scholarly journals Neuro-computational account of arbitration between imitation and emulation during human observational learning

2019 ◽  
Author(s):  
Caroline C. Charpentier ◽  
Kiyohito Iigaya ◽  
John P. O’Doherty
Keyword(s):  
Prefrontal Cortex ◽  
Observational Learning ◽  
Computational Modelling ◽  
Neural Correlates ◽  
Fundamental Question ◽  
Behavioral Task ◽  
Reliable Prediction ◽  
Ventrolateral Prefrontal Cortex ◽  
Temporoparietal Junction ◽  
The Brain

AbstractIn observational learning (OL), organisms learn from observing the behavior of others. There are at least two distinct strategies for OL. Imitation involves learning to repeat the previous actions of other agents, while in emulation, learning proceeds from inferring the goals and intentions of others. While putative neural correlates for these forms of learning have been identified, a fundamental question remains unaddressed: how does the brain decides which strategy to use in a given situation? Here we developed a novel computational model in which arbitration between the strategies is determined by the predictive reliability, such that control over behavior is adaptively weighted toward the strategy with the most reliable prediction. To test the theory, we designed a novel behavioral task in which our experimental manipulations produced dissociable effects on the reliability of the two strategies. Participants performed this task while undergoing fMRI in two independent studies (the second a pre-registered replication of the first). Behavior manifested patterns consistent with both emulation and imitation and flexibly changed between the two strategies as expected from the theory. Computational modelling revealed that behavior was best described by an arbitration model, in which the reliability of the emulation strategy determined the relative weights allocated to behavior for each strategy. Emulation reliability - the model’s arbitration signal - was encoded in the ventrolateral prefrontal cortex, temporoparietal junction and rostral cingulate cortex. Being replicated across two fMRI studies, these findings suggest a neuro-computational mechanism for allocating control between emulation and imitation during observational learning.

Altruism from the Perspective of the Social Neurosciences

e-Neuroforum ◽  
2018 ◽  
Vol 24 (1) ◽  
pp. A11-A18
Author(s):  
Sabine Windmann ◽  
Grit Hein
Keyword(s):  
Prefrontal Cortex ◽  
Dorsolateral Prefrontal Cortex ◽  
Anterior Insula ◽  
Future Research ◽  
Levels Of Explanation ◽  
Temporoparietal Junction ◽  
The Social ◽  
Dorsolateral Prefrontal ◽  
The Brain ◽  
Research Studies

Abstract Altruism is a puzzling phenomenon, especially for Biology and Economics. Why do individuals reduce their chances to provide some of the resources they own to others? The answer to this question can be sought at ultimate or proximate levels of explanation. The Social Neurosciences attempt to specify the brain mechanisms that drive humans to act altruistically, in assuming that overtly identical behaviours can be driven by different motives. The research has shown that activations and functional connectivities of the Anterior Insula and the Temporoparietal Junction play specific roles in empathetic versus strategic forms of altruism, whereas the dorsolateral prefrontal cortex, among other regions, is involved in norm-oriented punitive forms of altruism. Future research studies could focus on the processing of ambiguity and conflict in pursuit of altruistic intentions.

The Neural Correlates of Consciousness

2020 ◽  
pp. 231-260
Author(s):  
Jorge Morales ◽  
Hakwan Lau
Keyword(s):  
Prefrontal Cortex ◽  
Computational Modelling ◽  
Neural Correlates ◽  
Specific Role ◽  
Statistical Techniques ◽  
Neural Basis ◽  
Hierarchical Processing ◽  
Neural Correlates Of Consciousness ◽  
Processing Architecture ◽  
Selection Of

Our understanding of the neural basis of consciousness has substantially improved in the last few decades. New imaging and statistical techniques have been introduced, experiments have become more sophisticated, and several unsuccessful hypotheses have been quite conclusively ruled out. However, neuroscientists still do not entirely agree on the critical neural features required for sustaining perceptual conscious experiences in humans and other primates. This chapter discusses a selection of influential views of the neural correlates of consciousness and the predictions they make. By highlighting some neurobiological and computational modelling results, it will be argued that the currently available evidence favors a hierarchical processing architecture that confers a crucial, if subtle and specific, role to prefrontal cortex.

