scholarly journals Neural Arbitration between Social and Individual Learning Systems

2019 ◽  
Author(s):  
Andreea O. Diaconescu ◽  
Madeline Stecy ◽  
Lars Kasper ◽  
Christopher J. Burke ◽  
Zoltan Nagy ◽  
...  
Keyword(s):  
Prefrontal Cortex ◽  
Functional Neuroimaging ◽  
Learning Task ◽  
Brain Regions ◽  
Individual Learning ◽  
Learning Systems ◽  
Learning System ◽  
The Other ◽  
Relative Precision ◽  
Temporoparietal Junction

AbstractDecision making often requires integrating self-gathered information with information acquired from observing others. Depending on the situation, it may be beneficial to rely more on one than the other source, taking into account that either information may be imprecise or deceiving. The process by which one source is selected over the other based on perceived reliability, here defined as arbitration, has not been fully elucidated. In this study, we formalised arbitration as the relative reliability (precision) of predictions afforded by each learning system using hierarchical Bayesian models. In a probabilistic learning task, participants predicted the outcome of a lottery using recommendations from a more informed advisor and self-sampled outcomes. The number of points participants wagered on their predictions reflected arbitration: The higher the relative precision of one learning system over the other and the lower the intention volatility, the more points participants wagered on a given trial. Functional neuroimaging demonstrated that the arbitration signal was independent of decision confidence and involved modalityspecific brain regions. Arbitrating in favour of self-gathered information activated the dorsolateral prefrontal cortex and the midbrain whereas arbitrating in favour of social information engaged ventromedial prefrontal cortex and the temporoparietal junction. These findings are in line with domain specificity and indicate that relative precision captures arbitration between social and individual learning systems at both the behavioural and neural level.

scholarly journals Neural arbitration between social and individual learning systems

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Andreea Oliviana Diaconescu ◽  
Madeline Stecy ◽  
Lars Kasper ◽  
Christopher J Burke ◽  
Zoltan Nagy ◽  
...  
Keyword(s):  
Prefrontal Cortex ◽  
Functional Neuroimaging ◽  
Learning Task ◽  
Brain Regions ◽  
Individual Learning ◽  
Learning Systems ◽  
Learning System ◽  
Relative Precision ◽  
Decision Confidence ◽  
Dorsolateral Prefrontal

Decision making requires integrating knowledge gathered from personal experiences with advice from others. The neural underpinnings of the process of arbitrating between information sources has not been fully elucidated. In this study, we formalized arbitration as the relative precision of predictions, afforded by each learning system, using hierarchical Bayesian modeling. In a probabilistic learning task, participants predicted the outcome of a lottery using recommendations from a more informed advisor and/or self-sampled outcomes. Decision confidence, as measured by the number of points participants wagered on their predictions, varied with our definition of arbitration as a ratio of precisions. Functional neuroimaging demonstrated that arbitration signals were independent of decision confidence and involved modality-specific brain regions. Arbitrating in favor of self-gathered information activated the dorsolateral prefrontal cortex and the midbrain, whereas arbitrating in favor of social information engaged the ventromedial prefrontal cortex and the amygdala. These findings indicate that relative precision captures arbitration between social and individual learning systems at both behavioral and neural levels.

scholarly journals Shifting prosocial intuitions: Neurocognitive evidence for a value based account of group-based cooperation

2018 ◽  
Author(s):  
Leor M Hackel ◽  
Julian Augustus Wills ◽  
Jay Joseph Van Bavel
Keyword(s):  
Prefrontal Cortex ◽  
Social Issues ◽  
Functional Neuroimaging ◽  
Brain Regions ◽  
Selfish Behavior ◽  
Opposite Pattern ◽  
Temporoparietal Junction ◽  
Public Goods Games ◽  
Prosocial Tendencies ◽  
The Right

Cooperation is necessary for solving numerous social issues, including climate change, effective governance, and economic stability. Value-based decision models contend that prosocial tendencies and social context shape people’s preferences for cooperative or selfish behavior. Using functional neuroimaging and computational modeling, we tested these predictions by comparing activity in brain regions previously linked to valuation and executive function during decision-making—the ventromedial prefrontal cortex (vmPFC) and dorsolateral prefrontal cortex (dlPFC), respectively. Participants played Public Goods Games with students from fictitious universities, where social norms were selfish or cooperative. Prosocial participants showed greater vmPFC activity when cooperating and dlPFC-vmPFC connectivity when acting selfishly, whereas selfish participants displayed the opposite pattern. Norm-sensitive participants showed greater dlPFC-vmPFC connectivity when defying group norms. Modeling expectations of cooperation was associated with activity near the right temporoparietal junction. Consistent with value-based models, this suggests prosocial tendencies and contextual norms flexibly determine whether people prefer cooperation or defection.

