Adapting the flow of time with dopamine

Area of Science:

• Neuroscience
• Computational Neuroscience
• Behavioral Neuroscience

Background:

• Dopamine's (DA) modulation of interval timing is well-established but controversial.
• Pharmacological studies suggest higher DA levels overestimate time, while optogenetics show the opposite.
• DA is also recognized as a reward prediction error (RPE) signal in reinforcement learning.

Purpose of the Study:

• To investigate the relationship between DA's role in reinforcement learning and interval timing.
• To reconcile conflicting observations regarding DA's effects on time perception.
• To develop a unified computational framework for DA's functions in learning and timing.

Main Methods:

• Utilized a reinforcement learning-based approach to model interval timing.
• Derived a biologically plausible, DA-dependent plasticity rule.
• Analyzed effects on timekeeping rate, considering DA signal timing.

Main Results:

• The RPE interpretation of DA naturally extends to its role in timekeeping.
• A derived bidirectional update rule reconciles pharmacological and optogenetic findings.
• The model accounts for behavioral effects of reward rate and temporal selectivity of striatal neurons.

Conclusions:

• A single RPE interpretation of DA unifies its roles in reinforcement learning and interval timing.
• The derived plasticity rule explains DA's bidirectional modulation of time perception.
• This work bridges computational theories of learning and timing.