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PLoS One
2013 May 07;85:e62846. doi: 10.1371/journal.pone.0062846.
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Monitoring of single-cell responses in the optic tectum of adult zebrafish with dextran-coupled calcium dyes delivered via local electroporation.
Kassing V
,
Engelmann J
,
Kurtz R
.
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The zebrafish (Danio rerio) has become one of the major animal models for in vivo examination of sensory and neuronal computation. Similar to Xenopus tadpoles neural activity in the optic tectum, the major region controlling visually guided behavior, can be examined in zebrafish larvae by optical imaging. Prerequisites of these approaches are usually the transparency of larvae up to a certain age and the use of two-photon microscopy. This principle of fluorescence excitation was necessary to suppress crosstalk between signals from individual neurons, which is a critical issue when using membrane-permeant dyes. This makes the equipment to study neuronal processing costly and limits the approach to the study of larvae. Thus there is lack of knowledge about the properties of neurons in the optic tectum of adult animals. We established a procedure to circumvent these problems, enabling in vivo calcium imaging in the optic tectum of adult zebrafish. Following local application of dextran-coupled dyes single-neuron activity of adult zebrafish can be monitored with conventional widefield microscopy, because dye labeling remains restricted to tens of neurons or less. Among the neurons characterized with our technique we found neurons that were selective for a certain pattern orientation as well as neurons that responded in a direction-selective way to visual motion. These findings are consistent with previous studies and indicate that the functional integrity of neuronal circuits in the optic tectum of adult zebrafish is preserved with our staining technique. Overall, our protocol for in vivo calcium imaging provides a useful approach to monitor visual responses of individual neurons in the optic tectum of adult zebrafish even when only widefield microscopy is available. This approach will help to obtain valuable insight into the principles of visual computation in adult vertebrates and thus complement previous work on developing visual circuits.
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23667529
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Figure 2. Morphology of neurons in the optic tectum of adult zebrafish.A. Image of the head of an adult zebrafish following exposure of the lefttectum opticum. A schematic drawing of the brain is superimposed on the image of the head of a zebrafish. The region exposed for imaging is marked as the region of interest (ROI). B. Schematic transversal section through the tectum opticum (redrawn after [30]) showing the input layer and the overall cytoarchitecture of some prominent neurons. Areas highlighted in colour indicate where photomicrographs of labelled cells shown in D1–D2 are located. C. Schematic three-dimensional view on the tectum. The ROI is highlighted in yellow, while the tectal areas are indicated in blue (BioVis3D). D1–D2. Photomicrographs of stained cells. D1 shows an example of a top view using the in vivo imaging set-up (widefield fluorescence). D2 is an example of a neuron recovered after the in vivo experiments following routine histological methods. Here a confocal stack of the vibratome sectioned tectum was used to reconstruct the 3D properties of this neuron (BioVis3D). Abbreviations: SM Stratum moleculare; SO Stratum opticum; SFGS Stratum griseum et album superficial; SGC Stratum griseum central; SAC Stratum album central; SPV Stratum periventriculare; OBOlfactory bulb; Tel Telencephalon; TeO Tectum opticum; CCe Corpus Cerebellare; EG Eminentia granularis; MO Medulla oblongata.
Figure 3. Recording of somatic calcium signals in the optic tectum of adult zebrafish.A. Top view on the exposed tectum, showing several somata (yellow arrow) and some dendrites (green arrows). Note that not all aspects of the labelled neurons are in focus, since this is the view based on the experimental focus on the soma indicated by the white dotted square (ex2). Another soma, depicted by the yellow dotted square (ex1), yielded the calcium responses shown in panel B. B. Example of the responses to the preferred (45°, red trace) and a non-preferred (180°, blue trace) motion direction of the soma shown in A (ex1, yellow dotted square). Pink and light blue traces show the single repetitions (4 per direction) and the red and dark blue traces show the mean. Single colour-coded images showing the time course of the fluorescence change are depicted at the times indicated by the grey arrows. The first image shows the fluorescence before the pattern starts to move. Every following picture shows the fluorescence in steps of 20 frames. Stimuli lasted four seconds and the stimulus start and end are depicted by the striped pattern below the images. The time courses show the relative fluorescence changes (ΔF/F0) averaged over the pixels within a rectangular ROI (indicated as black square in the first image of each series). Baseline fluorescence (F0) was determined by averaging across the first 5–20 recorded frames of the series.