scholarly journals Shifting prosocial intuitions: neurocognitive evidence for a value-based account of group-based cooperation

2020 ◽  
Vol 15 (4) ◽  
pp. 371-381
Author(s):  
Leor M Hackel ◽  
Julian A Wills ◽  
Jay J Van Bavel
Keyword(s):  
Prefrontal Cortex ◽  
Social Issues ◽  
Functional Neuroimaging ◽  
Brain Regions ◽  
Selfish Behavior ◽  
Opposite Pattern ◽  
Temporoparietal Junction ◽  
Public Goods Games ◽  
Prosocial Tendencies ◽  
The Right

Abstract Cooperation is necessary for solving numerous social issues, including climate change, effective governance and economic stability. Value-based decision models contend that prosocial tendencies and social context shape people’s preferences for cooperative or selfish behavior. Using functional neuroimaging and computational modeling, we tested these predictions by comparing activity in brain regions previously linked to valuation and executive function during decision-making—the ventromedial prefrontal cortex (vmPFC) and dorsolateral prefrontal cortex (dlPFC), respectively. Participants played Public Goods Games with students from fictitious universities, where social norms were selfish or cooperative. Prosocial participants showed greater vmPFC activity when cooperating and dlPFC-vmPFC connectivity when acting selfishly, whereas selfish participants displayed the opposite pattern. Norm-sensitive participants showed greater dlPFC-vmPFC connectivity when defying group norms. Modeling expectations of cooperation was associated with activity near the right temporoparietal junction. Consistent with value-based models, this suggests that prosocial tendencies and contextual norms flexibly determine whether people prefer cooperation or defection.

scholarly journals Building Learning System for Content Knowledge and Social Knowledge

2018 ◽  
Vol 13 (01) ◽  
pp. 4
Author(s):  
S.M.F.D Syed Mustapha
Keyword(s):  
Content Knowledge ◽  
Intelligent Tutoring System ◽  
Individual Learning ◽  
Learning Systems ◽  
Learning System ◽  
Social Knowledge ◽  
Computer Based Training ◽  
Web 3.0 ◽  
Knowledge Models ◽  
Computer Aided

In the late 50’s or early 60’s, there were huge interests towards building learning systems for individual learning and they are called with various names such as Intelligent Tutoring System, Microworld, Computer Based Training, Computer Aided System, Intelligent Computer Aided Instruction and others. They are made to be different with regard to the technological approaches and the learning pedagogies, knowledge models and student models. Over the years, the interest of building learning systems has migrated from individual learning on content knowledge to community learning as the result of the recent Web 2.0 and Web 3.0 sociotechnological wave. The paper describes the work that was done to develop the learning system in both situations – content knowledge and social knowledge where the experiences mainly in capturing the knowledge and representing them are different

scholarly journals Novel Inferences in a Multidimensional Social Network Use a Grid-like Code

2020 ◽  
Author(s):  
Seongmin A. Park ◽  
Douglas S. Miller ◽  
Erie D. Boorman
Keyword(s):  
Decision Making ◽  
Prefrontal Cortex ◽  
Medial Prefrontal Cortex ◽  
Entorhinal Cortex ◽  
Brain Regions ◽  
Cognitive Map ◽  
General Mechanism ◽  
Temporoparietal Junction ◽  
Flexible Behavior ◽  
Discrete Problems

ABSTRACTGeneralizing experiences to guide decision making in novel situations is a hallmark of flexible behavior. It has been hypothesized such flexibility depends on a cognitive map of an environment or task, but directly linking the two has proven elusive. Here, we find that discretely sampled abstract relationships between entities in an unseen two-dimensional (2-D) social hierarchy are reconstructed into a unitary 2-D cognitive map in the hippocampus and entorhinal cortex. We further show that humans utilize a grid-like code in several brain regions, including entorhinal cortex and medial prefrontal cortex, for inferred direct trajectories between entities in the reconstructed abstract space during discrete decisions. Moreover, these neural grid-like codes in the entorhinal cortex predict neural decision value computations in the medial prefrontal cortex and temporoparietal junction area during choice. Collectively, these findings show that grid-like codes are used by the human brain to infer novel solutions, even in abstract and discrete problems, and suggest a general mechanism underpinning flexible decision making and generalization.

