scholarly journals Distinct replay signatures for planning and memory maintenance

2021 ◽  
Author(s):  
G. Elliott Wimmer ◽  
Yunzhe Liu ◽  
Daniel McNamee ◽  
Raymond Dolan
Keyword(s):  
Multivariate Analysis ◽  
Learning Task ◽  
Relative Strength ◽  
Task Demands ◽  
Reward Learning ◽  
Planning Strategy ◽  
Model Based ◽  
Human Participants ◽  
Structure Knowledge ◽  
And Task

Theories of neural replay propose that it supports a range of different functions, most prominently planning and memory maintenance. Here, we test the hypothesis that distinct replay signatures relate to planning and memory maintenance. Our reward learning task required human participants to utilize structure knowledge for 'model-based' evaluation, while maintaining knowledge for two independent and randomly alternating task environments. Using magnetoencephalography (MEG) and multivariate analysis, we found neural evidence for compressed forward replay during planning and backward replay following reward feedback. Prospective replay strength was enhanced for the current environment when the benefits of a model-based planning strategy were higher. Following reward receipt, backward replay for the alternative, distal environment was enhanced as a function of decreasing recency of experience for that environment. Consistent with a memory maintenance role, stronger maintenance-related replay was associated with a modulation of subsequent choices. These findings identify distinct replay signatures consistent with key theoretical proposals on planning and memory maintenance functions, with their relative strength modulated by on-going computational and task demands.

scholarly journals Confirmation bias optimizes reward learning

2021 ◽  
Author(s):  
Tor Tarantola ◽  
Tomas Folke ◽  
Annika Boldt ◽  
Omar D. Pérez ◽  
Benedetto De Martino
Keyword(s):  
Visual Attention ◽  
Confirmation Bias ◽  
Learning Task ◽  
Reward Learning ◽  
Artificial Agents ◽  
Opposite Pattern ◽  
Missed Opportunities ◽  
Predictive Learning ◽  
Asymmetric Learning ◽  
Human Participants

ABSTRACTConfirmation bias—the tendency to overweight information that matches prior beliefs or choices—has been shown to manifest even in simple reinforcement learning. In line with recent work, we find that participants learned significantly more from choice-confirming outcomes in a reward-learning task. What is less clear is whether asymmetric learning rates somehow benefit the learner. Here, we combine data from human participants and artificial agents to examine how confirmation-biased learning might improve performance by counteracting decisional and environmental noise. We evaluate one potential mechanism for such noise reduction: visual attention—a demonstrated driver of both value-based choice and predictive learning. Surprisingly, visual attention showed the opposite pattern to confirmation bias, as participants were most likely to fixate on “missed opportunities”, slightly dampening the effects of the confirmation bias we observed. Several million simulated experiments with artificial agents showed this bias to be a reward-maximizing strategy compared to several alternatives, but only if disconfirming feedback is not completely ignored—a condition that visual attention may help to enforce.

How Effective Feedback for Training Depends on Learner Resources and Task Demands

2006 ◽  
Author(s):  
Anne Collins McLaughlin ◽  
Wendy A. Rogers ◽  
Arthur D. Fisk
Keyword(s):  
Task Demands ◽  
Effective Feedback ◽  
And Task

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.

Construction of Graphic Symbol Utterances by Children, Teenagers, and Adults: The Effect of Structure and Task Demands

2007 ◽  
Vol 50 (5) ◽  
pp. 1314-1329 ◽  
Author(s):  
Natacha Trudeau ◽  
Ann Sutton ◽  
Emmanuelle Dagenais ◽  
Sophie de Broeck ◽  
Jill Morford
Keyword(s):  
Task Demands ◽  
Graphic Symbol ◽  
Effect Of Structure ◽  
And Task

The Effect of Attention on Repetition Suppression and Multivoxel Pattern Similarity

2013 ◽  
Vol 25 (8) ◽  
pp. 1305-1314 ◽  
Author(s):  
Katherine S. Moore ◽  
Do-Joon Yi ◽  
Marvin Chun
Keyword(s):  
Task Demands ◽  
Initial Presentation ◽  
Fmri Signal ◽  
Repetition Suppression ◽  
Specific Memory ◽  
Pattern Similarity ◽  
Parahippocampal Place Area ◽  
And Task

