Beta and High Gamma Oscillations in the Cortico-striatal Network Reflect Reward Certainty on a Probabilistic Reversal...

Area of Science:

• Neuroscience
• Computational Neuroscience
• Behavioral Neuroscience

Background:

• Flexible decision-making relies on adapting to uncertain reward feedback.
• Cortico-striatal circuitry is implicated in decision-making, but its precise role in reward learning is complex.
• Probabilistic reversal learning (PRL) tasks assess the ability to learn and adapt to changing reward contingencies.

Purpose of the Study:

• To investigate the role of cortico-striatal networks in reward feedback during PRL tasks using local field potentials.
• To identify specific oscillatory dynamics associated with reward value and behavioral adaptation.
• To determine how modulating neural activity affects task performance.

Main Methods:

• Recorded local field potentials (32-CH) in male Long-Evans rats during a PRL task.
• Analyzed reward-evoked oscillations at beta (15-30Hz) and high gamma (>70Hz) frequencies.
• Utilized optogenetics to modulate beta activity in the orbitofrontal cortex.
• Employed a reinforcement learning computational model to analyze behavior.

Main Results:

• Reward-evoked beta and high gamma oscillations reflected positive reward valence and probability.
• Beta-frequency activity and connectivity between cortico-striatal regions correlated with behavioral performance.
• Optogenetic stimulation of orbitofrontal cortex at beta frequencies promoted maladaptive behavior during non-target responses.

Conclusions:

• Reward-evoked beta oscillations are a key component of reward learning and adaptive behavior.
• Aberrant beta oscillations may contribute to maladaptive task performance and behavioral disruptions.
• Beta oscillations in the cortico-striatal network represent learned reward value, especially under uncertain conditions.