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A spike-timing mechanism for action selection

Abstract

We discovered a bimodal behavior in the genetically tractable organism Drosophila melanogaster that allowed us to directly probe the neural mechanisms of an action selection process. When confronted by a predator-mimicking looming stimulus, a fly responds with either a long-duration escape behavior sequence that initiates stable flight or a distinct, short-duration sequence that sacrifices flight stability for speed. Intracellular recording of the descending giant fiber (GF) interneuron during head-fixed escape revealed that GF spike timing relative to parallel circuits for escape actions determined which of the two behavioral responses was elicited. The process was well described by a simple model in which the GF circuit has a higher activation threshold than the parallel circuits, but can override ongoing behavior to force a short takeoff. Our findings suggest a neural mechanism for action selection in which relative activation timing of parallel circuits creates the appropriate motor output.

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Figure 1: Flies select between two escape sequences when confronted by a looming stimulus.
Figure 2: The GFs are necessary and sufficient for eliciting short-mode escapes.
Figure 3: GF Na+ spikes drive the short-mode escape.
Figure 4: GF spike timing determines escape mode.
Figure 5: A dual-circuit, angular size threshold model recapitulates the timing and selection between short- or long-mode escape.
Figure 6: GF-mediated short escapes confer a survival advantage within an ethologically relevant regime.

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References

  1. Gold, J.I. & Shadlen, M.N. The neural basis of decision making. Annu. Rev. Neurosci. 30, 535–574 (2007).

    Article  CAS  Google Scholar 

  2. Kristan, W.B. Neuronal decision-making circuits. Curr. Biol. 18, R928–R932 (2008).

    Article  CAS  Google Scholar 

  3. Herberholz, J. & Marquart, G.D. Decision making and behavioral choice during predator avoidance. Front. Neurosci. 6, 125 (2012).

    Article  Google Scholar 

  4. Seelig, J.D. & Jayaraman, V. Feature detection and orientation tuning in the Drosophila central complex. Nature 503, 262–266. 10.1038/nature12601 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Briggman, K.L., Abarbanel, H.D. & Kristan, W.B. Jr. Optical imaging of neuronal populations during decision-making. Science 307, 896–901 (2005).

    Article  CAS  Google Scholar 

  6. Zhang, K., Guo, J.Z., Peng, Y., Xi, W. & Guo, A. Dopamine-mushroom body circuit regulates saliency-based decision-making in Drosophila. Science 316, 1901–1904 (2007).

    Article  CAS  Google Scholar 

  7. Card, G. & Dickinson, M.H. Visually mediated motor planning in the escape response of Drosophila. Curr. Biol. 18, 1300–1307 (2008).

    Article  CAS  Google Scholar 

  8. Allen, M.J., Godenschwege, T.A., Tanouye, M.A. & Phelan, P. Making an escape: development and function of the Drosophila giant fibre system. Semin. Cell Dev. Biol. 17, 31–41 (2006).

    Article  CAS  Google Scholar 

  9. Wiersma, C.A. & Ikeda, K. Interneurons commanding swimmeret movements in the crayfish, Procambarus clarkii (Girard). Comp. Biochem. Physiol. 12, 509–525 (1964).

    Article  CAS  Google Scholar 

  10. Edwards, D.H., Heitler, W.J. & Krasne, F.B. Fifty years of a command neuron: the neurobiology of escape behavior in the crayfish. Trends Neurosci. 22, 153–161 (1999).

    Article  CAS  Google Scholar 

  11. Harley, C.M., English, B.A. & Ritzmann, R.E. Characterization of obstacle negotiation behaviors in the cockroach, Blaberus discoidalis. J. Exp. Biol. 212, 1463–1476 (2009).

    Article  CAS  Google Scholar 

  12. Ofstad, T.A., Zuker, C.S. & Reiser, M.B. Visual place learning in Drosophila melanogaster. Nature 474, 204–207 (2011).

    Article  CAS  Google Scholar 

  13. Card, G. & Dickinson, M.H. Performance trade-offs in the flight initiation of Drosophila. J. Exp. Biol. 211, 341–353 (2008).

    Article  Google Scholar 

  14. Hemmi, J.M. & Tomsic, D. The neuroethology of escape in crabs: from sensory ecology to neurons and back. Curr. Opin. Neurobiol. 22, 194–200 (2012).

