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Three-dimensional neurophenotyping of adult zebrafish behavior.

Cachat J, Stewart A, Utterback E, Hart P, Gaikwad S, Wong K, Kyzar E, Wu N, Kalueff AV - PLoS ONE (2011)

Bottom Line: The present large-scale study applied the newest video-tracking and data-mining technologies to further examine zebrafish anxiety-like phenotypes.It also enables rapid optimization of video tracking settings to improve quantification of automated parameters, and suggests that spatiotemporal organization of zebrafish swimming activity can be affected by various experimental manipulations in a manner predicted by their anxiolytic or anxiogenic nature.Our approach markedly enhances the power of zebrafish behavioral analyses, providing innovative framework for high-throughput 3D phenotyping of adult zebrafish behavior.

View Article: PubMed Central - PubMed

Affiliation: Department of Pharmacology and Neuroscience Program, Tulane Neurophenotyping Platform and Zebrafish Neuroscience Research Consortium, Tulane University Medical School, New Orleans, Louisiana, United States of America.

ABSTRACT
The use of adult zebrafish (Danio rerio) in neurobehavioral research is rapidly expanding. The present large-scale study applied the newest video-tracking and data-mining technologies to further examine zebrafish anxiety-like phenotypes. Here, we generated temporal and spatial three-dimensional (3D) reconstructions of zebrafish locomotion, globally assessed behavioral profiles evoked by several anxiogenic and anxiolytic manipulations, mapped individual endpoints to 3D reconstructions, and performed cluster analysis to reconfirm behavioral correlates of high- and low-anxiety states. The application of 3D swim path reconstructions consolidates behavioral data (while increasing data density) and provides a novel way to examine and represent zebrafish behavior. It also enables rapid optimization of video tracking settings to improve quantification of automated parameters, and suggests that spatiotemporal organization of zebrafish swimming activity can be affected by various experimental manipulations in a manner predicted by their anxiolytic or anxiogenic nature. Our approach markedly enhances the power of zebrafish behavioral analyses, providing innovative framework for high-throughput 3D phenotyping of adult zebrafish behavior.

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Macro- and micro-level behavioral analysis with three-dimensional (3D) spatial reconstruction of swim path.The reconstructed swim path presented here as an example was obtained from a naïve, wild-type control zebrafish tested in a standard novel tank test for 6 min (see Fig. 6 for more examples). Wild-type fish can be considered “mild anxiety”, compared to both anxiolytic (low anxiety) and anxiogenic (high anxiety) cohorts listed in Fig. 3. Although this fish spent a majority of the trial within the bottom half of the tank, the animal also made large sweeping transitions into the upper half. A detailed spatial dissection of 3D locomotion here revealed that (like temporal 3D reconstructions in Fig. 4) manually scored erratic movement events generally overlap with periods of elevated velocity, rapid movement, high angular velocity, high mobility and sharp turn angles, identified by the computer analysis. For better visuality, the observed endpoints were color-coded, with the legend color scales representing proportional spectrum across min/max ranges of observed experimental values. Overall, this approach strongly supports the utility of 3D-based computer-aided analyses of zebrafish behavior, and for the first time creates 3D reconstructions of zebrafish natural exploratory locomotion, mapping anxiety-related behaviors to these traces. The striking overlap between observer- and computer-generated indices in “real” 3D traces open opportunities for further refinement of video-tracking, eventually leading to fully automated 3D-based neurophenotyping tools to quantify zebrafish anxiety. This method of multidimensional phenotyping of zebrafish locomotion can complement temporal 3D reconstructions (as shown in Fig. 4 and 5).
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pone-0017597-g005: Macro- and micro-level behavioral analysis with three-dimensional (3D) spatial reconstruction of swim path.The reconstructed swim path presented here as an example was obtained from a naïve, wild-type control zebrafish tested in a standard novel tank test for 6 min (see Fig. 6 for more examples). Wild-type fish can be considered “mild anxiety”, compared to both anxiolytic (low anxiety) and anxiogenic (high anxiety) cohorts listed in Fig. 3. Although this fish spent a majority of the trial within the bottom half of the tank, the animal also made large sweeping transitions into the upper half. A detailed spatial dissection of 3D locomotion here revealed that (like temporal 3D reconstructions in Fig. 4) manually scored erratic movement events generally overlap with periods of elevated velocity, rapid movement, high angular velocity, high mobility and sharp turn angles, identified by the computer analysis. For better visuality, the observed endpoints were color-coded, with the legend color scales representing proportional spectrum across min/max ranges of observed experimental values. Overall, this approach strongly supports the utility of 3D-based computer-aided analyses of zebrafish behavior, and for the first time creates 3D reconstructions of zebrafish natural exploratory locomotion, mapping anxiety-related behaviors to these traces. The striking overlap between observer- and computer-generated indices in “real” 3D traces open opportunities for further refinement of video-tracking, eventually leading to fully automated 3D-based neurophenotyping tools to quantify zebrafish anxiety. This method of multidimensional phenotyping of zebrafish locomotion can complement temporal 3D reconstructions (as shown in Fig. 4 and 5).

