Dec 6, 2017

Efficient encoding of motion is mediated by gap junctions in the fly visual system

PLoS Computational Biology
Siwei WangIdan Segev

Abstract

Understanding the computational implications of specific synaptic connectivity patterns is a fundamental goal in neuroscience. In particular, the computational role of ubiquitous electrical synapses operating via gap junctions remains elusive. In the fly visual system, the cells in the vertical-system network, which play a key role in visual processing, primarily connect to each other via axonal gap junctions. This network therefore provides a unique opportunity to explore the functional role of gap junctions in sensory information processing. Our information theoretical analysis of a realistic VS network model shows that within 10 ms following the onset of the visual input, the presence of axonal gap junctions enables the VS system to efficiently encode the axis of rotation, θ, of the fly's ego motion. This encoding efficiency, measured in bits, is near-optimal with respect to the physical limits of performance determined by the statistical structure of the visual input itself. The VS network is known to be connected to downstream pathways via a subset of triplets of the vertical system cells; we found that because of the axonal gap junctions, the efficiency of this subpopulation in encoding θ is superior to that of the whole ...Continue Reading

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Mentioned in this Paper

Study
Optic Tract Structure
Visual System
Biochemical Pathway
Biological Neural Networks
Neurons
Theoretical Study
Neuronal Circuitry
Synaptic Connectivity
Triplet, Centriole

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