Using Effort to Measure Reward Value of Faces in Children with Autism

Ewing, Louise; Pellicano, Liz; Rhodes, Gillian

doi:10.1371/journal.pone.0079493

Cited by 37 publications

(43 citation statements)

References 39 publications

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“…Unlike preferential looking measures, behavioural approach or instrumental choice tasks have been less consistent in indicating preference for social stimuli in neurotypical children [20][21][22][23]. In the present study, we replicated the findings by Ruta and colleagues [23] using an adapted version of the original task.…”

Section: Discussionsupporting

confidence: 83%

“…The second set of studies examining social reward responsivity in instrumental paradigms used effort as an index of social reward responsivity. In tasks of this type, participants exert different amounts of effort (made through complex or multiple button presses) to obtain a social or a nonsocial reward [19,20]. These tasks demonstrate that neurotypical adults carefully evaluate the level of effort required and available outcomes while making a choice.…”

Section: Introductionmentioning

confidence: 99%

“…These tasks demonstrate that neurotypical adults carefully evaluate the level of effort required and available outcomes while making a choice. They invest more effort to get social reward than non-social but no such preference is seen in neurotypical adolescents [20][21][22]. Ruta and colleagues used a similar but simpler paradigm targeted for younger children (14-68 months), where children choose one of two buttons to look at social or non-social images [23].…”

Section: Introductionmentioning

confidence: 99%

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Quantifying social preference in young children using two tasks on a mobile platform

Dubey¹,

Brett²,

Ruta³

et al. 2019

Preprint

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˄ Membership of the START consortium is provided in the Acknowledgements. AbstractChildren typically prefer social stimuli (e.g. faces, smiles) over non-social stimuli (e.g. natural scene, household objects). This social preference is believed to be an essential building block for later social skills and healthy social development. Measuring social reward responsiveness poses an empirical challenge, as it encompasses multiple underlying processes. In this study, we use a preferential looking task and an instrumental choice task to capture different potential processes underlying social preference, in over 100 typically developing 3-9 year old children. Children spent longer looking at social stimuli in the preferential looking task but did not show a similar preference for social rewards on the instrumental choice task. This study highlights the importance of choice of paradigms when evaluating social preference and their potential impact on understanding social reward responsivity.

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Section: Discussionsupporting

confidence: 83%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Quantifying social preference in young children using two tasks on a mobile platform

Dubey¹,

Brett²,

Ruta³

et al. 2019

Preprint

View full text Add to dashboard Cite

show abstract

“…Findings also revealed higher scores in affective drive predicted higher scores on the SII-SF. This showed that the interest or tendency to be sensitive to others’ emotions relates to a greater sense of feeling towards others [166–168]. Findings also showed higher scores in cognitive ability predicted higher scores on the SII-SF.…”

Section: Discussionmentioning

confidence: 99%

The Development and Validation of the Empathy Components Questionnaire (ECQ)

2017

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Key research suggests that empathy is a multidimensional construct comprising of both cognitive and affective components. More recent theories and research suggest even further factors within these components of empathy, including the ability to empathize with others versus the drive towards empathizing with others. While numerous self-report measures have been developed to examine empathy, none of them currently index all of these wider components together. The aim of the present research was to develop and validate the Empathy Components Questionnaire (ECQ) to measure cognitive and affective components, as well as ability and drive components within each. Study one utilized items measuring cognitive and affective empathy taken from various established questionnaires to create an initial version of the ECQ. Principal component analysis (PCA) was used to examine the underlying components of empathy within the ECQ in a sample of 101 typical adults. Results revealed a five-component model consisting of cognitive ability, cognitive drive, affective ability, affective drive, and a fifth factor assessing affective reactivity. This five-component structure was then validated and confirmed using confirmatory factor analysis (CFA) in an independent sample of 211 typical adults. Results also showed that females scored higher than males overall on the ECQ, and on specific components, which is consistent with previous findings of a female advantage on self-reported empathy. Findings also showed certain components predicted scores on an independent measure of social behavior, which provided good convergent validity of the ECQ. Together, these findings validate the newly developed ECQ as a multidimensional measure of empathy more in-line with current theories of empathy. The ECQ provides a useful new tool for quick and easy measurement of empathy and its components for research with both healthy and clinical populations.

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“…One possible explanation for this phenomenon is the atypical development in social motivation in ASD (Chevallier et al, 2012). Some also argue that atypical development in social motivation in individuals with ASD is related to the atypical development of social reward processing (Bartz et al, 2011;Modi and Young, 2012;Dubey et al, 2015), although others did not find differences in the reinforcement value of social stimuli between individuals with and without ASD (e.g., Ewing et al, 2013;Vernetti et al, 2018). Overall, there is a theoretical and clinical interest in the possible influence of social motivation on the development of social attention and learning.…”

Section: Experiments 2: Modeling Individual Differencesmentioning

confidence: 99%

Learning Process of Gaze Following: Computational Modeling Based on Reinforcement Learning

2020

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Many studies have explored factors which influence gaze-following behavior of young infants. However, the results of empirical studies were inconsistent, and the mechanism underlying the contextual modulation of gaze following remains unclear. In order to provide valuable insight into the mechanisms underlying gaze following, we conducted computational modeling using Q-learning algorithm and simulated the learning process of infant gaze following to suggest a feasible model. In Experiment 1, we simulated how communicative cues and infant internal states affect the learning process of gaze following. The simulation indicated that the model in which communicative cues enhance infant internal states is the most feasible to explain the infant learning process. In Experiment 2, we simulated how individual differences in motivation for communication affect the learning process. The results showed that low motivation for communication can delay the learning process and decrease the frequency of gaze following. These simulations suggest that communicative cues may enhance infants' internal states and promote the development of gaze following. Also, initial social motivation may affect the learning process of social behaviors in the long term.

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Using Effort to Measure Reward Value of Faces in Children with Autism

Cited by 37 publications

References 39 publications

Quantifying social preference in young children using two tasks on a mobile platform

Quantifying social preference in young children using two tasks on a mobile platform

The Development and Validation of the Empathy Components Questionnaire (ECQ)

Learning Process of Gaze Following: Computational Modeling Based on Reinforcement Learning

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