Neurochemical and Behavioral Dissections of Decision-Making in a Rodent Multistage Task

J Neurosci. 2019 Jan 9;39(2):295-306. doi: 10.1523/JNEUROSCI.2219-18.2018. Epub 2018 Nov 9.

Abstract

Flexible decision-making in dynamic environments requires both retrospective appraisal of reinforced actions and prospective reasoning about the consequences of actions. These complementary reinforcement-learning systems can be characterized computationally with model-free and model-based algorithms, but how these processes interact at a neurobehavioral level in normal and pathological states is unknown. Here, we developed a translationally analogous multistage decision-making (MSDM) task to independently quantify model-free and model-based behavioral mechanisms in rats. We provide the first direct evidence that male rats, similar to humans, use both model-free and model-based learning when making value-based choices in the MSDM task and provide novel analytic approaches for independently quantifying these reinforcement-learning strategies. Furthermore, we report that ex vivo dopamine tone in the ventral striatum and orbitofrontal cortex correlate with model-based, but not model-free, strategies, indicating that the biological mechanisms mediating decision-making in the multistage task are conserved in rats and humans. This new multistage task provides a unique behavioral platform for conducting systems-level analyses of decision-making in normal and pathological states.SIGNIFICANCE STATEMENT Decision-making is influenced by both a retrospective "model-free" system and a prospective "model-based" system in humans, but the biobehavioral mechanisms mediating these learning systems in normal and disease states are unknown. Here, we describe a translationally analogous multistage decision-making task to provide a behavioral platform for conducting neuroscience studies of decision-making in rats. We provide the first evidence that choice behavior in rats is influenced by model-free and model-based systems and demonstrate that model-based, but not model-free, learning is associated with corticostriatal dopamine tone. This novel behavioral paradigm has the potential to yield critical insights into the mechanisms mediating decision-making alterations in mental disorders.

Keywords: computational psychiatry; decision-making; dopamine; model-free and model-based reinforcement learning.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Algorithms
  • Animals
  • Behavior, Animal / physiology*
  • Brain Chemistry / physiology*
  • Conditioning, Operant / physiology
  • Decision Making / physiology*
  • Dopamine / physiology
  • Male
  • Models, Psychological
  • Models, Statistical
  • Prefrontal Cortex / metabolism
  • Prefrontal Cortex / physiology
  • Rats
  • Rats, Long-Evans
  • Ventral Striatum / metabolism
  • Ventral Striatum / physiology

Substances

  • Dopamine