An Integrated Model of Emotion Processes and Cognition in Social Information Processing

Lemerise, Elizabeth A.; Arsenio, William F.

doi:10.1111/1467-8624.00124

Cited by 1,134 publications

(1,179 citation statements)

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“…Such steps would commonly involve interpreting cues, clarifying goals, generating alternative responses, selecting and implementing a specific response, and evaluating the outcome. Social problem solving is often assessed by asking children to reflect on and answer questions about hypothetical social dilemmas (Dodge, Laird, Lochman, & Zelli, 2002 Recent theorists have recognized that social information processing depends on other cognitive and affective factors and have incorporated into their models such constructs as language pragmatics, executive function, and emotion regulation (Dodge et al, 2002;Guralnick, 1999;Lemerise & Arsenio, 2000). The latter variables are typically treated as stable individual characteristics (i.e., "latent knowledge" per Dodge et al, 2002; "foundation processes" per Guralnick, 1999).…”

Section: Model Componentsmentioning

confidence: 99%

“…Specifically, the cognitive-executive and socialaffective functions in Figure 1 reflect aspects of social information processing that are linked to a network of specific brain regions (Adolphs, 2001;Grady & Keightley, 2002). At the same time, they also represent the stable individual characteristics (i.e., latent knowledge or foundation processes) described in recent models of social competence (Dodge et al, 2002;Guralnick, 1999;Lemerise & Arsenio, 2000).Social cognitive neuroscience also links research on children's social development to the study of childhood brain disorder. Many childhood brain disorders involve insults to the largely anterior brain regions implicated in social information processing.…”

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confidence: 99%

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Social outcomes in childhood brain disorder: A heuristic integration of social neuroscience and developmental psychology.

Yeates

Bigler

Dennis

et al. 2007

Psychological Bulletin

392

400

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The authors propose a heuristic model of the social outcomes of childhood brain disorder that draws on models and methods from both the emerging field of social cognitive neuroscience and the study of social competence in developmental psychology/psychopathology. The heuristic model characterizes the relationships between social adjustment, peer interactions and relationships, social problem solving and communication, social-affective and cognitive-executive processes, and their neural substrates. The model is illustrated by research on a specific form of childhood brain disorder, traumatic brain injury. The heuristic model may promote research regarding the neural and cognitiveaffective substrates of children's social development. It also may engender more precise methods of measuring impairments and disabilities in children with brain disorder and suggest ways to promote their social adaptation. Surprisingly little is known about the extent, basis, and consequences of the social problems associated with neurological dys-function and brain insults occurring during childhood, despite the significant long-term implications of social development for children's functioning at home, in school, and in the community (Parker, Rubin, Erath, Wojslawowicz, & Buskirk, 2006;Rubin, Bukowski, & Parker, 2006). Until recently, the lack of measurement tools and articulated models of social functioning has limited our ability to address social outcomes in children with brain disorder. The development of more sensitive measures and explicit models of social functioning would help researchers and clinicians to target children with brain disorders for further study and intervention.Now is an excellent time to consider social outcomes in children with brain disorder. The emerging field of social cognitive neuroscience provides a critical perspective on the social impact of childhood brain disorder. Social neuroscience not only supplies tools needed to better understand the neural substrates and social-cognitive processes associated with social functioning, but also provides a foundation for a multilevel, integrative analysis of the social difficulties arising from neurological insults (Brothers, 1990;Cacioppo, Berntson, Sheridan, & McClintock, 2000;Moss & Damasio, 2001;Ochsner & Lieberman, 2001;Posner, Rothbart, & Gerardi-Caulton, 2001). Although social neuroscience to date has focused primarily on adults, in part because of the inability to study the developing brain in vivo, this no longer need be the case. With contemporary neuroimaging, various elegant methods are available that can inform researchers about brain development and neuropathology in the study of social behavior in children with brain disorder (Toga & Thompson, 2005).The methods and models derived from social neuroscience will be particularly powerful when combined with those associated with the study of social competence in developmental psychology and developmental psychopathology Rubin, Bukowski, & Parker, 2006). The latter approaches reflect a development...

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Section: Model Componentsmentioning

confidence: 99%

mentioning

confidence: 99%

Social outcomes in childhood brain disorder: A heuristic integration of social neuroscience and developmental psychology.

Yeates

Bigler

Dennis

et al. 2007

Psychological Bulletin

392

400

View full text Add to dashboard Cite

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“…Emotion was measured in terms of arousal reactivity by Williams, Lochman, Phillips, and Barry (2003) who found that moderately aggressive boys exhibited increased heart rate and increased hostile attributions when a threat was introduced. In a test of Lemerise and Arsenio's (2000) theoretical model including emotion, hostile attributions, and aggression, boys' report of their own anger was related positively to their hostile attributions, as well as to their aggression (Orobio de Castro, Merk, Koops, Veerman, & Bosch, 2005). In this same study, boys' interpretation of a peer as appearing angry was related to increased hostile attributions.…”

Section: Hostile Attributions and Emotionmentioning

confidence: 63%

“…As emotion relates to step 2 (interpretation), the authors suggested that the interpretation of hostility could lead to fear or anger, which could further result in preemptive processing, rather than deliberative information-processing. More recent research has suggested that emotion should be an integrated part of the social informationprocessing model because children can come into a social interaction in pre-existing emotional states or with schemas that include affective components from past interactions, in addition to the emotion generated within the social interaction itself (Lemerise & Arsenio, 2000). The emotional cues of a peer in a social situation, as well as schemas, might be particularly influential on the attribution step.…”

