Attentional engagement in letter-like shape learning.

Author(s):  
Lola Seyll ◽  
Anne-Laure Salamin ◽  
Alain Content
2020 ◽  
Vol 63 (10) ◽  
pp. 3349-3363
Author(s):  
Naomi H. Rodgers ◽  
Jennifer Y. F. Lau ◽  
Patricia M. Zebrowski

Purpose The purpose of this study was to examine group and individual differences in attentional bias toward and away from socially threatening facial stimuli among adolescents who stutter and age- and sex-matched typically fluent controls. Method Participants included 86 adolescents (43 stuttering, 43 controls) ranging in age from 13 to 19 years. They completed a computerized dot-probe task, which was modified to allow for separate measurement of attentional engagement with and attentional disengagement from facial stimuli (angry, fearful, neutral expressions). Their response time on this task was the dependent variable. Participants also completed the Social Anxiety Scale for Adolescents (SAS-A) and provided a speech sample for analysis of stuttering-like behaviors. Results The adolescents who stutter were more likely to engage quickly with threatening faces than to maintain attention on neutral faces, and they were also more likely to disengage quickly from threatening faces than to maintain attention on those faces. The typically fluent controls did not show any attentional preference for the threatening faces over the neutral faces in either the engagement or disengagement conditions. The two groups demonstrated equivalent levels of social anxiety that were both, on average, very close to the clinical cutoff score for high social anxiety, although degree of social anxiety did not influence performance in either condition. Stuttering severity did not influence performance among the adolescents who stutter. Conclusion This study provides preliminary evidence for a vigilance–avoidance pattern of attentional allocation to threatening social stimuli among adolescents who stutter.


Games ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 62
Author(s):  
Ralph S. Redden ◽  
Greg A. Gagliardi ◽  
Chad C. Williams ◽  
Cameron D. Hassall ◽  
Olave E. Krigolson

When we play competitive games, the opponents that we face act as predictors of the outcome of the game. For instance, if you are an average chess player and you face a Grandmaster, you anticipate a loss. Framed in a reinforcement learning perspective, our opponents can be thought of as predictors of rewards and punishments. The present study investigates whether facing an opponent would be processed as a reward or punishment depending on the level of difficulty the opponent poses. Participants played Rock, Paper, Scissors against three computer opponents while electroencephalographic (EEG) data was recorded. In a key manipulation, one opponent (HARD) was programmed to win most often, another (EASY) was made to lose most often, and the third (AVERAGE) had equiprobable outcomes of wins, losses, and ties. Through practice, participants learned to anticipate the relative challenge of a game based on the opponent they were facing that round. An analysis of our EEG data revealed that winning outcomes elicited a reward positivity relative to losing outcomes. Interestingly, our analysis of the predictive cues (i.e., the opponents’ faces) demonstrated that attentional engagement (P3a) was contextually sensitive to anticipated game difficulty. As such, our results for the predictive cue are contrary to what one might expect for a reinforcement model associated with predicted reward, but rather demonstrate that the neural response to the predictive cue was encoding the level of engagement with the opponent as opposed to value relative to the anticipated outcome.


Author(s):  
Tan-Nhu Nguyen ◽  
Vi-Do Tran ◽  
Ho-Quang Nguyen ◽  
Duc-Phong Nguyen ◽  
Tien-Tuan Dao

2018 ◽  
Vol 55 (4) ◽  
pp. 657-696 ◽  
Author(s):  
Steve Myran ◽  
Ian Sutherland

Purpose: The purpose of this article is to reframe our field’s narrative around the science of learning. We seek to (1) describe the patterns within educational leadership and administration that are conceptually tethered to scientific management and highlight the absence of clearly defined conceptions of learning, (2) provide a synthesis of the science of learning, and (3) offer a “progressive problem shift” that promotes such a reframing. Methods: An integration of theory building methods with problem posing/identification strategies is designed to deconstruct the field of educational leadership through a science of learning lens and build toward theory that is more adaptive to our goals of leading for learning. Findings: Our findings stem from the central observation that educational leadership and administration has to date produced no conceptual or explicit operational definition of learning. Lacking such a definition, the field has been vulnerable to outlooks about learning that default to assumptions notably shaped by scientific management. This is in contrast to our review of the learning sciences literature, which emphasizes that learning is dependent on the active and deliberate agency of the learner and a host of introspective outlooks and behaviors and that these individual learning characteristics are situated within complex and dynamic social contexts that serve to mediate and shape learning. Implications and Conclusions: We argue that the future of our field rests, in large measure, on our ability to address the incongruences between our field’s foundations in scientific management and the science of learning.


2019 ◽  
Author(s):  
Alexandra O. Cohen ◽  
Kate Nussenbaum ◽  
Hayley Dorfman ◽  
Samuel J. Gershman ◽  
Catherine A. Hartley

Beliefs about the controllability of positive or negative events in the environment can shape learning throughout the lifespan. Previous research has shown that adults’ learning is modulated by beliefs about the causal structure of the environment such that they will update their value estimates to a lesser extent when the outcomes can be attributed to hidden causes. The present study examined whether external causes similarly influenced outcome attributions and learning across development. Ninety participants, ages 7 to 25 years, completed a reinforcement learning task in which they chose between two options with fixed reward probabilities. Choices were made in three distinct environments in which different hidden agents occasionally intervened to generate positive, negative, or random outcomes. Participants’ beliefs about hidden-agent intervention aligned well with the true probabilities of positive, negative, or random outcome manipulation in each of the three environments. Computational modeling of the learning data revealed that while the choices made by both adults (ages 18 - 25) and adolescents (ages 13 - 17) were best fit by Bayesian reinforcement learning models that incorporate beliefs about hidden agent intervention, those of children (ages 7 - 12) were best fit by a one learning rate model that updates value estimates based on choice outcomes alone. Together, these results suggest that while children demonstrate explicit awareness of the causal structure of the task environment they do not implicitly use beliefs about the causal structure of the environment to guide reinforcement learning in the same manner as adolescents and adults.


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