Indexing Serious Games to Meet Adaptive E-Learning System Needs

2020 ◽  
pp. 284-303
Author(s):  
Yassine El Borji ◽  
Mohammed Khaldi
Keyword(s):  
Serious Games ◽  
Main Idea ◽  
Learning Objects ◽  
Learning Systems ◽  
Learning System ◽  
The Other ◽  
E Learning ◽  
Technical Sense ◽  
Application Profile ◽  
Educational Field

This chapter aims to strengthen the integration of serious games in the educational field by providing tools to monitor and assist the progress of learners/players. The main idea is to address the integration aspects and the deployment of serious games in adaptive e-learning systems based on the automatic package and the export of serious games as reusable learning objects (LO). This integration will allow SGs to benefit from the tracking and support features offered by the LMS. On the other hand, LMS can supplement their training offer and reach a certain maturity. The approach aims to meet the specific needs of SGs in terms of metadata so that they can be described, indexed, and capitalized. This is a new application profile of the IEEE LOM standard entitled “SGLOM” integrating fields to describe SGs not only in a technical sense but also by examining the pedagogical and playful criteria. The authors also focus on the integration and extraction aspects of SGs in an LMS using the ADL SCORM 2004 data model that defines how content can be packaged as a SCORM PIF (package interchange file).

scholarly journals Dorsolateral and dorsomedial prefrontal cortex track distinct properties of dynamic social behavior

2020 ◽  
Vol 15 (4) ◽  
pp. 383-393
Author(s):  
Kelsey R McDonald ◽  
John M Pearson ◽  
Scott A Huettel
Keyword(s):  
Prefrontal Cortex ◽  
Video Game ◽  
Brain Regions ◽  
Neural Mechanisms ◽  
Strategic Action ◽  
General Role ◽  
Temporoparietal Junction ◽  
Dorsomedial Prefrontal Cortex ◽  
Decision Neuroscience ◽  
Dorsolateral Prefrontal

Abstract Understanding how humans make competitive decisions in complex environments is a key goal of decision neuroscience. Typical experimental paradigms constrain behavioral complexity (e.g. choices in discrete-play games), and thus, the underlying neural mechanisms of dynamic social interactions remain incompletely understood. Here, we collected fMRI data while humans played a competitive real-time video game against both human and computer opponents, and then, we used Bayesian non-parametric methods to link behavior to neural mechanisms. Two key cognitive processes characterized behavior in our task: (i) the coupling of one’s actions to another’s actions (i.e. opponent sensitivity) and (ii) the advantageous timing of a given strategic action. We found that the dorsolateral prefrontal cortex displayed selective activation when the subject’s actions were highly sensitive to the opponent’s actions, whereas activation in the dorsomedial prefrontal cortex increased proportionally to the advantageous timing of actions to defeat one’s opponent. Moreover, the temporoparietal junction tracked both of these behavioral quantities as well as opponent social identity, indicating a more general role in monitoring other social agents. These results suggest that brain regions that are frequently implicated in social cognition and value-based decision-making also contribute to the strategic tracking of the value of social actions in dynamic, multi-agent contexts.

scholarly journals Early and late neural correlates of mentalizing: ALE meta-analyses in adults, children and adolescents

2021 ◽  
Author(s):  
Lynn V Fehlbaum ◽  
Réka Borbás ◽  
Katharina Paul ◽  
Simon b Eickhoff ◽  
Nora m Raschle
Keyword(s):  
Prefrontal Cortex ◽  
Children And Adolescents ◽  
Medial Prefrontal Cortex ◽  
Temporal Cortex ◽  
Mental States ◽  
Brain Regions ◽  
Inferior Temporal Cortex ◽  
Temporoparietal Junction ◽  
Right Temporoparietal Junction ◽  
Meta Analyses

Abstract The ability to understand mental states of others is referred to as mentalizing and enabled by our Theory of Mind. This social skill relies on brain regions comprising the mentalizing network as robustly observed in adults but also in a growing number of developmental studies. We summarized and compared neuroimaging evidence in children/adolescents and adults during mentalizing using coordinate-based activation likelihood estimation meta-analyses to inform about brain regions consistently or differentially engaged across age categories. Adults (N = 5286) recruited medial prefrontal and middle/inferior frontal cortices, precuneus, temporoparietal junction and middle temporal gyri during mentalizing, which were functionally connected to bilateral inferior/superior parietal lobule and thalamus/striatum. Conjunction and contrast analyses revealed that children and adolescents (N = 479) recruit similar but fewer regions within core mentalizing regions. Subgroup analyses revealed an early continuous engagement of middle medial prefrontal cortex, precuneus and right temporoparietal junction in younger children (8–11 years) and adolescents (12–18 years). Adolescents additionally recruited the left temporoparietal junction and middle/inferior temporal cortex. Overall, the observed engagement of the medial prefrontal cortex, precuneus and right temporoparietal junction during mentalizing across all ages reflects an early specialization of some key regions of the social brain.