Mentions: Temporal three-dimensional (3D) reconstructions plotted X,Y-coordinates (exported from EthoVision XT7 video-tracking software) on respective X,Y-axes, with experimental time plotted across the Z-axis (see Fig. 4 for an example). Spatial 3D reconstructions were generated in a similar fashion, with spatial coordinates from a top-view recording plotted on the Z-axis (see Fig. 5 for an example). Arrows indicate swimming activity patterns of interest; note the overall similarity of behavioral dynamics across two different novel tanks. Track color reflects changes in velocity (m/s), moving from dark to light (i.e., from blue to green, yellow and red) as velocity increases. Zebrafish placed in standard (small) or large novel tank displayed similar exploratory behavior dynamics (also see transitions to top as an example). Two-way ANOVA (factors: tank type; test time) revealed no tank type effect across all manual endpoints, but a significant time effect with transitions to and time spent in the upper half, increasing and freezing bouts and duration decreasing over time (F(1,5) = 2.1-9.3, p<0.05; ***p<0.01, post-hoc test vs. the respective min 1). This figure serves two purposes. First, it illustrates that the approach presented here can be applied to novel tanks of various shapes and sizes. Additionally, it validates the small novel tank test as a paradigm suitable for standardized phenotyping of zebrafish anxiety-like behavior.


Three-dimensional neurophenotyping of adult zebrafish behavior.

Cachat J, Stewart A, Utterback E, Hart P, Gaikwad S, Wong K, Kyzar E, Wu N, Kalueff AV - PLoS ONE (2011)

Macro- and micro-level behavioral analysis with three-dimensional (3D) spatial reconstruction of swim path.The reconstructed swim path presented here as an example was obtained from a naïve, wild-type control zebrafish tested in a standard novel tank test for 6 min (see Fig. 6 for more examples). Wild-type fish can be considered “mild anxiety”, compared to both anxiolytic (low anxiety) and anxiogenic (high anxiety) cohorts listed in Fig. 3. Although this fish spent a majority of the trial within the bottom half of the tank, the animal also made large sweeping transitions into the upper half. A detailed spatial dissection of 3D locomotion here revealed that (like temporal 3D reconstructions in Fig. 4) manually scored erratic movement events generally overlap with periods of elevated velocity, rapid movement, high angular velocity, high mobility and sharp turn angles, identified by the computer analysis. For better visuality, the observed endpoints were color-coded, with the legend color scales representing proportional spectrum across min/max ranges of observed experimental values. Overall, this approach strongly supports the utility of 3D-based computer-aided analyses of zebrafish behavior, and for the first time creates 3D reconstructions of zebrafish natural exploratory locomotion, mapping anxiety-related behaviors to these traces. The striking overlap between observer- and computer-generated indices in “real” 3D traces open opportunities for further refinement of video-tracking, eventually leading to fully automated 3D-based neurophenotyping tools to quantify zebrafish anxiety. This method of multidimensional phenotyping of zebrafish locomotion can complement temporal 3D reconstructions (as shown in Fig. 4 and 5).
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3049776&req=5

