Abstract
Local interneurons (LNs) in the Drosophila olfactory system exhibit neuronal diversity and variability, yet it is still unknown how these features impact information encoding capacity and reliability in a complex LN network. We employed two strategies to construct a diverse excitatory-inhibitory neural network beginning with a ring network structure and then introduced distinct types of inhibitory interneurons and circuit variability to the simulated network. The continuity of activity within the node ensemble (oscillation pattern) was used as a readout to describe the temporal dynamics of network activity. We found that inhibitory interneurons enhance the encoding capacity by protecting the network from extremely short activation periods when the network wiring complexity is very high. In addition, distinct types of interneurons have differential effects on encoding capacity and reliability. Circuit variability may enhance the encoding reliability, with or without compromising encoding capacity. Therefore, we have described how circuit variability of interneurons may interact with excitatory-inhibitory diversity to enhance the encoding capacity and distinguishability of neural networks. In this work, we evaluate the effects of different types and degrees of connection diversity on a ring model, which may simulate interneuron networks in the Drosophila olfactory system or other biological systems.
Highlights
Animals sense environmental stimuli and initiate appropriate behavioral responses through the action of neural circuits
We first determined the ratio of excitatory local interneurons (LNs) and inhibitory LNs in the antennal lobe (AL)
Limited by current knowledge of neuronal types, numbers, and details of connections among neurons in a given circuit, it is far from clear how neuronal variability works with inhibition to influence encoding capacity and reliability of the circuit
Summary
Animals sense environmental stimuli and initiate appropriate behavioral responses through the action of neural circuits. Mitral cells (the vertebrate analog of fly PNs) exhibit intrinsic heterogeneity, which decorrelates neuronal firing and increases coding capacity[18] These regulatory processes should result in pattern decorrelation[2], but collective variations in subsets of neurons within a circuit have been shown to produce consistent network activity, maintaining encoding reliability[21]. We began by using a ring model as a basic representation of an oscillating isolated LN network (interactions with ORNs and PNs were excluded) With this model, we asked (1) why biological networks might exhibit high levels of diversity, (2) if morphological diversity contributes to the encoding capacity of a network consisting of inhibitory and excitatory neurons, and (3) if so, whether and how circuit variability drives the circuit toward a balance between encoding capacity and reliability. Such mechanisms are likely to be generalizable to interneuron networks in other circuits and other species
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