Goal-Directed Decision Making. Computations and Neural Circuits

Table of Contents

1. Actions and Habits: Psychological Issues in Dual Process Theory

Computations 2. Instrumental Divergence and Goal-Directed Choice 3. Temporal Dynamics of Goal-Directed Decision Making 4. Episodic Memory Influences on Goal-Directed Decision Making 5. Structure Learning 6. Simulation and Evaluation in Deliberative Decision Making 7. Competition and Cooperation between Multiple RL Systems

Neuroscience 8. Cortical Determinants of Goal-Directed Action 9. Distinct Functional Microcircuits in the Nucleus Accumbens Underlying Goal-Directed Decision Making 10. Striatal Cholinergic Interneurons and Goal-Directed Learning 11. Dopaminergic Prediction Errors and the Acquisition of Model-Based Behavior 12. The Role of the Orbitofrontal Cortex in Reinforcement Learning and Goal-Directed Decision Making

Applications 13. The Development of Goal-Directed Decision Making 14. Social Behavior 15. Goal-Directed Deficits in Psychosis 16. Goal-Directed Action in Disorders of Compulsivity 17. Drug Addiction: Augmented Habit Learning or Failure of Goal-Directed Control? 18. Alpha-Go

Open Questions 19. Realigning Models of Habitual and Goal-Directed Decision Making 20. Motivations of Action and Reward

Authors

Richard W. Morris Senior Postdoctoral Fellow, University of New South Wales, Australia. Dr Richard W. Morris has studied learning and decision-making in multiple species, including rodents, monkeys and humans. He has distinguished novel computational mechanisms in the brain during goal-directed learning in humans and revealed a novel source of goal-directed deficits in psychosis. He completed his PhD in Psychology at the University of New South Wales, and since then his work has been supported by NARSAD, the Australian NHMRC and the Schizophrenia Research Institute. His research has been featured in top ranked journals including Molecular Psychiatry and Nature Communications, as well as numerous mainstream media, including Australia's national broadcaster (ABC Science), ScienceDaily, and Motherboard Vice. Aaron Bornstein Postdoctoral Research Associate, Princeton Neuroscience Institute, Princeton University, USA. Dr Aaron M. Bornstein was trained in mathematics and computer science before obtaining his PhD in Cognition & Perception from New York University. His work has helped us understand how decision-making can be understood in computational terms, merging ideas from computational reinforcement learning with the rich understanding of learning and memory systems in the brain to investigate multiple forms of goal-directed choice. Beginning at NYU and continuing into his current position at the Princeton Neuroscience Institute, he has distinguished important cortical and subcortical contributions to learning and decision-making and his reviews have helped forge a rapprochement across the disparate fields of psychology, neuroscience and computer science. Amitai Shenhav Assistant Professor, Department of Cognitive, Linguistic and Psychological Sciences, Brown University. Amitai Shenhav earned a B.A. in Cognitive Science from UC Berkeley in 2005 and a Ph.D. in Psychology from Harvard University in 2012. After completing his graduate work, he was a C.V. Starr Postdoctoral Fellow at Princeton University before arriving at Brown. His research investigates neural and computational mechanisms at the intersection of decision-making and cognitive control.