scholarly journals Causal evidence for mnemonic metacognition in human precuneus

2018 ◽  
Author(s):  
Qun Ye ◽  
Futing Zou ◽  
Hakwan Lau ◽  
Yi Hu ◽  
Sze Chai Kwok
Keyword(s):  
Prefrontal Cortex ◽  
Transcranial Magnetic Stimulation ◽  
Magnetic Stimulation ◽  
Parietal Lobe ◽  
Functional Neuroimaging ◽  
Repetitive Transcranial Magnetic Stimulation ◽  
Brain Regions ◽  
Neural Basis ◽  
Anterior Prefrontal Cortex

AbstractMetacognition is the capacity to introspectively monitor and control one’s own cognitive processes. Previous anatomical and functional neuroimaging findings implicated the important role of precuneus in metacognition processing, especially during mnemonic tasks. However, the issue of whether this medial parietal cortex is a domain-specific region that supports mnemonic metacognition remains controversial. Here, we focally disrupted this parietal area with repetitive transcranial magnetic stimulation in healthy participants of both sexes, seeking to ascertain its functional necessity for metacognition for memory versus perceptual decisions. Perturbing the precuneal activity impaired the metacognitive efficiency selectively in the memory judgment of temporal-order, but not in perceptual discrimination. Moreover, the correlation in individuals’ metacognitive efficiency between the domains disappeared when the precuneus was perturbed. Together with the previous finding that lesion to the anterior prefrontal cortex impairs perceptual but not mnemonic metacognition, we double dissociated the macro-anatomical underpinnings for the two kinds of metacognitive capacity in an interconnected network of brain regions.SIGNIFICANCE STATEMENTTheories on the neural basis of metacognition have thus far largely centered on the role of prefrontal cortex. Here we refined the theoretical framework through characterizing a unique precuneal involvement in mnemonic metacognition with a noninvasive but inferentially powerful method: transcranial magnetic stimulation. By quantifying meta-cognitive efficiency across two distinct domains (memory vs. perception) that are matched for stimulus characteristics, we reveal an instrumental – and highly selective – role of the precuneus in mnemonic metacognition. These causal evidence corroborate ample clinical reports that parietal lobe lesions often produce inaccurate self-reports of confidence in memory recollection and establish that the precuneus as a nexus for the introspective ability to evaluate the success of memory judgment in humans.

scholarly journals Increased ventromedial prefrontal cortex activity in adolescence benefits prosocial reinforcement learning

2021 ◽  
Author(s):  
Bianca Westhoff ◽  
Neeltje E. Blankenstein ◽  
Elisabeth Schreuders ◽  
Eveline A. Crone ◽  
Anna C. K. van Duijvenvoorde
Keyword(s):  
Prefrontal Cortex ◽  
Reinforcement Learning ◽  
Functional Neuroimaging ◽  
Learning Task ◽  
Developmental Trajectory ◽  
Ventromedial Prefrontal Cortex ◽  
Prediction Errors ◽  
Age Related ◽  
Probabilistic Reinforcement ◽  
Neuroimaging Study

AbstractLearning which of our behaviors benefit others contributes to social bonding and being liked by others. An important period for the development of (pro)social behavior is adolescence, in which peers become more salient and relationships intensify. It is, however, unknown how learning to benefit others develops across adolescence and what the underlying cognitive and neural mechanisms are. In this functional neuroimaging study, we assessed learning for self and others (i.e., prosocial learning) and the concurring neural tracking of prediction errors across adolescence (ages 9-21, N=74). Participants performed a two-choice probabilistic reinforcement learning task in which outcomes resulted in monetary consequences for themselves, an unknown other, or no one. Participants from all ages were able to learn for themselves and others, but learning for others showed a more protracted developmental trajectory. Prediction errors for self were observed in the ventral striatum and showed no age-related differences. However, prediction error coding for others was specifically observed in the ventromedial prefrontal cortex and showed age-related increases. These results reveal insights into the computational mechanisms of learning for others across adolescence, and highlight that learning for self and others show different age-related patterns.

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