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Controlling airborne cues to study small animal navigation

Nature Methods volume 9, pages 290–296 (2012)Cite this article

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Abstract

Small animals such as nematodes and insects analyze airborne chemical cues to infer the direction of favorable and noxious locations. In these animals, the study of navigational behavior evoked by airborne cues has been limited by the difficulty of precisely controlling stimuli. We present a system that can be used to deliver gaseous stimuli in defined spatial and temporal patterns to freely moving small animals. We used this apparatus, in combination with machine-vision algorithms, to assess and quantify navigational decision making of Drosophila melanogaster larvae in response to ethyl acetate (a volatile attractant) and carbon dioxide (a gaseous repellant).

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Figure 1: Apparatus design and performance.
Figure 2: Response to spatial gradients.
Figure 3: Navigation of a 2 p.p.m. cm−1 ethyl acetate concentration gradient.
Figure 4: Navigation of a 2,500 p.p.m. cm−1 CO2 concentration gradient.
Figure 5: Temporal CO2 and ethyl acetate gradients.

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Acknowledgements

We thank E. Soucy and J. Greenwood for engineering advice and suggestions. This work was supported by a US National Institutes of Health (NIH) Pioneer award to A.D.T.S., NIH grants to J.R.C. and an NIH National Research Service award to E.A.K.

Author information

Authors and Affiliations

  1. Department of Physics and Center for Brain Science, Harvard University, Cambridge, Massachusetts, USA

    Marc Gershow, Matthew Berck, Linjiao Luo, Elizabeth A Kane & Aravinthan D T Samuel

  2. Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, Connecticut, USA

    Dennis Mathew & John R Carlson

Authors
  1. Marc Gershow
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  2. Matthew Berck
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  3. Dennis Mathew
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  4. Linjiao Luo
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  7. Aravinthan D T Samuel
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Contributions

M.G. designed and constructed the linear and dynamic gaseous gradient apparatus, designed and wrote MAGAT analyzer software, designed and carried out experiments, analyzed all data and assembled figures. M.B. designed and carried out experiments. D.M. and L.L. designed and carried out preliminary experiments. E.A.K. designed experiments. J.R.C. and A.D.T.S. supervised the project and designed experiments. M.G., E.A.K. and A.D.T.S. wrote the manuscript.

Corresponding author

Correspondence to Aravinthan D T Samuel.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–3, Supplementary Tables 1 and 2, Supplementary Notes 1–3 (PDF 1917 kb)

Supplementary Video 1

Overview of video analysis steps. Video shows in sequence (1) raw image of larvae in a 2ppm cm−1 EtAc gradient (gradient increases in concentration to the right) (2) individual larvae are all tracked separately (colored tracks show movement history, circles indicate current position) (3) for each larva, we find a contour, midline, head and tail (4 larvae shown as examples) (4) from extracted position and postural features, we derive metrics (speed, body bend angle shown here) and behavioral states (1 larva shown as an example). At default playback speed of 30 frames per second (fps), video is 6× real time. (MOV 17156 kb)

Supplementary Video 2

Video complement to Figure 2a,b. Video sequence of still images depicted in Figure 2a, accompanied by navigational metrics (speed, dot product between head direction and direction of forward movement, body bend angle) presented in Figure 2b. Cyan dot on each data plot shows value associated with current frame. Text overlay on video shows elapsed time (time matches that shown in Fig. 2a,b) and behavioral state. As in Figure 2b, colored regions under data plots indicate behavioral state. At default playback speed of 10 fps, video is 2× real time. (MOV 8372 kb)

Supplementary Video 3

Extended playback of track excerpted in Supplementary Video 2. Video sequence, accompanied by navigational metrics (speed, dot product between head direction and direction of forward movement, body bend angle). Cyan dot on each data plot shows value associated with current frame. Text overlay on video shows elapsed time (time matches that shown in Fig. 2a,b) and behavioral state. As in Figure 2b, colored regions under data plots indicate behavioral state. At default playback speed of 25 fps, video is 5× real time. (MOV 25005 kb)

Supplementary Video 4

Example of runs and turns. Larva's track over video period indicated by white dots. As the video show the larva moving along the track, portions of the trajectory corresponding to runs and turns are indicated. At default playback speed of 25 fps, video is 5× real time. (MOV 702 kb)

Supplementary Video 5

Description of turn angles. The same larva and track from Supplementary Video 4 are shown. As the video plays, the prior heading angle (orange θ) and heading angle change (green Δθ) are graphically indicated for each turn. Figures 3g and 4g show distributions of Δθ, sorted according to θ. Figures 3h and 4h show the mean of Δθ versus θ. Figures 3i and 4i show the root mean square of Δθ versus θ. At default playback speed of 25 fps, video is 5× real time (except for pauses to highlight turn angles). (MOV 709 kb)

Supplementary Video 6

Example of rejected and accepted head sweeps. A portion of the video and track shown in Supplementary Videos 4, 5; the larva executes at rejected head sweep to its left followed by an accepted head sweep to its right. At default playback speed of 10 fps, video is 2× real time (except for pauses to highlight head sweeps). (MOV 232 kb)

Supplementary Software 1

Video analysis software. (ZIP 41302 kb)

Supplementary Software 2

Valve driver firmware and circuit layout. (ZIP 138 kb)

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Gershow, M., Berck, M., Mathew, D. et al. Controlling airborne cues to study small animal navigation. Nat Methods 9, 290–296 (2012). https://doi.org/10.1038/nmeth.1853

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