Neural signatures of experience-based improvements in deterministic decision-making
| Autor: | Patryk Laurent, Julie A. Fiez, Joshua J. Tremel, Mark E. Wheeler, David A. Wolk |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Adult
Male Decision Making Control (management) Mnemonic Article 050105 experimental psychology Task (project management) Discrimination Learning Young Adult 03 medical and health sciences Behavioral Neuroscience 0302 clinical medicine Feedback Sensory Image Processing Computer-Assisted Reaction Time Humans Reinforcement learning 0501 psychology and cognitive sciences Set (psychology) 05 social sciences Perspective (graphical) Brain Cognition Magnetic Resonance Imaging Oxygen Female Psychology Reinforcement Psychology Social psychology Photic Stimulation 030217 neurology & neurosurgery Cognitive psychology Optimal decision |
| Zdroj: | Behavioural Brain Research. 315:51-65 |
| ISSN: | 0166-4328 |
| DOI: | 10.1016/j.bbr.2016.08.023 |
| Popis: | Feedback about our choices is a crucial part of how we gather information and learn from our environment. It provides key information about decision experiences that can be used to optimize future choices. However, our understanding of the processes through which feedback translates into improved decision-making is lacking. Using neuroimaging (fMRI) and cognitive models of decision-making and learning, we examined the influence of feedback on multiple aspects of decision processes across learning. Subjects learned correct choices to a set of 50 word pairs across eight repetitions of a concurrent discrimination task. Behavioral measures were then analyzed with both a drift-diffusion model and a reinforcement learning model. Parameter values from each were then used as fMRI regressors to identify regions whose activity fluctuates with specific cognitive processes described by the models. The patterns of intersecting neural effects across models support two main inferences about the influence of feedback on decision-making. First, frontal, anterior insular, fusiform, and caudate nucleus regions behave like performance monitors, reflecting errors in performance predictions that signal the need for changes in control over decision-making. Second, temporoparietal, supplementary motor, and putamen regions behave like mnemonic storage sites, reflecting differences in learned item values that inform optimal decision choices. As information about optimal choices is accrued, these neural systems dynamically adjust, likely shifting the burden of decision processing from controlled performance monitoring to bottom-up, stimulus-driven choice selection. Collectively, the results provide a detailed perspective on the fundamental ability to use past experiences to improve future decisions. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect