Sarah L. Master

发表

Modeling the development of decision making in volatile environments using strategies, reinforcement learning, and Bayesian inference

Ronald E. Dahl, Maria K. Eckstein, Anne G. E. Collins, 2019 .

Reinforcement Learning and Bayesian Inference Provide Complementary Models for the Unique Advantage of Adolescents in Stochastic Reversal

Ronald E. Dahl, Maria K. Eckstein, Sarah L. Master, 2020, bioRxiv.

Neurocognitive components of the behavioral inhibition and activation systems: implications for theories of self-regulation.

Sarah L. Master, Shelley E. Taylor, C. M. Yee, 2007, Psychophysiology.

Attachment figures activate a safety signal-related neural region and reduce pain experience

Matthew D. Lieberman, Bruce D. Naliboff, Naomi I. Eisenberger, 2011, Proceedings of the National Academy of Sciences.

Distentangling the systems contributing to changes in learning during adolescence

Maria K. Eckstein, Sarah L. Master, Linda Wilbrecht, 2019, Developmental Cognitive Neuroscience.

A Picture's Worth

Matthew D. Lieberman, Bruce D. Naliboff, Naomi I. Eisenberger, 2009, Psychological science.

Distentangling the systems contributing to changes in learning during adolescence

Maria K. Eckstein, Sarah L. Master, Linda Wilbrecht, 2020, Developmental Cognitive Neuroscience.

Modeling changes in probabilistic reinforcement learning during adolescence

Maria K. Eckstein, Sarah L. Master, Anne G E Collins, 2020, bioRxiv.

Reinforcement learning and Bayesian inference provide complementary models for the unique advantage of adolescents in stochastic reversal

Maria K. Eckstein, Sarah L. Master, L. Wilbrecht, 2022, Developmental Cognitive Neuroscience.

The interpretation of computational model parameters depends on the context

Maria K. Eckstein, Sarah L. Master, L. Wilbrecht, 2021, bioRxiv.

Neurobiological correlates of coping through emotional approach

Sarah L. Master, Shelley E. Taylor, Clayton J. Hilmert, 2009, Brain, Behavior, and Immunity.

Resting-state brain oscillations predict cognitive function in psychiatric disorders: A transdiagnostic machine learning approach

Sarah L. Master, D. Smit, D. Denys, 2021, NeuroImage: Clinical.

Reinforcement learning and Bayesian inference provide complementary models for the unique advantage of adolescents in stochastic reversal

Maria K. Eckstein, Sarah L. Master, L. Wilbrecht, 2020, Developmental Cognitive Neuroscience.

The Unique Advantage of 1 Adolescents in Probabilistic Reversal: 2 Reinforcement Learning and 3 Bayesian Inference Provide 4 Adequate and Complementary 5 Models 6

Maria K. Eckstein, Sarah L. Master, L. Wilbrecht, 2021 .

Neurocognitive correlates of liberalism and conservatism

Sarah L. Master, C. M. Yee, J. Jost, 2007, Nature Neuroscience.

Social responses to stress: The tend-and-befriend model.

Sarah L. Master, Shelley E. Taylor, 2011 .

Reinforcement learning and Bayesian inference provide complementary models for the unique advantage of adolescents in stochastic reversal

Maria K. Eckstein, Sarah L. Master, L. Wilbrecht, 2022, Developmental Cognitive Neuroscience.

Wagers for work: Decomposing the costs of cognitive effort

Sarah L. Master, P. Dayan, C. Curtis, 2023, bioRxiv.

Neurobiological correlates of coping through emotional approach

Sarah L. Master, Shelley E. Taylor, Clayton J. Hilmert, 2009, Brain, behavior, and immunity.

Trying harder: how cognitive effort sculpts neural representations during working memory

Sarah L. Master, Shanshan Li, Clayton E. Curtis, 2023, bioRxiv.

The Unique Advantage of 1 Adolescents in Probabilistic Reversal: 2 Reinforcement Learning and 3 Bayesian Inference Provide 4 Adequate and Complementary 5 Models 6

Maria K. Eckstein, Sarah L. Master, L. Wilbrecht, 2021 .

Learning under uncertainty changes during adolescence

Maria K. Eckstein, Sarah L. Master, Linda Wilbrecht, 2020, CogSci.