    Article  CAS  Google Scholar 

  15. Card, G.M. Escape behaviors in insects. Curr. Opin. Neurobiol. 22, 180–186 (2012).

    Article  CAS  Google Scholar 

  16. Bacon, J.P. & Strausfeld, N.J. The dipteran 'Giant fiber' pathway - neurons and signals. J. Comp. Physiol. A Neuroethol. Sens. Neural Behav. Physiol. 158, 529–548 (1986).

    Article  Google Scholar 

  17. Thomas, J.B. & Wyman, R.J. Mutations altering synaptic connectivity between identified neurons in Drosophila. J. Neurosci. 4, 530–538 (1984).

    Article  CAS  Google Scholar 

  18. Tanouye, M.A. & Wyman, R.J. Motor outputs of giant nerve fiber in Drosophila. J. Neurophysiol. 44, 405–421 (1980).

    Article  CAS  Google Scholar 

  19. Lima, S.Q. & Miesenbock, G. Remote control of behavior through genetically targeted photostimulation of neurons. Cell 121, 141–152 (2005).

    Article  CAS  Google Scholar 

  20. Holmqvist, M.H. A visually elicited escape response in the fly that does not use the giant fiber pathway. Vis. Neurosci. 11, 1149–1161 (1994).

    Article  CAS  Google Scholar 

  21. Fotowat, H., Fayyazuddin, A., Bellen, H.J. & Gabbiani, F. A novel neuronal pathway for visually guided escape in Drosophila melanogaster. J. Neurophysiol. 102, 875–885 (2009).

    Article  Google Scholar 

  22. Mu, L., Ito, K., Bacon, J.P. & Strausfeld, N.J. Optic glomeruli and their inputs in Drosophila share an organizational ground pattern with the antennal lobes. J. Neurosci. 32, 6061–6071 (2012).

    Article  CAS  Google Scholar 

  23. Gabbiani, F., Krapp, H.G. & Laurent, G. Computation of object approach by a wide-field, motion-sensitive neuron. J. Neurosci. 19, 1122–1141 (1999).

    Article  CAS  Google Scholar 

  24. Pfeiffer, B.D. et al. Refinement of tools for targeted gene expression in Drosophila. Genetics 186, 735–755 (2010).

    Article  CAS  Google Scholar 

  25. Baines, R.A., Uhler, J.P., Thompson, A., Sweeney, S.T. & Bate, M. Altered electrical properties in Drosophila neurons developing without synaptic transmission. J. Neurosci. 21, 1523–1531 (2001).

    Article  CAS  Google Scholar 

  26. Klapoetke, N.C. et al. Independent optical excitation of distinct neural populations. Nat. Methods 11, 338–346 (2014).

    Article  CAS  Google Scholar 

  27. Levine, J. & Tracey, D. Structure and gunction of giant motorneuron of Drosophila melanogaster. J. Comp. Physiol. 87, 213–235 (1973).

    Article  Google Scholar 

  28. Fayyazuddin, A. & Dickinson, M.H. Haltere afferents provide direct, electrotonic input to a steering motor neuron in the blowfly, Calliphora. J. Neurosci. 16, 5225–5232 (1996).

    Article  CAS  Google Scholar 

  29. Fayyazuddin, A., Zaheer, M.A., Hiesinger, P.R. & Bellen, H.J. The nicotinic acetylcholine receptor Dalpha7 is required for an escape behavior in Drosophila. PLoS Biol. 4, e63 (2006).

    Article  Google Scholar 

  30. Allen, M.J. & Murphey, R.K. The chemical component of the mixed GF-TTMn synapse in Drosophila melanogaster uses acetylcholine as its neurotransmitter. Eur. J. Neurosci. 26, 439–445 (2007).

    Article  Google Scholar 

  31. Maimon, G., Straw, A.D. & Dickinson, M.H. Active flight increases the gain of visual motion processing in Drosophila. Nat. Neurosci. 13, 393–399 (2010).

    Article  CAS  Google Scholar 

  32. Tootoonian, S., Coen, P., Kawai, R. & Murthy, M. Neural representations of courtship song in the Drosophila brain. J. Neurosci. 32, 787–798 (2012).

    Article  CAS  Google Scholar 

  33. Llinás, R. & Sugimori, M. Electrophysiological properties of in vitro Purkinje cell dendrites in mammalian cerebellar slices. J. Physiol. (Lond.) 305, 197–213 (1980).

    Article  Google Scholar 

  34. Gouwens, N.W. & Wilson, R.I. Signal propagation in Drosophila central neurons. J. Neurosci. 29, 6239–6249 (2009).

    Article  CAS  Google Scholar 

  35. Hatsopoulos, N., Gabbiani, F. & Laurent, G. Elementary computation of object approach by wide-field visual neuron. Science 270, 1000–1003 (1995).

