Novelty is not surprise: Human exploratory and adaptive behavior in sequential decision-making
Published 2021 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Novelty is not surprise: Human exploratory and adaptive behavior in sequential decision-making
Authors
Keywords
Learning, Electroencephalography, Event-related potentials, Algorithms, Decision making, Statistical models, Regression analysis, Linear regression analysis
Journal
PLoS Computational Biology
Volume 17, Issue 6, Pages e1009070
Publisher
Public Library of Science (PLoS)
Online
2021-06-04
DOI
10.1371/journal.pcbi.1009070
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Learning in Volatile Environments with the Bayes Factor Surprise
- (2021) Vasiliki Liakoni et al. NEURAL COMPUTATION
- Cue-Evoked Dopamine Promotes Conditioned Responding during Learning
- (2020) Joachim Morrens et al. NEURON
- Understanding exploration in humans and machines by formalizing the function of curiosity
- (2020) Rachit Dubey et al. Current Opinion in Behavioral Sciences
- A Unified Framework for Dopamine Signals across Timescales
- (2020) HyungGoo R. Kim et al. CELL
- Dopamine signals as temporal difference errors: recent advances
- (2020) Clara Kwon Starkweather et al. CURRENT OPINION IN NEUROBIOLOGY
- Adaptive learning under expected and unexpected uncertainty
- (2019) Alireza Soltani et al. NATURE REVIEWS NEUROSCIENCE
- Confidence resets reveal hierarchical adaptive learning in humans
- (2019) Micha Heilbron et al. PLoS Computational Biology
- Learning and forgetting using reinforced Bayesian change detection
- (2019) Vincent Moens et al. PLoS Computational Biology
- Brain signatures of a multiscale process of sequence learning in humans
- (2019) Maxime Maheu et al. eLife
- Diverse motives for human curiosity
- (2019) Kenji Kobayashi et al. Nature Human Behaviour
- Trial-by-trial surprise-decoding model for visual and auditory binary oddball tasks
- (2019) Alireza Modirshanechi et al. NEUROIMAGE
- Visual novelty, curiosity, and intrinsic reward in machine learning and the brain
- (2019) Andrew Jaegle et al. CURRENT OPINION IN NEUROBIOLOGY
- Where Does Value Come From?
- (2019) Keno Juechems et al. TRENDS IN COGNITIVE SCIENCES
- One-shot learning and behavioral eligibility traces in sequential decision making
- (2019) Marco P Lehmann et al. eLife
- Ten simple rules for the computational modeling of behavioral data
- (2019) Robert C Wilson et al. eLife
- On the marginal likelihood and crossvalidation
- (2019) E Fong et al. BIOMETRIKA
- Reconciling novelty and complexity through a rational analysis of curiosity.
- (2019) Rachit Dubey et al. PSYCHOLOGICAL REVIEW
- Balancing New against Old Information: The Role of Puzzlement Surprise in Learning
- (2018) Mohammadjavad Faraji et al. NEURAL COMPUTATION
- Eligibility Traces and Plasticity on Behavioral Time Scales: Experimental Support of NeoHebbian Three-Factor Learning Rules
- (2018) Wulfram Gerstner et al. Frontiers in Neural Circuits
- Towards a neuroscience of active sampling and curiosity
- (2018) Jacqueline Gottlieb et al. NATURE REVIEWS NEUROSCIENCE
- The algorithmic architecture of exploration in the human brain
- (2018) Eric Schulz et al. CURRENT OPINION IN NEUROBIOLOGY
- Active Inference: A Process Theory
- (2017) Karl Friston et al. NEURAL COMPUTATION
- The computational nature of memory modification
- (2017) Samuel J Gershman et al. eLife
- Neuromodulated Spike-Timing-Dependent Plasticity, and Theory of Three-Factor Learning Rules
- (2016) Nicolas Frémaux et al. Frontiers in Neural Circuits
- Human Inferences about Sequences: A Minimal Transition Probability Model
- (2016) Florent Meyniel et al. PLoS Computational Biology
- When Does Model-Based Control Pay Off?
- (2016) Wouter Kool et al. PLoS Computational Biology
- Reinforcement Learning in Multidimensional Environments Relies on Attention Mechanisms
- (2015) Y. Niv et al. JOURNAL OF NEUROSCIENCE
- A computational analysis of the neural bases of Bayesian inference
- (2015) Antonio Kolossa et al. NEUROIMAGE
- Interplay of approximate planning strategies
- (2015) Quentin J. M. Huys et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
- Simple Plans or Sophisticated Habits? State, Transition and Learning Interactions in the Two-Step Task
- (2015) Thomas Akam et al. PLoS Computational Biology
- A critical time window for dopamine actions on the structural plasticity of dendritic spines
- (2014) S. Yagishita et al. SCIENCE
- Statistical Computations Underlying the Dynamics of Memory Updating
- (2014) Samuel J. Gershman et al. PLoS Computational Biology
- VBA: A Probabilistic Treatment of Nonlinear Models for Neurobiological and Behavioural Data
- (2014) Jean Daunizeau et al. PLoS Computational Biology
- Bayesian model selection for group studies — Revisited
- (2013) L. Rigoux et al. NEUROIMAGE
- Information-seeking, curiosity, and attention: computational and neural mechanisms
- (2013) Jacqueline Gottlieb et al. TRENDS IN COGNITIVE SCIENCES
- Rational regulation of learning dynamics by pupil-linked arousal systems
- (2012) Matthew R Nassar et al. NATURE NEUROSCIENCE
- Mapping value based planning and extensively trained choice in the human brain
- (2012) Klaus Wunderlich et al. NATURE NEUROSCIENCE
- Evidence for neural encoding of Bayesian surprise in human somatosensation
- (2012) Dirk Ostwald et al. NEUROIMAGE
- Learning from experience: Event-related potential correlates of reward processing, neural adaptation, and behavioral choice
- (2012) Matthew M. Walsh et al. NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS
- Multiple representations and algorithms for reinforcement learning in the cortico-basal ganglia circuit
- (2011) Makoto Ito et al. CURRENT OPINION IN NEUROBIOLOGY
- Model-Based Influences on Humans' Choices and Striatal Prediction Errors
- (2011) Nathaniel D. Daw et al. NEURON
- An Approximately Bayesian Delta-Rule Model Explains the Dynamics of Belief Updating in a Changing Environment
- (2010) M. R. Nassar et al. JOURNAL OF NEUROSCIENCE
- The free-energy principle: a unified brain theory?
- (2010) Karl Friston NATURE REVIEWS NEUROSCIENCE
- States versus Rewards: Dissociable Neural Prediction Error Signals Underlying Model-Based and Model-Free Reinforcement Learning
- (2010) Jan Gläscher et al. NEURON
- Formal Theory of Creativity, Fun, and Intrinsic Motivation (1990–2010)
- (2010) Jürgen Schmidhuber IEEE Transactions on Autonomous Mental Development
- Bayesian model selection for group studies
- (2009) Klaas Enno Stephan et al. NEUROIMAGE
- Trial-by-Trial Fluctuations in the Event-Related Electroencephalogram Reflect Dynamic Changes in the Degree of Surprise
- (2008) R. B. Mars et al. JOURNAL OF NEUROSCIENCE
Publish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn MoreAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started