Dataset Information

Brain activation during social cognition predicts everyday perspective-taking: A combined fMRI and ecological momentary assessment study of the social brain.

ABSTRACT: Identifying distinct neural networks underlying social affect (empathy, compassion) and social cognition (Theory of Mind) has advanced our understanding of social interactions. However, little is known about the relation of activation in these networks to psychological experience in daily life. This study (N = 122) examined the ecological validity of neural activation patterns induced by a laboratory paradigm of social affect and cognition with respect to social interactions in everyday life. We used the EmpaToM task, a naturalistic video-based paradigm for the assessment of empathy, compassion, and Theory of Mind, and combined it with a subsequent 14-day ecological momentary assessment protocol on social interactions. Everyday social affect was predicted by social affect experienced during the EmpaToM task, but not by related neural activation in regions of interest from the social affect network. In contrast, everyday social cognition was predicted by neural activation differences in the medial prefrontal cortex - a region of interest from the social cognition network - but not by social cognition performance in the EmpaToM task. The relationship between medial prefrontal cortex activation and everyday social cognition was stronger for spontaneous rather than deliberate perspective taking during the EmpaToM task, pointing to a distinction between propensity and capacity in social cognition. Finally, this neural indicator of Theory of Mind explained variance in everyday social cognition to a similar extent as an established self-report scale. Taken together, this study provides evidence for the ecological validity of lab-based social affect and cognition paradigms when considering relevant moderating factors.

SUBMITTER: Hildebrandt MK

PROVIDER: S-EPMC7611322 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Objective: Parental influence during children's "everyday" pain events is under-explored, compared to clinical or experimental pains. We trialed two digital reporting methods for parents to record the real-world context surrounding their child's everyday pain events within the family home. Methods: Parents (N = 21) completed a structured e-diary for 14 days, reporting on one pain event experienced by their child (aged 2.5-6 years) each day, and describing child pain responses, parental supervision, parental estimates of pain severity and intensity, and parental catastrophizing, distress, and behavioral responses. During the same 2-week period, a subsample of parent-child pairs (N = 9) completed digital ecological momentary assessments (EMA), immediately after any chosen pain event. Children reported their current pain while parents estimated the child's pain and indicated their own distress. Results: "Everyday" pain events frequently featured minor injuries to the child's head, hands or knees, and child responses included crying and non-verbal comments (e.g., "Ouch!"). Pain events occurred less frequently when parents had been supervising their child, and supervising parents reported lower levels of worry and anxiety than non-supervising parents. Child sex was significantly associated with parental estimates of pain intensity, with parents of girls giving higher estimates than parents of boys. Child age was significantly associated with both the number of pain events and with parental estimates of pain intensity and child distress: the youngest children (2-3 years) experienced the fewest pain events but received higher pain and distress estimates from parents than older children. Hierarchal Linear Modeling revealed that parental estimates of pain severity were significant positive predictors of parental distress and catastrophizing in response to a specific pain event. Furthermore, higher levels of parental catastrophic thinking in response to a specific pain event resulted in increased distress, solicitousness, and coping-promoting behaviors in parents. The EMA data revealed that children reported significantly higher pain intensity than their parents. Conclusion: The electronic pain diary provided a key insight into the nature of "everyday" pain experiences around the family home. Digital daily reporting of how the family copes with "everyday" events represents a viable means to explore a child's everyday pains without disrupting their home environment.

Project description:BackgroundThe current methods of evaluating cognitive functioning typically rely on a single time point to assess and characterize an individual's performance. However, cognitive functioning fluctuates within individuals over time in relation to environmental, psychological, and physiological contexts. This limits the generalizability and diagnostic utility of single time point assessments, particularly among individuals who may exhibit large variations in cognition depending on physiological or psychological context (eg, those with type 1 diabetes [T1D], who may have fluctuating glucose concentrations throughout the day).ObjectiveWe aimed to report the reliability and validity of cognitive ecological momentary assessment (EMA) as a method for understanding between-person differences and capturing within-person variation in cognition over time in a community sample and sample of adults with T1D.MethodsCognitive performance was measured 3 times a day for 15 days in the sample of adults with T1D (n=198, recruited through endocrinology clinics) and for 10 days in the community sample (n=128, recruited from TestMyBrain, a web-based citizen science platform) using ultrabrief cognitive tests developed for cognitive EMA. Our cognitive EMA platform allowed for remote, automated assessment in participants' natural environments, enabling the measurement of within-person cognitive variation without the burden of repeated laboratory or clinic visits. This allowed us to evaluate reliability and validity in samples that differed in their expected degree of cognitive variability as well as the method of recruitment.ResultsThe results demonstrate excellent between-person reliability (ranging from 0.95 to 0.99) and construct validity of cognitive EMA in both the sample of adults with T1D and community sample. Within-person reliability in both samples (ranging from 0.20 to 0.80) was comparable with that observed in previous studies in healthy older adults. As expected, the full-length baseline and EMA versions of TestMyBrain tests correlated highly with one another and loaded together on the expected cognitive domains when using exploratory factor analysis. Interruptions had higher negative impacts on accuracy-based outcomes (β=-.34 to -.26; all P values <.001) than on reaction time-based outcomes (β=-.07 to -.02; P<.001 to P=.40).ConclusionsWe demonstrated that ultrabrief mobile assessments are both reliable and valid across 2 very different clinic versus community samples, despite the conditions in which cognitive EMAs are administered, which are often associated with more noise and variability. The psychometric characteristics described here should be leveraged appropriately depending on the goals of the cognitive assessment (eg, diagnostic vs everyday functioning) and the population being studied.

Project description:BACKGROUND: When our PC goes on strike again we tend to curse it as if it were a human being. Why and under which circumstances do we attribute human-like properties to machines? Although humans increasingly interact directly with machines it remains unclear whether humans implicitly attribute intentions to them and, if so, whether such interactions resemble human-human interactions on a neural level. In social cognitive neuroscience the ability to attribute intentions and desires to others is being referred to as having a Theory of Mind (ToM). With the present study we investigated whether an increase of human-likeness of interaction partners modulates the participants' ToM associated cortical activity. METHODOLOGY/PRINCIPAL FINDINGS: By means of functional magnetic resonance imaging (subjects n = 20) we investigated cortical activity modulation during highly interactive human-robot game. Increasing degrees of human-likeness for the game partner were introduced by means of a computer partner, a functional robot, an anthropomorphic robot and a human partner. The classical iterated prisoner's dilemma game was applied as experimental task which allowed for an implicit detection of ToM associated cortical activity. During the experiment participants always played against a random sequence unknowingly to them. Irrespective of the surmised interaction partners' responses participants indicated having experienced more fun and competition in the interaction with increasing human-like features of their partners. Parametric modulation of the functional imaging data revealed a highly significant linear increase of cortical activity in the medial frontal cortex as well as in the right temporo-parietal junction in correspondence with the increase of human-likeness of the interaction partner (computer<functional robot<anthropomorphic robot<human). CONCLUSIONS/SIGNIFICANCE: Both regions correlating with the degree of human-likeness, the medial frontal cortex and the right temporo-parietal junction, have been associated with Theory-of-Mind. The results demonstrate that the tendency to build a model of another's mind linearly increases with its perceived human-likeness. Moreover, the present data provides first evidence of a contribution of higher human cognitive functions such as ToM in direct interactions with artificial robots. Our results shed light on the long-lasting psychological and philosophical debate regarding human-machine interaction and the question of what makes humans being perceived as human.

Dataset Information

Brain activation during social cognition predicts everyday perspective-taking: A combined fMRI and ecological momentary assessment study of the social brain.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets