Cortical gamma-band resonance preferentially transmits coherent input.

Christopher Murphy Lewis,Pascal Fries,Ilka Diester,Thomas Wunderle,Jianguang Ni,Andreea Lazar,Patrick Jendritza

doi:10.1016/j.celrep.2021.109083

Abstract

SUMMARYSynchronization has been implicated in neuronal communication, but causal evidence remains indirect. We use optogenetics to generate depolarizing currents in pyramidal neurons of the cat visual cortex, emulating excitatory synaptic inputs under precise temporal control, while measuring spike output. The cortex transforms constant excitation into strong gamma-band synchronization, revealing the well-known cortical resonance. Increasing excitation with ramps increases the strength and frequency of synchronization. Slow, symmetric excitation profiles reveal hysteresis of power and frequency. White-noise input sequences enable causal analysis of network transmission, establishing that the cortical gamma-band resonance preferentially transmits coherent input components. Models composed of recurrently coupled excitatory and inhibitory units uncover a crucial role of feedback inhibition and suggest that hysteresis can arise through spike-frequency adaptation. The presented approach provides a powerful means to investigate the resonance properties of local circuits and probe how these properties transform input and shape transmission.

Highlights

The brain’s computational abilities arise from communication within and between neuronal groups, and the dynamic modulation of neuronal communication is believed to enable flexible behavior (Engel et al, 2001; Fries, 2015; Varela et al, 2001)
Synchronization has been implicated in neuronal communication, but causal evidence remains indirect
Models composed of recurrently coupled excitatory and inhibitory units uncover a crucial role of feedback inhibition and suggest that hysteresis can arise through spike-frequency adaptation

Summary

Introduction

The brain’s computational abilities arise from communication within and between neuronal groups, and the dynamic modulation of neuronal communication is believed to enable flexible behavior (Engel et al, 2001; Fries, 2015; Varela et al, 2001). A compelling means to modulate neuronal communication is synchronization (Akam and Kullmann, 2010; Azouz and Gray, 2003; Borgers and Kopell, 2008; Hahn et al, 2014; Palmigiano et al, 2017; Salinas and Sejnowski, 2001; Wang, 2010). Neuronal synchronization is determined by cellular and network properties that define intrinsic timescales for activity. The intrinsic timescale of cells and circuits can be characterized by resonance, i.e., how inputs are amplified, or preferentially transmitted. Interactions between recurrently coupled excitatory and inhibitory (E-I) neurons generate resonances based on connectivity (Borgers and Kopell, 2003; Buzsaki and Wang, 2012; Tiesinga and Sejnowski, 2009; Whittington and Traub, 2003)

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Conclusion