scholarly journals Model-based learning deficits in compulsivity are linked to faulty representations of task structure

2020 ◽  
Author(s):  
Tricia X.F. Seow ◽  
Redmond O’Connell ◽  
Claire M. Gillan
Keyword(s):  
Learning Task ◽  
Task Structure ◽  
Learning Deficits ◽  
Accurate Model ◽  
Model Based ◽  
Relational Knowledge ◽  
Band Power ◽  
The World ◽  
Underlying Causes ◽  
Eeg Recordings

AbstractIndividuals with higher levels of compulsivity exhibit poorer performance on tasks that require model-based planning but the underlying causes have yet to be established. Here, we sought to determine whether these deficits stem from impoverished action-outcome relational knowledge (i.e. issues building an accurate model of the world) and/or an inability to translate models into action. 192 participants performed a two-step reinforcement learning task with concurrent EEG recordings. We found that representations of task-relevant action-outcome associations reflected in reaction time and parietal-occipital alpha-band power were stronger in individuals whose decisions were more model-based, and critically, were weaker in those high in compulsivity. At the time of choice, mid-frontal theta power, a general marker of cognitive control, was also negatively associated with compulsivity, but not model-based planning. These data suggest that model-based planning deficits in compulsive individuals may arise from failures in building an accurate model of the world.

scholarly journals Acquisition of visual priors and induced hallucinations in chronic schizophrenia

2018 ◽  
Author(s):  
Vincent Valton ◽  
Povilas Karvelis ◽  
Katie L. Richards ◽  
Aaron R. Seitz ◽  
Stephen M. Lawrie ◽  
...  
Keyword(s):  
Statistical Learning ◽  
Antipsychotic Medication ◽  
Chronic Schizophrenia ◽  
Learning Task ◽  
Detection Task ◽  
Estimation Task ◽  
Learning Deficits ◽  
The World ◽  
Sensory Evidence ◽  
Perceptual Threshold

AbstractProminent theories suggest that symptoms of schizophrenia stem from learning deficiencies resulting in distorted internal models of the world. To further test these theories, we here use a visual statistical learning task known to induce rapid implicit learning of the stimulus statistics (Chalk et al., 2010). In this task, participants are presented with a field of coherently moving dots and need to report the presented direction of the dots (estimation task) and whether they saw any dots or not (detection task). Two of the directions were more frequently presented than the others. In controls, the implicit acquisition of the stimuli statistics influences their perception in two ways: 1-motion directions are perceived as being more similar to the most frequently presented directions than they really are (estimation biases); 2-in the absence of stimuli, participants sometimes report perceiving the most frequently presented directions (a form of hallucinations). Such behaviour is consistent with probabilistic inference, i.e. combining learnt perceptual priors with sensory evidence. We investigated whether patients with chronic, stable, treated schizophrenia (n=20) differ from controls (n=23) in the acquisition of the perceptual priors and/or their influence on perception. We found that, although patients were slower than controls, they showed comparable acquisition of perceptual priors, correctly approximating the stimulus statistics. This suggests that patients have no statistical learning deficits in our task. This may reflect our patients relative wellbeing on antipsychotic medication. Intriguingly, however, patients made significantly fewer hallucinations of the most frequently presented directions than controls and fewer prior-based lapse estimations. This suggests that prior expectations had less influence on patients’ perception than on controls when stimuli were absent or below perceptual threshold.

scholarly journals Acquisition of visual priors and induced hallucinations in chronic schizophrenia

Brain ◽  
2019 ◽  
Vol 142 (8) ◽  
pp. 2523-2537 ◽  
Author(s):  
Vincent Valton ◽  
Povilas Karvelis ◽  
Katie L Richards ◽  
Aaron R Seitz ◽  
Stephen M Lawrie ◽  
...  
Keyword(s):  
Statistical Learning ◽  
Antipsychotic Medication ◽  
Chronic Schizophrenia ◽  
Learning Task ◽  
Detection Task ◽  
Estimation Task ◽  
Learning Deficits ◽  
The World ◽  
Sensory Evidence ◽  
Perceptual Threshold