Fundamental to our understanding of learning is the role of attention. We investigated how attention affects two fMRI measures of stimulus-specific memory: repetition suppression (RS) and pattern similarity (PS). RS refers to the decreased fMRI signal when a stimulus is repeated, and it is sensitive to manipulations of attention and task demands. In PS, region-wide voxel-level patterns of responses are evaluated for their similarity across repeated presentations of a stimulus. More similarity across presentations is related to better learning, but the role of attention on PS is not known. Here, we directly compared these measures during the visual repetition of scenes while manipulating attention. Consistent with previous findings, we observed RS in the scene-sensitive parahippocampal place area only when a scene was attended both at initial presentation and upon repetition in subsequent trials, indicating that attention is important for RS. Likewise, we observed greater PS in response to repeated pairs of scenes when both instances of the scene were attended than when either or both were ignored. However, RS and PS did not correlate on either a scene-by-scene or subject-by-subject basis, and PS measures revealed above-chance similarity even when stimuli were ignored. Thus, attention has different effects on RS and PS measures of perceptual repetition.

scholarly journals Color Can Shorten Breakthrough Times in Continuous Flash Suppression through Increased Salience and Task Relevance

Vision ◽  
2021 ◽  
Vol 5 (1) ◽  
pp. 13
Author(s):  
Christian Valuch
Keyword(s):  
Visual Search ◽  
Response Times ◽  
Top Down ◽  
Interocular Suppression ◽  
Continuous Flash Suppression ◽  
Task Relevance ◽  
Mediated Effects ◽  
Dominant Eye ◽  
Human Participants ◽  
And Task

Color can enhance the perception of relevant stimuli by increasing their salience and guiding visual search towards stimuli that match a task-relevant color. Using Continuous Flash Suppression (CFS), the current study investigated whether color facilitates the discrimination of targets that are difficult to perceive due to interocular suppression. Gabor patterns of two or four cycles per degree (cpd) were shown as targets to the non-dominant eye of human participants. CFS masks were presented at a rate of 10 Hz to the dominant eye, and participants had the task to report the target’s orientation as soon as they could discriminate it. The 2-cpd targets were robustly suppressed and resulted in much longer response times compared to 4-cpd targets. Moreover, only for 2-cpd targets, two color-related effects were evident. First, in trials where targets and CFS masks had different colors, targets were reported faster than in trials where targets and CFS masks had the same color. Second, targets with a known color, either cyan or yellow, were reported earlier than targets whose color was randomly cyan or yellow. The results suggest that the targets’ entry to consciousness may have been speeded by color-mediated effects relating to increased (bottom-up) salience and (top-down) task relevance.

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 Moving Beyond Self Introductions to Sharing Self Exploration and Expression

2012 ◽  
Vol 36 (6) ◽  
pp. 27
Author(s):  
Ellen Motohashi
Keyword(s):  
Language Acquisition ◽  
Language Teaching ◽  
Learning Task ◽  
Language Teachers ◽  
Language Teacher ◽  
Teachers And Students ◽  
Based Instruction ◽  
Opening Up ◽  
And Task

Language teachers can easily get caught up in the mechanics and outcome-based instruction of language teaching. Too often, the pedagogic relationship between the language teacher and learner are defined according to the narrowly defined discourse and task-based nature of the learning task designed for language acquisition. Pushing back the boundaries on this relationship and opening up opportunities for self-expression and self exploration through an introductory task termed Self Maps helps teachers and students to move beyond formulaic introductory exchanges and express themselves more deeply in their unique and singular individuality. 語学教師は授業の際、文の構造や学習の成果についとらわれがちである。また多くの場合、語学教師と学習者の関係は、言語習得のためにデザインされた、狭義でのディスコースやタスクに基づく学習活動の性質によって決まってしまう。この両者の間の境界を押し広げ、セルフマップという自己紹介活動を通して自己表現と自己探求の機会を与えることにより、教師と学習者は紋切り型の自己紹介を超え、個々の唯一無二の個性をより深く表現できるようになる。

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