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Control of Excitatory Hierarchical Circuits by Parvalbumin-FS Basket Cells in Layer 5 of the Frontal Cortex: Insights for Cortical Oscillations

Overview
Journal J Neurophysiol
Specialties Neurology
Physiology
Date 2019 Apr 18
PMID 30995139
Citations 11
Authors
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Abstract

The cortex contains multiple neuron types with specific connectivity and functions. Recent progress has provided a better understanding of the interactions of these neuron types as well as their output organization particularly for the frontal cortex, with implications for the circuit mechanisms underlying cortical oscillations that have cognitive functions. Layer 5 pyramidal cells (PCs) in the frontal cortex comprise two major subtypes: crossed-corticostriatal (CCS) and corticopontine (CPn) cells. Functionally, CCS and CPn cells exhibit similar phase-dependent firing during gamma waves but participate in two distinct subnetworks that are linked unidirectionally from CCS to CPn cells. GABAergic parvalbumin-expressing fast-spiking (PV-FS) cells, necessary for gamma oscillation, innervate PCs, with stronger and global inhibition to somata and weaker and localized inhibitions to dendritic shafts/spines. While PV-FS cells form reciprocal connections with both CCS and CPn cells, the excitation from CPn to PV-FS cells exhibits short-term synaptic dynamics conducive for oscillation induction. The electrical coupling between PV-FS cells facilitates spike synchronization among PV-FS cells receiving common excitatory inputs from local PCs and inhibits other PV-FS cells via electrically communicated spike afterhyperpolarizations. These connectivity characteristics can promote synchronous firing in the local networks of CPn cells and firing of some CCS cells by anode-break excitation. Thus subsets of L5 CCS and CPn cells within different levels of connection hierarchy exhibit coordinated activity via their common connections with PV-FS cells, and the resulting PC output drives diverse neuronal targets in cortical layer 1 and the striatum with specific temporal precision, expanding the computational power of the cortical network.

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