Inhibitory microcircuits for top-down plasticity of sensory representations

Area of Science:

• Computational neuroscience
• Systems neuroscience
• Neuroplasticity

Background:

• Reward processing significantly impacts sensory representation plasticity.
• Inhibitory circuits are implicated in learning and modulated by reward signals.
• The precise role of inhibitory plasticity in reward-driven learning remains unclear.

Purpose of the Study:

• To investigate the role of inhibitory plasticity in reward-mediated adjustments of sensory representations.
• To model the interaction between top-down reward modulation and local plasticity.
• To understand how inhibitory circuits store reward information for long-term changes.

Main Methods:

• Development of a computational model of layer 2/3 primary visual cortex.
• Simulation of interactions between stimulus presentation, reward signals, and neural plasticity.
• Analysis of changes in excitatory and inhibitory connectivity.

Main Results:

• Interneuron circuits can store information about rewarded stimuli.
• Somatostatin-positive interneurons strengthen connections with parvalbumin-positive interneurons during reward.
• This leads to selective disinhibition and subsequent excitatory plasticity, enhancing stimulus representation.
• The model demonstrates translation invariance in learned representations.

Conclusions:

• Inhibitory plasticity, particularly involving somatostatin-positive and parvalbumin-positive interneurons, is crucial for reward-driven learning.
• A two-stage mechanism involving inhibitory circuit memory and subsequent excitatory plasticity underlies long-lasting changes in sensory representations.
• The model provides testable predictions for experimental validation.