fundamental social needs. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

People accurately predict the transition probabilities between actions.

Social life is a complex dance. To coordinate gracefully with one's partners, one must predict their actions. Here, we investigated how people predict others' actions. We hypothesized that people can accurately predict others' future actions based on knowledge of their current actions, coupled with knowledge of action transitions. To test whether people have accurate knowledge of the transition probabilities between actions, we compared actual rates of action transitions-calculated from four large naturalistic datasets-to participants' ratings of the transition probabilities between corresponding sets of actions. In five preregistered studies, participants demonstrated accurate mental models of action transitions. Furthermore, we found that people drew upon conceptual knowledge of actions-described by the six-dimensional ACT-FASTaxonomy-to guide their accurate predictions. Together, these results indicate that people can accurately anticipate other people's moves in the dance of social life and that the structure of action knowledge may be tailored to making these predictions.

Perceiving actions before they happen: psychological dimensions scaffold neural action prediction.

The social world buzzes with action. People constantly walk, talk, eat, work, play, snooze and so on. To interact with others successfully, we need to both understand their current actions and predict their future actions. Here we used functional neuroimaging to test the hypothesis that people do both at the same time: when the brain perceives an action, it simultaneously encodes likely future actions. Specifically, we hypothesized that the brain represents perceived actions using a map that encodes which actions will occur next: the six-dimensional Abstraction, Creation, Tradition, Food(-relevance), Animacy and Spiritualism Taxonomy (ACT-FAST) action space. Within this space, the closer two actions are, the more likely they are to precede or follow each other. To test this hypothesis, participants watched a video featuring naturalistic sequences of actions while undergoing functional magnetic resonance imaging (fMRI) scanning. We first use a decoding model to demonstrate that the brain uses ACT-FAST to represent current actions. We then successfully predicted as-yet unseen actions, up to three actions into the future, based on their proximity to the current action's coordinates in ACT-FAST space. This finding suggests that the brain represents actions using a six-dimensional action space that gives people an automatic glimpse of future actions.

Successful simulation requires bridging levels of abstraction.

Although many simulations draw upon only one level of abstraction, the process for generating rich simulations requires a dynamic interplay between abstract and concrete knowledge. A complete model of simulation must account for a mind and brain that can bridge the perceptual with the conceptual, the episodic with the semantic, and the concrete with the abstract.

People represent mental states in terms of rationality, social impact, and valence: Validating the 3d Mind Model.

Humans can experience a wide variety of different thoughts and feelings in the course of everyday life. To successfully navigate the social world, people need to perceive, understand, and predict others' mental states. Previous research suggests that people use three dimensions to represent mental states: rationality, social impact, and valence. This 3d Mind Model allows people to efficiently "see" the state of another person's mind by considering whether that state is rational or emotional, more or less socially impactful, and positive or negative. In the current investigation, we validate this model using neural, behavioral, and linguistic evidence. First, we examine the robustness of the 3d Mind Model by conducting a mega-analysis of four fMRI studies in which participants considered others' mental states. We find evidence that rationality, social impact, and valence each contribute to explaining the neural representation of mental states. Second, we test whether the 3d Mind Model offers the optimal combination of dimensions for describing neural representations of mental state. Results reveal that the 3d Mind Model achieve the best performance among a large set of candidate dimensions. Indeed, it offers a highly explanatory account of mental state representation, explaining over 80% of reliable neural variance. Finally, we demonstrate that all three dimensions of the model likewise capture convergent behavioral and linguistic measures of mental state representation. Together, these findings provide strong support for the 3d Mind Model, indicating that is it is a robust and generalizable account of how people think about mental states.