Abstract

Visual processing transforms the complexities of the visual world into useful information. Ciona, an invertebrate chordate and close relative of the vertebrates, has one of the simplest nervous systems known, yet has a range of visuomotor behaviors. This simplicity has facilitated studies linking behavior and neural circuitry. Ciona larvae have two distinct visuomotor behaviors – a looming shadow response and negative phototaxis. These are mediated by separate neural circuits that initiate from different clusters of photoreceptors, with both projecting to a CNS structure called the posterior brain vesicle (pBV). We report here that inputs from both circuits are processed to generate fold change detection (FCD) outputs. In FCD, the behavioral response scales with the relative fold change in input, but is invariant to the overall magnitude of the stimulus. Moreover, the two visuomotor behaviors have fundamentally different stimulus/response relationships – indicative of differing circuit strategies, with the looming shadow response showing a power relationship to fold change, while the navigation behavior responds linearly. Pharmacological modulation of the FCD response points to the FCD circuits lying outside of the visual organ (the ocellus), with the pBV being the most likely location. Consistent with these observations, the connectivity and properties of pBV interneurons conform to known FCD circuit motifs, but with different circuit architectures for the two circuits. The negative phototaxis circuit forms a putative incoherent feedforward loop that involves interconnecting cholinergic and GABAergic interneurons. The looming shadow circuit uses the same cholinergic and GABAergic interneurons, but with different synaptic inputs to create a putative non-linear integral feedback loop. These differing circuit architectures are consistent with the behavioral outputs of the two circuits. Finally, while some reports have highlighted parallels between the pBV and the vertebrate midbrain, suggesting a common origin for the two, others reports have disputed this, suggesting that invertebrate chordates lack a midbrain homolog. The convergence of visual inputs at the pBV, and its putative role in visual processing reported here and in previous publications, lends further support to the proposed common origin of the pBV and the vertebrate midbrain.

Highlights

  • The ascidian Ciona has served as a valuable model organism both because of its close evolutionary relationship to the vertebrates, and because of its genetic, embryonic, and anatomical simplicity (Satoh, 1994, 2014; Lemaire et al, 2008)

  • We have reported that Ciona larvae are able to successfully navigate in a wide range of ambient lighting conditions (Salas et al, 2018), the phototaxis assay would not permit precise control of the amount of light the PR-I photoreceptors were receiving, making it difficult to assess their responses to fold change (FC) stimuli

  • By in situ hybridization analysis we confirmed expression in the posterior brain vesicle (pBV) (Figure 4E, left panel), as well as two groups of the neurons in the motor ganglion (MG) that we have tentatively identified as ddNs and motor ganglion interneurons (MGINs) based on their locations to each other and the AMG cells

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Summary

Introduction

The ascidian Ciona has served as a valuable model organism both because of its close evolutionary relationship to the vertebrates, and because of its genetic, embryonic, and anatomical simplicity (Satoh, 1994, 2014; Lemaire et al, 2008). In common with staged vertebrates, the Ciona larva features a notochord running the length of its muscular tail and a dorsal central nervous system (CNS) with a central ventricle. Despite this conserved chordate anatomy, Ciona larval organs are composed of very few cells: 40 notochord cells, 36 tail muscle cells, and ∼180 neurons in the CNS (Nicol and Meinertzhagen, 1991; Satoh, 1994). The simplicity of the Ciona larval CNS has facilitated the generation of a complete synaptic connectome by serial-section electron microscopy (Ryan et al, 2016)

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