Circuit Organization Underlying Optic Flow Processing in Zebrafish

Characterizing medaka visual features using a high-throughput optomotor response assay

Medaka fish (Oryzias latipes) is a powerful model to study genetics underlying the developmental and functional traits of the vertebrate visual system. We established a simple and high-throughput optomotor response (OMR) assay utilizing medaka larvae to study visual functions including visual acuity and contrast sensitivity. Our assay presents multiple adjustable stripes in motion to individual fish in a linear arena. For that the OMR assay employs a tablet display and the Fish Stripes software to adjust speed, width, color, and contrast of the stripes. Our results demonstrated that optomotor responses were robustly induced by black and white stripes presented from below in the linear-pool-arena. We detected robust strain specific differences in the OMR when comparing long established medaka inbred strains. We observed an interesting training effect upon the initial exposure of larvae to thick stripes, which allowed them to better respond to narrower stripes. The OMR setup and protocol presented here provide an efficient tool for quantitative phenotype mapping, addressing visual acuity, trainability of cortical neurons, color sensitivity, locomotor response, retinal regeneration and others. Our open-source setup presented here provides a crucial prerequisite for ultimately addressing the genetic basis of those processes.

Multisensory strategies for postural compensation after lateral line loss

To control elevation underwater, aquatic vertebrates integrate multisensory information (e.g., vestibular, visual, proprioceptive) to guide posture and swim kinematics. Here we characterized how larval zebrafish changed posture and locomotive strategies after imposed instability (decreased buoyancy) in the presence and absence of visual cues. We discovered that larvae sank more after acute loss of lateral line (flow-sensing) hair cells. In response, larvae engaged different compensatory strategies, depending on whether they were in the light or dark. In the dark, larvae swam more frequently, engaging their trunk to steer their nose up and climb more effectively. However, in the light, larvae climbed more often, engaging both pectoral fins and trunk to elevate. We conclude that larvae sense instability and use vestibular and visual information as available to control posture and trajectory. Our work is a step towards understanding the multisensory neural computations responsible for control strategies that allow orientation and navigation in depth.

Optic flow in the natural habitats of zebrafish supports spatial biases in visual self-motion estimation

Animals benefit from knowing if and how they are moving. Across the animal kingdom, sensory information in the form of optic flow over the visual field is used to estimate self-motion. However, different species exhibit strong spatial biases in how they use optic flow. Here, we show computationally that noisy natural environments favor visual systems that extract spatially biased samples of optic flow when estimating self-motion. The performance associated with these biases, however, depends on interactions between the environment and the animal's brain and behavior. Using the larval zebrafish as a model, we recorded natural optic flow associated with swimming trajectories in the animal's habitat with an omnidirectional camera mounted on a mechanical arm. An analysis of these flow fields suggests that lateral regions of the lower visual field are most informative about swimming speed. This pattern is consistent with the recent findings that zebrafish optomotor responses are preferentially driven by optic flow in the lateral lower visual field, which we extend with behavioral results from a high-resolution spherical arena. Spatial biases in optic-flow sampling are likely pervasive because they are an effective strategy for determining self-motion in noisy natural environments.

Optic flow in the natural habitats of zebrafish supports spatial biases in visual self-motion estimation

Animals benefit from knowing if and how they are moving. Across the animal kingdom, sensory information in the form of optic flow over the visual field is used to estimate self-motion. However, different species exhibit strong spatial biases in how they use optic flow. Here, we show computationally that noisy natural environments favor visual systems that extract spatially biased samples of optic flow when estimating self-motion. The performance associated with these biases, however, depends on interactions between the environment and the animal's brain and behavior. Using the larval zebrafish as a model, we recorded natural optic flow associated with swimming trajectories in the animal's habitat with an omnidirectional camera mounted on a mechanical arm. An analysis of these flow fields suggests that lateral regions of the lower visual field are most informative about swimming speed. This pattern is consistent with the recent findings that zebrafish optomotor responses are preferentially driven by optic flow in the lateral lower visual field, which we extend with behavioral results from a high-resolution spherical arena. Spatial biases in optic-flow sampling are likely pervasive because they are an effective strategy for determining self-motion in noisy natural environments.

Optic flow in the natural habitats of zebrafish supports spatial biases in visual self-motion estimation

Animals benefit from knowing if and how they are moving. Across the animal kingdom, sensory information in the form of optic flow over the visual field is used to estimate self-motion. However, different species exhibit strong spatial biases in how they use optic flow. Here, we show computationally that noisy natural environments favor visual systems that extract spatially biased samples of optic flow when estimating self-motion. The performance associated with these biases, however, depends on interactions between the environment and the animal's brain and behavior. Using the larval zebrafish as a model, we recorded natural optic flow associated with swimming trajectories in the animal's habitat with an omnidirectional camera mounted on a mechanical arm. An analysis of these flow fields suggests that lateral regions of the lower visual field are most informative about swimming speed. This pattern is consistent with the recent findings that zebrafish optomotor responses are preferentially driven by optic flow in the lateral lower visual field, which we extend with behavioral results from a high-resolution spherical arena. Spatial biases in optic-flow sampling are likely pervasive because they are an effective strategy for determining self-motion in noisy natural environments.

Automated synapse-level reconstruction of neural circuits in the larval zebrafish brain

Dense reconstruction of synaptic connectivity requires high-resolution electron microscopy images of entire brains and tools to efficiently trace neuronal wires across the volume. To generate such a resource, we sectioned and imaged a larval zebrafish brain by serial block-face electron microscopy at a voxel size of 14 × 14 × 25 nm3. We segmented the resulting dataset with the flood-filling network algorithm, automated the detection of chemical synapses and validated the results by comparisons to transmission electron microscopic images and light-microscopic reconstructions. Neurons and their connections are stored in the form of a queryable and expandable digital address book. We reconstructed a network of 208 neurons involved in visual motion processing, most of them located in the pretectum, which had been functionally characterized in the same specimen by two-photon calcium imaging. Moreover, we mapped all 407 presynaptic and postsynaptic partners of two superficial interneurons in the tectum. The resource developed here serves as a foundation for synaptic-resolution circuit analyses in the zebrafish nervous system.

Fourier Motion Processing in the Optic Tectum and Pretectum of the Zebrafish Larva

In the presence of moving visual stimuli, the majority of animals follow the Fourier motion energy (luminance), independently of other stimulus features (edges, contrast, etc.). While the behavioral response to Fourier motion has been studied in the past, how Fourier motion is represented and processed by sensory brain areas remains elusive. Here, we investigated how visual moving stimuli with or without the first Fourier component (square-wave signal or missing fundamental signal) are represented in the main visual regions of the zebrafish brain. First, we monitored the larva's optokinetic response (OKR) induced by square-wave and missing fundamental signals. Then, we used two-photon microscopy and GCaMP6f zebrafish larvae to monitor neuronal circuit dynamics in the optic tectum and the pretectum. We observed that both the optic tectum and the pretectum circuits responded to the square-wave gratings. However, only the pretectum responded specifically to the direction of the missing-fundamental signal. In addition, a group of neurons in the pretectum responded to the direction of the behavioral output (OKR), independently of the type of stimulus presented. Our results suggest that the optic tectum responds to the different features of the stimulus (e.g., contrast, spatial frequency, direction, etc.), but does not respond to the direction of motion if the motion information is not coherent (e.g., the luminance and the edges and contrast in the missing-fundamental signal). On the other hand, the pretectum mainly responds to the motion of the stimulus based on the Fourier energy.