Non-monotonic effects of GABAergic synaptic inputs on neuronal firing

Abstract

AbstractGABA is canonically known as the principal inhibitory neurotransmitter in the nervous system, usually acting by hyper-polarizing membrane potential. However, GABAergic currents can also exhibit non-inhibitory effects, depending on the brain region, developmental stage or pathological condition. Here, we investigate the diverse effects of GABA on the firing rate of several single neuron models, using both analytical calculations and numerical simulations. We find that the relationship between GABAergic synaptic conductance and output firing rate exhibits three qualitatively different regimes as a function of GABA reversal potential, vGABA: monotonically decreasing for sufficiently low vGABA (inhibitory), monotonically increasing for vGABA above firing threshold (excitatory); and a non-monotonic region for intermediate values of vGABA. In the non-monotonic regime, small GABA conductances have an excitatory effect while large GABA conductances show an inhibitory effect. We provide a phase diagram of different GABAergic effects as a function of GABA reversal potential and glutamate conductance. We find that noisy inputs increase the range of vGABA for which the non-monotonic effect can be observed. We also construct a micro-circuit model of striatum to explain observed effects of GABAergic fast spiking interneurons on spiny projection neurons, including non-monotonicity, as well as the heterogeneity of the effects. Our work provides a mechanistic explanation of paradoxical effects of GABAergic synaptic inputs, with implications for understanding the effects of GABA in neural computation and development.Author summaryNeurons in nervous systems mainly communicate at chemical synapses by releasing neurotransmitters from the presynaptic side that bind to receptors on the postsynaptic side, triggering ion flow through cell membrane and changes in the membrane potential of the postsynaptic neuron. Gamma-aminobutyric acid (GABA) is the principal neurotransmitter expressed by inhibitory neurons. Its binding to GABAergic receptors mainly causes a flow of chloride ions through the membrane, and typically hyperpolarizes the postsynaptic neuron, resulting in firing suppression. While GABA is canonically viewed as an inhibitory neurotransmitter, non-inhibitory effects have been observed in early stages of development, in stress-related disorders, and in specific parts of brain structures [1–4]. Here, we employ analytical and computational approaches on spiking neuronal models to investigate the mechanisms of diverse effects of GABAergic synaptic inputs. We find that in addition to monotonically excitatory or monotonically inhibitory effects, GABAergic inputs show non-monotonic effects, for which the effect depends on the strength of the input. This effect is stronger in the presence of noise, and is observed in different models both at the single cell, and at the network level. Our findings provide a mechanistic explanation of several paradoxical experimental observations, with potential implications in neural network dynamics and computation.