    Article  CAS  Google Scholar 

  36. Sun, H. & Frost, B.J. Computation of different optical variables of looming objects in pigeon nucleus rotundus neurons. Nat. Neurosci. 1, 296–303 (1998).

    Article  CAS  Google Scholar 

  37. Kohashi, T. & Oda, Y. Initiation of Mauthner- or non-Mauthner-mediated fast escape evoked by different modes of sensory input. J. Neurosci. 28, 10641–10653 (2008).

    Article  CAS  Google Scholar 

  38. Cisek, P. & Kalaska, J.F. Neural mechanisms for interacting with a world full of action choices. Annu. Rev. Neurosci. 33, 269–298. 10.1146/annurev.neuro.051508.135409 (2010).

    Article  CAS  PubMed  Google Scholar 

  39. McPeek, R.M. & Keller, E.L. Superior colliculus activity related to concurrent processing of saccade goals in a visual search task. J. Neurophysiol. 87, 1805–1815 (2002).

    Article  Google Scholar 

  40. Cisek, P. & Kalaska, J.F. Neural correlates of reaching decisions in dorsal premotor cortex: specification of multiple direction choices and final selection of action. Neuron 45, 801–814. 10.1016/j.neuron.2005.01.027 (2005).

    Article  CAS  Google Scholar 

  41. Cisek, P. Cortical mechanisms of action selection: the affordance competition hypothesis. Phil. Trans. R. Soc. Lond. B 362, 1585–1599. 10.1098/rstb.2007.2054 (2007).

    Article  Google Scholar 

  42. Burrows, M. & Rowell, C.H.F. Connections between descending visual interneurons and metathoracic motoneurons in locust. J. Comp. Physiol. 85, 221–234 (1973).

    Article  Google Scholar 

  43. Rind, F.C. A chemical synapse between two motion detecting neurones in the locust brain. J. Exp. Biol. 110, 143–167 (1984).

    CAS  PubMed  Google Scholar 

  44. Gray, J.R., Blincow, E. & Robertson, R.M. A pair of motion-sensitive neurons in the locust encode approaches of a looming object. J. Comp. Physiol. A Neuroethol. Sens. Neural Behav. Physiol. 196, 927–938 (2010).

    Article  Google Scholar 

  45. Eaton, R.C., Lee, R.K. & Foreman, M.B. The Mauthner cell and other identified neurons of the brainstem escape network of fish. Prog. Neurobiol. 63, 467–485 (2001).

    Article  CAS  Google Scholar 

  46. O'Malley, D.M., Kao, Y.H. & Fetcho, J.R. Imaging the functional organization of zebrafish hindbrain segments during escape behaviors. Neuron 17, 1145–1155 (1996).

    Article  CAS  Google Scholar 

  47. Svoboda, K.R. & Fetcho, J.R. Interactions between the neural networks for escape and swimming in goldfish. J. Neurosci. 16, 843–852 (1996).

    Article  CAS  Google Scholar 

  48. Bullock, T.H . Comparative neuroethology of startle, rapid escape, and giant fiber–mediated responses in Neural Mechanisms of Startle Behavior (ed. R.C. Eaton) 1–13 (Plenum Press, 1984).

  49. Trimarchi, J.R. & Schneiderman, A.M. Different neural pathways coordinate Drosophila flight initiations evoked by visual and olfactory stimuli. J. Exp. Biol. 198, 1099–1104 (1995).

    CAS  PubMed  Google Scholar 

  50. de Vries, S.E. & Clandinin, T.R. Loom-sensitive neurons link computation to action in the Drosophila visual system. Curr. Biol. 22, 353–362 (2012).

    Article  CAS  Google Scholar 

  51. Pfeiffer, B.D., Truman, J.W. & Rubin, G.M. Using translational enhancers to increase transgene expression in Drosophila. Proc. Natl. Acad. Sci. USA 109, 6626–6631 (2012).

    CAS  Google Scholar 

  52. Brainard, D.H. The psychophysics toolbox. Spat. Vis. 10, 433–436 (1997).

    Article  CAS  Google Scholar 

  53. Pelli, D.G. The VideoToolbox software for visual psychophysics: transforming numbers into movies. Spat. Vis. 10, 437–442 (1997).