Abstract Prominent theories suggest that symptoms of schizophrenia stem from learning deficiencies resulting in distorted internal models of the world. To test these theories further, we used a visual statistical learning task known to induce rapid implicit learning of the stimulus statistics. In this task, participants are presented with a field of coherently moving dots and are asked to report the presented direction of the dots (estimation task), and whether they saw any dots or not (detection task). Two of the directions were more frequently presented than the others. In controls, the implicit acquisition of the stimuli statistics influences their perception in two ways: (i) motion directions are perceived as being more similar to the most frequently presented directions than they really are (estimation biases); and (ii) in the absence of stimuli, participants sometimes report perceiving the most frequently presented directions (a form of hallucinations). Such behaviour is consistent with probabilistic inference, i.e. combining learnt perceptual priors with sensory evidence. We investigated whether patients with chronic, stable, treated schizophrenia (n = 20) differ from controls (n = 23) in the acquisition of the perceptual priors and/or their influence on perception. We found that although patients were slower than controls, they showed comparable acquisition of perceptual priors, approximating the stimulus statistics. This suggests that patients have no statistical learning deficits in our task. This may reflect our patients’ relative wellbeing on antipsychotic medication. Intriguingly, however, patients experienced significantly fewer (P = 0.016) hallucinations of the most frequently presented directions than controls when the stimulus was absent or when it was very weak (prior-based lapse estimations). This suggests that prior expectations had less influence on patients’ perception than on controls when stimuli were absent or below perceptual threshold.

Model-Based and Model-Free Social Cognition

2019 ◽  
Author(s):  
Leor M Hackel ◽  
Jeffrey Jordan Berg ◽  
Björn Lindström ◽  
David Amodio
Keyword(s):  
Reinforcement Learning ◽  
Social Cognition ◽  
Learning Strategies ◽  
Memory Systems ◽  
Learning Task ◽  
Financial Advisors ◽  
Model Based ◽  
Model Free ◽  
Systems Model ◽  
Task Assessment

Do habits play a role in our social impressions? To investigate the contribution of habits to the formation of social attitudes, we examined the roles of model-free and model-based reinforcement learning in social interactions—computations linked in past work to habit and planning, respectively. Participants in this study learned about novel individuals in a sequential reinforcement learning paradigm, choosing financial advisors who led them to high- or low-paying stocks. Results indicated that participants relied on both model-based and model-free learning, such that each independently predicted choice during the learning task and self-reported liking in a post-task assessment. Specifically, participants liked advisors who could provide large future rewards as well as advisors who had provided them with large rewards in the past. Moreover, participants varied in their use of model-based and model-free learning strategies, and this individual difference influenced the way in which learning related to self-reported attitudes: among participants who relied more on model-free learning, model-free social learning related more to post-task attitudes. We discuss implications for attitudes, trait impressions, and social behavior, as well as the role of habits in a memory systems model of social cognition.

scholarly journals Multi-Task Learning Using Task Dependencies for Face Attributes Prediction

2019 ◽  
Vol 9 (12) ◽  
pp. 2535
Author(s):  
Di Fan ◽  
Hyunwoo Kim ◽  
Jummo Kim ◽  
Yunhui Liu ◽  
Qiang Huang
Keyword(s):  
Human Computer Interaction ◽  
Video Surveillance ◽  
State Of The Art ◽  
Learning Task ◽  
Face Verification ◽  
Task Learning ◽  
The World ◽  
In The Wild ◽  
And Gender ◽  
Learning Architectures

Face attributes prediction has an increasing amount of applications in human–computer interaction, face verification and video surveillance. Various studies show that dependencies exist in face attributes. Multi-task learning architecture can build a synergy among the correlated tasks by parameter sharing in the shared layers. However, the dependencies between the tasks have been ignored in the task-specific layers of most multi-task learning architectures. Thus, how to further boost the performance of individual tasks by using task dependencies among face attributes is quite challenging. In this paper, we propose a multi-task learning using task dependencies architecture for face attributes prediction and evaluate the performance with the tasks of smile and gender prediction. The designed attention modules in task-specific layers of our proposed architecture are used for learning task-dependent disentangled representations. The experimental results demonstrate the effectiveness of our proposed network by comparing with the traditional multi-task learning architecture and the state-of-the-art methods on Faces of the world (FotW) and Labeled faces in the wild-a (LFWA) datasets.

scholarly journals Sentiment Analysis on Twitter Airline Data

2021 ◽  
Vol 9 (VI) ◽  
pp. 3767-3770
Author(s):  
Kirti Jain
Keyword(s):  
Machine Learning ◽  
Natural Language Processing ◽  
Natural Language ◽  
Sentiment Analysis ◽  
Language Processing ◽  
Learning Task ◽  
Model Based ◽  
Sentiment Mining ◽  
General Opinion