Section: Hostile Attributions and Emotionmentioning

confidence: 99%

“…Anger has been included in previous models of social information-processing. Specifically, the anger cues exhibited by peers are thought to be used to develop hostile attributions (Lemerise & Arsenio, 2000). This study controls for the emotional cues of the peer because the "peer" was automated and standard across participants.…”

Section: The Role Of Emotion In Hostile Attributionsmentioning

confidence: 99%

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Real‐time hostile attribution measurement and aggression in children

Yaros

Lochman

Rosenbaum

et al. 2014

Aggressive Behavior

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Hostile attributions are acknowledged as an important part of maladaptive social information-processing that results in aggression in children. Literature suggests the largest effect size between aggressive behavior and hostile attributions is found when hostile attributions are measured using staged situations rather than commonly used vignette-based measures (Orobio de Castro et al., 2002), but few, if any, studies have investigated hostile attributions as they occur in real-time. The current study uses an interactive, video racing game along with a verbal and nonverbal response procedure to measure hostile attributions while children are playing against a presumed peer. A sample of 75 children between the ages of 10 and 13 played the game while their parents were asked to rate their child's reactive and proactive aggression. It was expected that the new real-time measure of hostile attributions would predict reactive aggression, but not proactive aggression. The predictive ability of the new measure was compared with that of the traditional, vignette-based measure of hostile attributions.Participants played a computer video game created for this study by racing their car against a presumed peer, though the opponent's car was actually computer-operated and preprogrammed to ambiguously provoke participants by crashing into their car. A visual prompt appeared on screen to elicit real-time attribution responses, either verbally or nonverbally, after each of eight crashes and at eight non-crash moments.iii Participants' hostile attributions using the nonverbal and verbal response procedures were significantly positively related to parent-rated reactive aggression, when controlling for proactive aggression. Multiple regression indicated that the real-time measure was a significant predictor of reactive aggression, while the vignette-based measure was not. The results of this study illustrate how hostile attributions in real-time occur quickly and simultaneously with social interaction, which differs from the deliberative, controlled appraisal process described in previous literature. These findings can be used to identify specific appraisal deficits in children at risk for aggressive behavior, which could enhance preventive interventions by more precisely targeting these cognitions and more effectively preventing aggression. iv LIST OF ABBREVIATIONS AND SYMBOLS αCronbach's index of internal consistency; probability of a Type I error

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Youth Generalized Anxiety and Brain Activation States During Socioemotional Processing

Camacho,

Schwarzlose,

Perino

et al. 2024

JAMA Psychiatry

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ImportanceThe brain enters distinct activation states to support differential cognitive and emotional processes, but little is known about how brain activation states differ in youths with clinical anxiety.ObjectiveTo characterize brain activation states during socioemotional processing (movie stimuli) and assess associations between state characteristics and movie features and anxiety symptoms.Design, Setting, and ParticipantsThe Healthy Brain Network is an ongoing cross-sectional study of individuals aged 5 to 21 years experiencing difficulties in school, of whom approximately 45% met criteria for a lifetime anxiety disorder diagnosis. Data used in this study are from the first 9 releases (collected in a nonclinical research setting in the New York City metropolitan area from 2015 to 2020) and include 620 youths aged 5 to 15 years (53% of whom met criteria for a lifetime anxiety disorder diagnosis) who watched an emotional video during functional magnetic resonance imaging and completed questionnaires and clinical evaluation. Of those with functional magnetic resonance imaging data, 432 youths aged 7 to 15 years also self-reported on anxiety symptoms. Data were processed and analyzed between February 2020 and August 2024.Main Outcomes and MeasuresA hidden Markov model was trained to identify brain activation states across participants during video watching. Time spent in each state and the moment-to-moment probability of being in each state were extracted. Videos were annotated for emotion-specific and nonspecific information using the EmoCodes system. Self-reported anxiety symptoms were assessed using the Screen for Child Anxiety Related Disorders. Time spent in each state across the video and during and outside of peaks in negative content correlated with generalized and social anxiety scores.ResultsAmong the 620 youths in the overall analysis, 369 were male and the mean (SD) age was 10.4 (2.8) years. In the anxiety symptom analysis, 263 of 432 youths were male and the mean (SD) age was 11.5 (2.2) years. Three brain activation states were identified: a high somatomotor activation state (state 1), a high cingulo-opercular network activation state (state 2), and a high ventral attention and default mode state (state 3). The probability of being in state 3 was correlated with video content that was more negative, quieter, and with less visual motion (ρ &lt; 0.08; P &lt; .001). Increased generalized anxiety was associated with greater time in state 3 (B, 0.10; 95% CI, 0.01 to 0.20; false discovery rate [FDR]–corrected P = .048) and less time in state 2 (B, −0.11; 95% CI, −0.21 to −0.02; FDR-corrected P = .048) when negative social cues were present.Conclusions and RelevanceYouths entered 3 distinct brain activation states during movie watching, and youths with anxiety spent more time in a state with high ventral attention and default activation during negative socioemotional processing. Youths high in generalized anxiety may be more engaged in deeply processing negative emotional content, which may influence self-regulation. Interventions that focus on changing physiological and psychological state during negative social interactions in youths with anxiety should be considered.

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An Integrated Model of Emotion Processes and Cognition in Social Information Processing

Cited by 1,134 publications

References 46 publications

Social outcomes in childhood brain disorder: A heuristic integration of social neuroscience and developmental psychology.

Social outcomes in childhood brain disorder: A heuristic integration of social neuroscience and developmental psychology.

Real‐time hostile attribution measurement and aggression in children

Youth Generalized Anxiety and Brain Activation States During Socioemotional Processing

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