Parvalbumin neurons and cortical coding of dynamic stimuli: a network model

Area of Science:

• Neuroscience
• Computational Neuroscience
• Systems Neuroscience

Background:

• Cortical circuits use excitatory and inhibitory cells for dynamic sensory encoding.
• The precise coordination between these cells for temporal stimulus encoding remains unclear.
• Inhibitory neuron function, specifically parvalbumin neurons, is crucial for neural coding.

Purpose of the Study:

• To mechanistically explain how inhibitory (parvalbumin) neurons contribute to the neural discrimination of dynamic sensory stimuli.
• To investigate the role of distinct stimulus onset and offset inputs to parvalbumin neurons in shaping neural codes.
• To model the impact of parvalbumin neuron activity on cortical encoding performance.

Main Methods:

• Developed a multilayer computational model of a cortical circuit.
• Incorporated experimentally observed responses of parvalbumin neurons to stimulus onsets and offsets.
• Included short-term synaptic plasticity profiles for excitatory and parvalbumin neurons.
• Simulated optogenetic suppression of parvalbumin neurons to assess its effect on neural discrimination.

Main Results:

• The model demonstrated that tuning onset and offset inputs to parvalbumin neurons creates distinct coding regimes (firing rate vs. spike timing).
• Model simulations replicated the experimental finding that parvalbumin neuron suppression reduces neural discriminability.
• Distinct inputs to parvalbumin neurons were shown to enhance temporal coding and reduce cortical noise.

Conclusions:

• Parvalbumin neurons play a critical role in enhancing the cortical discriminability of dynamic sensory stimuli.
• Distinct onset and offset inputs to parvalbumin neurons encode specific temporal features, improving temporal coding.
• The model provides a mechanistic explanation for the observed effects of parvalbumin neuron activity on neural discrimination.