Dynamic cholinergic signaling differentially desynchronizes cortical microcircuits dependent on modulation rate and network topology
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Acetylcholine (ACh) affects both the intrinsic properties of individual neurons and the oscillatory tendencies of neuronal microcircuits by modulating the muscarinic-receptor gated m-current. However, despite contemporary experimental evidence of ACh concentrations changing at millisecond timescales, computational studies traditionally model ACh solely as a tonic neuromodulator. How time-varying, dynamic cholinergic modulation of the m-current affects the dynamics of neuronal microcircuits therefore remains an open question. Using a new implementation of a time-varying cholinergic signal in computational excitatory-inhibitory (E-I) spiking neuronal networks, we here delineate how the interaction between dynamic cholinergic modulation and network topology influences the oscillatory tendencies of these systems. While the dynamics of networks with dominant inter-connectivity (strong E-to-I and I-to-E synaptic weights) are minimally affected, networks with dominant intra-connectivity (strong E-to-E and I-to-I synaptic weights) exhibit dynamics heavily dependent upon dynamic cholinergic signaling. Further investigation of these latter type of networks reveals that their firing patterns are sensitive to the timecourse of cholinergic modulation and that relatively minor changes to the E-I connectivity strength promote distinct desynchronization mechanisms. Our results indicate that network topology plays a paramount role in dictating the modulatory effects of time-varying cholinergic signals, a finding of broad relevance to our understanding of cholinergic modulation and potentially impactful in the design of neurostimulation therapies believed to act through cholinergic pathways.
Author summary
Acetylcholine (ACh) is a chemical messenger that alters the intrinsic properties of neurons and in turn regulates brain activity related to cognitive functions such as sensory processing, memory formation, and attention. Although mounting experimental evidence shows that ACh concentrations in the brain can change dynamically at rapid timescales, computational studies conventionally consider ACh concentrations as constant across time. This motivated us to create a computational model of a neuronal microcircuit in which cellular properties are affected by ACh concentrations varying at millisecond-level timescales. The oscillatory dynamics of this microcircuit differ in important ways from similar systems with constant ACh levels, with the influence of dynamically changing ACh critically dependent upon the connectivity of the neurons in the modeled brain region. These results describe novel mechanisms by which ACh controls microcircuit activity overlooked in existing models in which ACh varies only over long timescales, an understanding which may be vital for the refinement of neurostimulation therapies believed to act through transient alterations to ACh activity.
