Abstract
Acetylcholine (ACh), one of the brain’s most potent neuromodulators, can affect intrinsic neuron properties through blockade of an M-type potassium current. The effect of ACh on excitatory and inhibitory cells with this potassium channel modulates their membrane excitability, which in turn affects their tendency to synchronize in networks. Here, we study the resulting changes in dynamics in networks with inter-connected excitatory and inhibitory populations (E–I networks), which are ubiquitous in the brain. Utilizing biophysical models of E–I networks, we analyze how the network connectivity structure in terms of synaptic connectivity alters the influence of ACh on the generation of synchronous excitatory bursting. We investigate networks containing all combinations of excitatory and inhibitory cells with high (Type I properties) or low (Type II properties) modulatory tone. To vary network connectivity structure, we focus on the effects of the strengths of inter-connections between excitatory and inhibitory cells (E–I synapses and I–E synapses), and the strengths of intra-connections among excitatory cells (E–E synapses) and among inhibitory cells (I-I synapses). We show that the presence of ACh may or may not affect the generation of network synchrony depending on the network connectivity. Specifically, strong network inter-connectivity induces synchronous excitatory bursting regardless of the cellular propensity for synchronization, which aligns with predictions of the PING model. However, when a network’s intra-connectivity dominates its inter-connectivity, the propensity for synchrony of either inhibitory or excitatory cells can determine the generation of network-wide bursting.
Highlights
Neuromodulation of brain networks occurs via multiple pathways
Given the paramount effect cholinergic modulation has on intrinsic cellular properties and a neuron’s tendency to exhibit synchrony, here we investigate its influence on the synchronous dynamics of networks of inter-connected excitatory and inhibitory neurons (E–I networks), as such networks are ubiquitous in the brain (Brea et al 2009; Kopell et al 2010; Best et al 2007)
To vary network connectivity structure, we focus on the effects of the strengths of interconnections between excitatory and inhibitory cells (E–I synapses and I–E synapses), and the strengths of intra-connections among excitatory cells (E–E synapses) and among inhibitory cells (I–I synapses)
Summary
Neuromodulation of brain networks occurs via multiple pathways. The different types of modulators can wield powerful effects on neural network dynamics, as they can change intrinsic firing properties of neurons as well as alter their effective synaptic strengths. ACh affects intrinsic neuronal properties as well as synaptic transmission through two major pathways: nicotinic and muscarinic receptors. ACh blocks the slow, potassium-mediated M-type ionic current via muscarinic channels, which has a threefold effect on cellular properties: (1) altering the current–frequency (I–F) curve, to increase excitability, (2) increasing spike frequency adaptation (SFA) and 3) altering neuronal phase response curves (PRCs) (Aton et al 2013; Ruivo et al 2013; Ermentrout et al 2001; Stiefel et al 2008). In cortical and hippocampal networks, excitatory pyramidal cells and some types of inhibitory interneurons can contain the M-type potassium current and are targets for these effects of ACh (Stiefel et al 2008; Saraga et al 2003; Lawrence et al 2006; Perrenoud et al 2013; Markram et al 2004)
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