scholarly journals Computational modelling of social cognition and behaviour—a reinforcement learning primer

2020 ◽  
Author(s):  
Patricia L Lockwood ◽  
Miriam C Klein-Flügge
Keyword(s):  
Reinforcement Learning ◽  
Social Cognition ◽  
Observational Learning ◽  
Impression Formation ◽  
Computational Models ◽  
Computational Modelling ◽  
Neural Systems ◽  
Neural Basis ◽  
The Past ◽  
The Brain

Abstract Social neuroscience aims to describe the neural systems that underpin social cognition and behaviour. Over the past decade, researchers have begun to combine computational models with neuroimaging to link social computations to the brain. Inspired by approaches from reinforcement learning theory, which describes how decisions are driven by the unexpectedness of outcomes, accounts of the neural basis of prosocial learning, observational learning, mentalizing and impression formation have been developed. Here we provide an introduction for researchers who wish to use these models in their studies. We consider both theoretical and practical issues related to their implementation, with a focus on specific examples from the field.

scholarly journals Neural Responses in Dorsal Prefrontal Cortex Reflect Proactive Interference during an Auditory Reversal Task

2018 ◽  
Author(s):  
Nikolas A. Francis ◽  
Susanne Radtke-Schuller ◽  
Jonathan B. Fritz ◽  
Shihab A. Shamma
Keyword(s):  
Prefrontal Cortex ◽  
Frontal Cortex ◽  
Proactive Interference ◽  
Cognitive Flexibility ◽  
Neural Activity ◽  
Neural Correlates ◽  
Neural Responses ◽  
Reversal Task ◽  
Neural Correlate ◽  
The Brain

AbstractTask-related plasticity in the brain is triggered by changes in the behavioral meaning of sounds. We investigated plasticity in ferret dorsolateral frontal cortex (dlFC) during an auditory reversal task to study the neural correlates of proactive interference, i.e., perseveration of previously learned behavioral meanings that are no longer task-appropriate. Although the animals learned the task, target recognition decreased after reversals, indicating proactive interference. Frontal cortex responsiveness was consistent with previous findings that dlFC encodes the behavioral meaning of sounds. However, the neural responses observed here were more complex. For example, target responses were strongly enhanced, while responses to non-target tones and noises were weakly enhanced and strongly suppressed, respectively. Moreover, dlFC responsiveness reflected the proactive interference observed in behavior: target responses decreased after reversals, most significantly during incorrect behavioral responses. These findings suggest that the weak representation of behavioral meaning in dlFC may be a neural correlate of proactive interference.Significance StatementNeural activity in prefrontal cortex (PFC) is believed to enable cognitive flexibility during sensory-guided behavior. Since PFC encodes the behavioral meaning of sensory events, we hypothesized that weak representation of behavioral meaning in PFC may limit cognitive flexibility. To test this hypothesis, we recorded neural activity in ferret PFC, while ferrets performed an auditory reversal task in which the behavioral meanings of sounds were reversed during experiments. The reversal task enabled us study PFC responses during proactive interference, i.e. perseveration of previously learned behavioral meanings that are no longer task-appropriate. We found that task performance errors increased after reversals while PFC representation of behavioral meaning diminished. Our findings suggest that proactive interference may occur when PFC forms weak sensory-cognitive associations.

scholarly journals Computational modelling of social cognition and behaviour – a reinforcement learning primer

2019 ◽  
Author(s):  
Patricia Lockwood ◽  
Miriam Klein-Flugge
Keyword(s):  
Reinforcement Learning ◽  
Social Cognition ◽  
Observational Learning ◽  
Impression Formation ◽  
Computational Models ◽  
Computational Modelling ◽  
Neural Systems ◽  
Neural Basis ◽  
The Past ◽  
The Brain

Social neuroscience aims to describe the neural systems that underpin social cognition and behaviour. Over the past decade, researchers have begun to combine computational models with neuroimaging to link social computations to the brain. Inspired by approaches from reinforcement learning theory, which describes how decisions are driven by the unexpectedness of outcomes, accounts of the neural basis of prosocial learning, observational learning, mentalising and impression formation have been developed. Here we provide an introduction for researchers who wish to use these models in their studies. We consider both theoretical and practical issues related to their implementation, with a focus on specific examples from the field.