Figure 4. Responses of tectal neurons to three different types of visual stimuli.A1. Mean responses (n = 3) to grating motion (red), motion of a random dot pattern (blue) and counterphase flicker of the grating (black) of the neuron shown in Figure 3 (ex1) in eight different directions (0°–315°). A2. Polar plots for the three different types of visual stimuli shown in A1. The plot shows the mean amplitude of the responses with the shaded areas indicating one standard deviation. The neuron had a clear and significant directional tuning for both, the moving random dot pattern (blue) and the moving grating (red), but was unselective for the orientation of the flicker stimulus. Throughout the figure, responses to grating motion are shown in red, responses to motion of the random dot pattern are shown in blue, and responses to counter-phase flicker are indicated in black. Note that for uniformity with the motion stimuli each of the four different flicker conditions is represented by pairs of opposite “directions”, e.g. 0° and 180° both denote flicker of a grating with vertically oriented bars (compare Figure 1C). B. Example from a second neuron in the same preparation (see white square in Figure 3A, ex2). As in A1–A2, this cell was directionally selective but with a different preferred direction (290°) and was non-selective for the orientation of the flicker stimulus.
Figure 5. Example of an orientation-selective neuron.A. The polar plot in A shows the mean response (black dots) in response to the moving gratings (n = 3) with the standard deviation being shown by the grey shaded area. The neuron was selective for motion in almost horizontal directions (e.g., moving gratings with vertically oriented stripes). The red dotted ellipse shows the fit to the raw data with the major and minor axis of the ellipse depicted by the red and green line. Note that the centre of the ellipse (red dot) is only shifted slightly off origin (black dot), which indicates very weak direction selectivity at most. In contrast, the major and minor axes differ markedly in their length, indicating a strong orientation preference of this cell. Direction selectivity was quantified by the DSI, defined as the metric distance of the centre of the ellipse from the centre of the coordinate system, relative to the radius of the major axis of the ellipse (see Methods and inset in C). Orientation selectivity was quantified by the OSI = 1−(minor axis/major axis) (see A and inset in B). B, C. A Monte-Carlo approach was applied to test the robustness of the calculated OSI and DSI values. In each case the distribution of the indices obtained for 10.000 repetitions is shown, with the experimentally determined OSI and DSI values being superimposed by solid lines. Note that orientation preference was highly significant, whereas no directional preference was present. Rayleigh statistics confirmed the lack of directionality tuning of this neuron.
Figure 6. Summary plot of direction and orientation preferences.The blue, solid lines with arrowheads indicate the preferred direction of motion of the significantly direction-selective neurons relative to the fish’s body axis. The red, broken lines with arrowheads at both ends indicate the preferred axes of motion of the significantly orientation-selective neurons. Note that the corresponding stripe orientation of the grating is in all cases perpendicular to these axes (see inset at 45°).
Figure 7. Superficial dendritic structures are accessible and yield consistent Ca2+ signals.A. Mean raw fluorescence image showing a somatic ROIs (yellow) and a dendritic ROIs (red). The mean orientation vectors obtained at each ROI (sizing 12×12 pixels) are shown centred on the ROIs. B–C. Responses to the eight different pattern directions are shown for somatic (B) and dendritic (C) signals. Black arrows represent the normalized response strength for the individual grating orientations. For a given ROI the maximal amplitude was used to normalize the vector lengths. The mean vectors (coloured arrows) are superimposed on these data. Mean vectors are normalized to the strongest orientation tuning found in the somata (ROI 1) and the dendrites (ROI d), respectively.
Figure 1. Schematic drawing of the experimental set-up.
A. The animal was placed under a standard upright fixed-stage microscope, equipped with a sensitive electron-multiplying CCD camera and LED-based epifluorescence illumination. To deliver visual stimuli, we used a TFT screen, which was placed in front of the eye facing the experimenter (drawn transparent for clarity). B. Detailed view of the recording chamber. Fish were placed on a styrofoam support tray and held in place by tungsten wires bent to support the animals. The chamber was continuously perfused with Hickmann ringer. C. Schematic display of the grating stimulus used for the determination of orientation and directional selectivity of tectal cells. For all data the denomination of the motion directions corresponds to the one shown here.
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