Cortical parvalbumin-expressing interneurons sample network oscillations in their synaptic activity

Area of Science:

• Neuroscience
• Computational Neuroscience
• Cellular Neuroscience

Background:

• Brain oscillations, including delta (δ) to gamma (γ) bands, are crucial for cognitive functions and are typically recorded via electroencephalogram (EEG) and local field potentials (LFPs).
• Parvalbumin-expressing (PV+) neurons are key inhibitory interneurons involved in cortical network synchronization and gamma oscillation generation during cholinergic modulation.
• Cholinergic stimulation, using carbachol (CCh), increases cortical excitability, leading to pyramidal neuron depolarization and firing, while inducing synaptic potentials without firing in most PV+ neurons.

Purpose of the Study:

• To investigate whether synaptic activity in PV+ neurons mirrors the frequency bands observed in cortical network recordings.
• To analyze the spectral content of synaptic events in PV+ neurons under cholinergic stimulation.
• To elucidate the role of inhibitory and excitatory synaptic events in shaping network oscillations within PV+ neurons.

Main Methods:

• Recording synaptic activity in layer 5 PV+ neurons in isolated cortical tissue.
• Applying the muscarinic agonist carbachol (CCh) to enhance cortical excitability.
• Analyzing the frequency spectra and power density of isolated inhibitory and excitatory synaptic events.

Main Results:

• Synaptic events recorded in PV+ neurons exhibited frequency spectra spanning from delta (δ) to gamma (γ) bands, reflecting network oscillations.
• Isolation of inhibitory events revealed increased potency in the δ band and decreased potency in other bands.
• Isolated excitatory events showed a decrease in the β band, suggesting a regulatory role for inhibition and a driving role for excitation.
• Muscarinic M1 receptors were identified as the primary mediators of the synaptic activity generating these oscillatory bands.

Conclusions:

• PV+ interneurons continuously "sample" network activity through incoming synaptic events.
• The frequency spectra of random synaptic events in single neurons contain rich information about the wide range of brain oscillations.
• This study demonstrates that individual inhibitory neurons integrate network-level oscillatory information via their synaptic inputs.