Sentiment analysis, also known as sentiment mining, is a submachine learning task where we want to determine the overall sentiment of a particular document. With machine learning and natural language processing (NLP), we can extract the information of a text and try to classify it as positive, neutral, or negative according to its polarity. In this project, We are trying to classify Twitter tweets into positive, negative, and neutral sentiments by building a model based on probabilities. Twitter is a blogging website where people can quickly and spontaneously share their feelings by sending tweets limited to 140 characters. Because of its use of Twitter, it is a perfect source of data to get the latest general opinion on anything.

scholarly journals Spontaneous task structure formation results in a cost to incidental memory of task stimuli

2018 ◽  
Author(s):  
Christina Bejjani ◽  
Tobias Egner
Keyword(s):  
Structure Formation ◽  
Structure Learning ◽  
Learning Task ◽  
Underlying Structure ◽  
Task Structure ◽  
Cognitive Demands ◽  
Task Set ◽  
Stimulus Response ◽  
Attention To Task ◽  
Task Sets

Humans are characterized by their ability to leverage rules for classifying and linking stimuli to context-appropriate actions. Previous studies have shown that when humans learn stimulus-response associations for two-dimensional stimuli, they implicitly form and generalize hierarchical rule structures (task-sets). However, the cognitive processes underlying structure formation are poorly understood. Across four experiments, we manipulated how trial-unique images mapped onto responses to bias spontaneous task-set formation and investigated structure learning through the lens of incidental stimulus encoding. Participants performed a learning task designed to either promote task-set formation (by “motor-clustering” possible stimulus-action rules), or to discourage it (by using arbitrary category-response mappings). We adjudicated between two hypotheses: Structure learning may promote attention to task stimuli, thus resulting in better subsequent memory. Alternatively, building task-sets might impose cognitive demands (for instance, on working memory) that divert attention away from stimulus encoding. While the clustering manipulation affected task-set formation, there were also substantial individual differences. Importantly, structure learning incurred a cost: spontaneous task-set formation was associated with diminished stimulus encoding. Thus, spontaneous hierarchical task-set formation appears to involve cognitive demands that divert attention away from encoding of task stimuli during structure learning.

Violence, War, and Capital Punishment in For the Life of the World: Toward a Social Ethos of the Orthodox Church

2021 ◽  
pp. 095394682110453
Author(s):  
Philip LeMasters
Keyword(s):  
Capital Punishment ◽  
Orthodox Church ◽  
Moral Reflection ◽  
Power Structures ◽  
The World ◽  
Underlying Causes ◽  
Causes Of Violence ◽  
Spiritual Resources ◽  
The Church ◽  
Social Ethos

In response to the challenges presented by violence, war, and capital punishment, For the Life of the World: Toward a Social Ethos of the Orthodox Church argues that foundational liturgical, canonical, and spiritual resources invite the Church to manifest a foretaste of the fullness of God’s peace amidst the brokenness of a world that remains tragically inclined toward taking the lives of those who bear the divine image and likeness. It also summons the Church to engage people and power structures toward the end of enacting practical reforms that ameliorate the underlying causes of violence, a task especially urgent in light of the powerful weapons and technologies employed by governments today. While reflecting distinctive Orthodox sensibilities on the topics it addresses, the document also presents points of commonality with other Christian traditions of theological and moral reflection, especially concerning the obligation to take realistic initiatives in peacemaking.

Exploration of Non-Revolved Parts Modeling Based on MBD and Pro/ENGINEER

2013 ◽  
Vol 712-715 ◽  
pp. 1171-1174 ◽  
Author(s):  
Li Xin Wang ◽  
Yu Guo ◽  
Ming Yue Guo
Keyword(s):  
Three Dimensional ◽  
Great Change ◽  
Two Dimensional ◽  
Modeling Methods ◽  
Model Based ◽  
Boeing Company ◽  
The World ◽  
Definition Of ◽  
Key Steps ◽  
Product Definition

A great change in mechanical industry has occurred after several successful practices using MBD (Model Based Definition) of The Boeing Company. It is an inevitable trend from two-dimensional product definition to three-dimensional product definition in mechanical industry. Several standards for MBD have emerged around the world. This paper explores the non-revolved parts modeling methods based on MBD and Pro/ENGINEER, presents several key steps about full-annotated model per MBD and then makes a conclusion. Following these methods we successfully build a typical non-revolved model which conforms to MBD standards correctly and efficiently.

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