scholarly journals Neural Correlates of Attitudes and Risk Perception for Food Technology Topics

2019 ◽  
Author(s):  
Tyler Davis ◽  
Mark LaCour ◽  
Erin Beyer ◽  
Jessica L. Finck ◽  
Markus F. Miller
Keyword(s):  
Prefrontal Cortex ◽  
Risk Perception ◽  
Resistance To Change ◽  
Neural Correlates ◽  
Consumer Acceptability ◽  
Technological Innovations ◽  
Food Technology ◽  
Perceptions Of Risk ◽  
Subjective Value ◽  
The Brain

AbstractFood technologies provide numerous benefits to society and are extensively vetted for safety. However, many technological innovations still face high levels of skepticism from consumers. To promote development and use of food technologies, it is critical to understand the psychological and neurobiological processes associated with consumer acceptability concerns. The current study uses a neuroscience-based approach to understand consumer attitudes and perceptions of risk associated with food technologies and investigate how such attitudes impact consumer’s processing of information related to food technologies. We used functional magnetic resonance imaging (fMRI) to measure brain activation while participants processed infographics related to food technology topics. For technology topics perceived as riskier (antibiotics and hormones), activation was higher in areas of the lateral prefrontal cortex that are associated with decisional uncertainty. In contrast, technology topics that were viewed more favorably (sustainability and animal welfare) tended to activate the ventromedial prefrontal cortex, a region that processes positive affect and subjective value. Moreover, for information about hormones, the lateral PFC activation was associated with individual differences in resistance to change in risk perception. These results reveal how attitudes and risk perception relate to how the brain processes information about food technologies and how people respond to information about such technologies.

scholarly journals How Self-Appraisal Is Mediated by the Brain

2021 ◽  
Vol 15 ◽  
Author(s):  
Gennady G. Knyazev ◽  
Alexander N. Savostyanov ◽  
Andrey V. Bocharov ◽  
Pavel D. Rudych
Keyword(s):  
Prefrontal Cortex ◽  
Well Being ◽  
Self Esteem ◽  
Causal Modeling ◽  
Mediation Effect ◽  
Inhibitory Input ◽  
Subjective Well Being ◽  
Personality Profiles ◽  
Temporoparietal Junction ◽  
The Brain

Self-appraisal is a process that leads to the formation of self-esteem, which contributes to subjective well-being and mental health. Neuroimaging studies link self-esteem with the activity of the medial prefrontal cortex (MPFC), right temporoparietal junction (rTPJ), posterior cingulate cortex (PCC), anterior insula (AIns), and dorsolateral prefrontal cortex. It is not known, however, how the process of self-appraisal itself is mediated by the brain and how different nodes of the self-appraisal network interact with each other. In this study, we used multilevel mediation analysis of functional MRI data recorded during the trait adjective judgment task, treating the emotional valence of adjectives as the predictor, behavioral response as the dependent variable, and brain activity as the mediator. The mediation effect was revealed in the rTPJ. Dynamic causal modeling showed that positive self-descriptions trigger communication within the network, with the rTPJ exerting the strongest excitatory output and MPFC receiving the strongest excitatory input. rAIns receives the strongest inhibitory input and sends exclusively inhibitory connections to other regions pointing out to its role in the processing of negative self-descriptions. Analysis of individual differences showed that in some individuals, self-appraisal is mostly driven by the endorsement of positive self-descriptions and is accompanied by increased activation and communication between rTPJ, MPFC, and PCC. In others, self-appraisal is driven by the rejection of negative self-descriptions and is accompanied by increased activation of rAIns and inhibition of PCC and MPFC. Membership of these groups was predicted by different personality variables. This evidence uncovers different mechanisms of positive self-bias, which may contribute to different facets of self-esteem and are associated with different personality profiles.

scholarly journals Computational approaches to mentalizing during observational learning and strategic social interactions