pone-0017597-g005: Macro- and micro-level behavioral analysis with three-dimensional (3D) spatial reconstruction of swim path.The reconstructed swim path presented here as an example was obtained from a naïve, wild-type control zebrafish tested in a standard novel tank test for 6 min (see Fig. 6 for more examples). Wild-type fish can be considered “mild anxiety”, compared to both anxiolytic (low anxiety) and anxiogenic (high anxiety) cohorts listed in Fig. 3. Although this fish spent a majority of the trial within the bottom half of the tank, the animal also made large sweeping transitions into the upper half. A detailed spatial dissection of 3D locomotion here revealed that (like temporal 3D reconstructions in Fig. 4) manually scored erratic movement events generally overlap with periods of elevated velocity, rapid movement, high angular velocity, high mobility and sharp turn angles, identified by the computer analysis. For better visuality, the observed endpoints were color-coded, with the legend color scales representing proportional spectrum across min/max ranges of observed experimental values. Overall, this approach strongly supports the utility of 3D-based computer-aided analyses of zebrafish behavior, and for the first time creates 3D reconstructions of zebrafish natural exploratory locomotion, mapping anxiety-related behaviors to these traces. The striking overlap between observer- and computer-generated indices in “real” 3D traces open opportunities for further refinement of video-tracking, eventually leading to fully automated 3D-based neurophenotyping tools to quantify zebrafish anxiety. This method of multidimensional phenotyping of zebrafish locomotion can complement temporal 3D reconstructions (as shown in Fig. 4 and 5).
Mentions: Temporal three-dimensional (3D) reconstructions plotted X,Y-coordinates (exported from EthoVision XT7 video-tracking software) on respective X,Y-axes, with experimental time plotted across the Z-axis (see Fig. 4 for an example). Spatial 3D reconstructions were generated in a similar fashion, with spatial coordinates from a top-view recording plotted on the Z-axis (see Fig. 5 for an example). Arrows indicate swimming activity patterns of interest; note the overall similarity of behavioral dynamics across two different novel tanks. Track color reflects changes in velocity (m/s), moving from dark to light (i.e., from blue to green, yellow and red) as velocity increases. Zebrafish placed in standard (small) or large novel tank displayed similar exploratory behavior dynamics (also see transitions to top as an example). Two-way ANOVA (factors: tank type; test time) revealed no tank type effect across all manual endpoints, but a significant time effect with transitions to and time spent in the upper half, increasing and freezing bouts and duration decreasing over time (F(1,5) = 2.1-9.3, p<0.05; ***p<0.01, post-hoc test vs. the respective min 1). This figure serves two purposes. First, it illustrates that the approach presented here can be applied to novel tanks of various shapes and sizes. Additionally, it validates the small novel tank test as a paradigm suitable for standardized phenotyping of zebrafish anxiety-like behavior.

Bottom Line: The present large-scale study applied the newest video-tracking and data-mining technologies to further examine zebrafish anxiety-like phenotypes.It also enables rapid optimization of video tracking settings to improve quantification of automated parameters, and suggests that spatiotemporal organization of zebrafish swimming activity can be affected by various experimental manipulations in a manner predicted by their anxiolytic or anxiogenic nature.Our approach markedly enhances the power of zebrafish behavioral analyses, providing innovative framework for high-throughput 3D phenotyping of adult zebrafish behavior.

View Article: PubMed Central - PubMed

Affiliation: Department of Pharmacology and Neuroscience Program, Tulane Neurophenotyping Platform and Zebrafish Neuroscience Research Consortium, Tulane University Medical School, New Orleans, Louisiana, United States of America.

ABSTRACT
The use of adult zebrafish (Danio rerio) in neurobehavioral research is rapidly expanding. The present large-scale study applied the newest video-tracking and data-mining technologies to further examine zebrafish anxiety-like phenotypes. Here, we generated temporal and spatial three-dimensional (3D) reconstructions of zebrafish locomotion, globally assessed behavioral profiles evoked by several anxiogenic and anxiolytic manipulations, mapped individual endpoints to 3D reconstructions, and performed cluster analysis to reconfirm behavioral correlates of high- and low-anxiety states. The application of 3D swim path reconstructions consolidates behavioral data (while increasing data density) and provides a novel way to examine and represent zebrafish behavior. It also enables rapid optimization of video tracking settings to improve quantification of automated parameters, and suggests that spatiotemporal organization of zebrafish swimming activity can be affected by various experimental manipulations in a manner predicted by their anxiolytic or anxiogenic nature. Our approach markedly enhances the power of zebrafish behavioral analyses, providing innovative framework for high-throughput 3D phenotyping of adult zebrafish behavior.

Show MeSH