2021 ◽  
Author(s):  
Caroline Juliette Charpentier ◽  
John O'Doherty
Keyword(s):  
Social Learning ◽  
Social Interactions ◽  
Observational Learning ◽  
Computational Modelling ◽  
Mental States ◽  
Fully Integrated ◽  
Open Questions ◽  
Predicting Behavior ◽  
The Brain ◽  
Shed Light

In order to make decisions, we often seek and integrate information coming from other people, while at times also keeping track of the knowledge other people acquire from observing our own actions. In this chapter, we examine the computational mechanisms and the involvement of mentalizing when we learn from observing other people and when we engage in strategic social interactions in which two agents recursively represent each other’s beliefs and intentions. We shed light on evidence that regions of the brain’s mentalizing system play a key role in implementing these social learning computations, by representing (i) the mental states of other agents, (ii) how these mental states are dynamically updated over time and (iii) how other agents represent our own beliefs and intentions. We argue in favor of using a neuro-computational approach to study these processes, combining computational modelling to identify specific variables predicting behavior and model-based neuroimaging to understand how and where these variables are represented in the brain. We conclude by highlighting some open questions that remain to be addressed to provide a fully integrated account of mentalizing computations during social learning.

scholarly journals Parsing the components of forgiveness: Psychological and neural mechanisms

2020 ◽  
Author(s):  
Melike Fourie ◽  
Ruud Hortensius ◽  
Jean Decety
Keyword(s):  
Prefrontal Cortex ◽  
Future Research ◽  
Distinct Component ◽  
Temporoparietal Junction ◽  
Proximate Mechanisms ◽  
Neuroscience Research ◽  
Component Processes ◽  
Personal Wellbeing ◽  
The Brain ◽  
Methodological Difficulties

Forgiveness - a shift in motivation away from retaliation and avoidance towards increased goodwill for the perceived wrongdoer - is vital for restoring social relationships and positively impacts personal wellbeing and society at large. Parsing the psychological and neurobiological mechanisms of forgiveness contributes theoretical clarity, yet has remained an outstanding challenge because of conceptual and methodological difficulties in the field. Here, we critically examine the neuroscientific evidence to provide a theoretical framework that accounts for the proximate mechanisms underlying forgiveness. Specifically, we integrate empirical evidence from social psychology and neuroscience to propose that forgiveness relies on three distinct and interacting psychological components: cognitive control, perspective taking, and social valuation. The implication of the lateral prefrontal cortex, temporoparietal junction, and ventromedial prefrontal cortex, respectively, is discussed in the brain networks subserving these distinct component processes. Finally, we outline some caveats that limit the translational value of existing social neuroscience research and provide directions for future research to advance the field of forgiveness.

SPECIFIC PROPERTIES OF TUBULIN IN THE PREFRONTAL CORTEX IN CONTROL, SCHIZOPHRENIA AND VASCULAR DEMENTIA

2020 ◽  
pp. 65-71
Author(s):  
Burbaeva G.Sh. ◽  
Androsova L.V. ◽  
Vorobyeva E.A. ◽  
Savushkina O.K.
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Prefrontal Cortex ◽  
Vascular Dementia ◽  
Binding Activity ◽  
Nephelometric Method ◽  
Rate Of Polymerization ◽  
Mental Diseases ◽  
And Control ◽  
The Brain

The aim of the study was to evaluate the rate of polymerization of tubulin into microtubules and determine the level of colchicine binding (colchicine-binding activity of tubulin) in the prefrontal cortex in schizophrenia, vascular dementia (VD) and control. Colchicine-binding activity of tubulin was determined by Sherlinе in tubulin-enriched extracts of proteins from the samples. Measurement of light scattering during the polymerization of the tubulin was carried out using the nephelometric method at a wavelength of 450-550 nm. There was a significant decrease in colchicine-binding activity and the rate of tubulin polymerization in the prefrontal cortex in both diseases, and in VD to a greater extent than in schizophrenia. The obtained results suggest that not only in Alzheimer's disease, but also in other mental diseases such as schizophrenia and VD, there is a decrease in the level of tubulin in the prefrontal cortex of the brain, although to a lesser extent than in Alzheimer's disease, and consequently the amount of microtubules.

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