    Article  CAS  Google Scholar 

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Acknowledgements

We thank T. Ngo and A. Jenett (Janelia Farm Research Campus) for providing the GF-split GAL4 line, B.D. Pfeiffer (Janelia Farm Research Campus) for pJFRC12-10XUAS-IVS-myrGFP, pJFRC28-10XUAS-IVS-GFP, and pJFRC49-10XUAS-IVS-eGFPKir2.1 flies, and K. Wantanabe (Caltech) for the pUAS-EGFP-Kir2.1 DNA. We thank V. Jayaraman and A. Karpova (Janelia Farm Research Campus) for providing UAS-CsChrimson flies. We thank P. Herold for damselfly husbandry and assistance with data collection and R. Franconville for help troubleshooting P2X2 receptor experiments. We thank V. Jayaraman, G. Murphy and S. Huston for their comments on the manuscript. We thank the Janelia Fly Facility (T. Laverty, A. Cavallaro, K. Hibbard, D. Hall, M. Mercer, D. Fetter, J. McMachon, J.-C. Kao and D. Ruiz). We thank the Janelia Instrument Design and Fabrication Department for help with the behavioral apparatus.

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Authors and Affiliations

Authors

Contributions

C.R.v.R., A.L. and G.M.C. prepared the paper. C.R.v.R., P.B. and G.M.C. analyzed data. C.R.v.R., P.B., W.R.W. A.L.Y. and G.M.C. performed experiments. C.R.v.R., A.L. and G.M.C. designed experiments. G.Z.Z. provided genetic tools. C.R.v.R. built the electrophysiology apparatus. M.Y.P., W.R.W. and G.M.C. built the behavioral apparatus. A.L. built the damselfly tracking system.

Corresponding author

Correspondence to Gwyneth M Card.

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The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Apparatus for video recording an individual fly's response to projected looming stimuli.

Supplementary Figure 2 Motor program durations for several genotypes.

(a) Escape sequence duration histograms (bars) and probability density functions (black lines) following Gaussian curve fits for each control genotype, combined for r/v=14, 40, and 70 ms. n are listed on histograms. Genotypes: “WT”: wild-type DL, “GF WT”: w+GF-split-GAL4 UAS-myrGFP, “AD Kir”: w+ GF-split-AD UAS-Kir2.1, “DBD Kir”: w+GF-split-DBD UAS-Kir2.1, “WT Kir”: w+ UAS-Kir2.1. (b) Escape sequence duration histogram and probability density function with GF silencing. “GF Kir”: w+GF-split-GAL4 UAS-myrGFP UAS-Kir2.1. Inset: Expressing Kir2.1 with the GF split-GAL4 driver line causes a significant hyperpolarization of the GF resting membrane potential, compared to control lines (boxplots as described in Fig. 2, n = 3 flies, two sided t-test, ** = P<0.005, t = 6.352). “GF +”: w+GF-split-GAL4 UAS-myrGFP

Supplementary Figure 3 Takeoff percentages and takeoff timing for several genotypes.

(a) Takeoff percentages across r/v values of 14, 40, and 70 ms, from left to right (number of flies as listed, χ2-test, P = 0.015, 0.087, 0.148 and χ2 = 11.81, 6.447, and 2.371 for r/v = 14, 40, and 70 ms, Bonferroni correction post hoc where permitted, ** = P < 0.005). (b) Time of takeoff, with respect to time to contact (time of contact, TOC = 0 ms), across r/v (Kruskal-Wallis, P=<<0.0001, <<0.0001, and 0.021 and χ2 = 41.01, 42.80, and 13.27 for r/v = 14, 40, and 70 ms, Bonferroni correction post hoc, ** = P <0.005, ***=P<0.001).

Supplementary Figure 4 GF Na+ spikes can be evoked upon ATP stimulation of P2X2 receptor expressing flies.

(a, b) ATP (1mM) stimulation of P2X2 receptor expressing GFs evokes spiking in the ipsilateral (a, black trace, representative example from 5 flies) or contralateral (b, black trace, representative example from 3 flies) GF but not in GFs only expressing GFP (gray traces, representative example of 3 flies each). (c) Ipsilateral ATP pulses can also evoke both large Ca2+-mediated potentials and small, narrow spikes (inset is expanded yellow box). (d) Tetrodotoxin (TTX, 1 μm) application eliminates the small, narrow Na+ spikes while the Ca2+-mediated potentials remain (representative example from 3 flies). Genotypes: GF-split-GAL4 UAS-GFP UAS-P2X2, GF-split-GAL4 UAS-GFP (control).

Supplementary Figure 5

Example spike (top, representative response chosen from 10 flies) and subthreshold (middle, representative response chosen from 33 flies) traces in response to looms (bottom) at three separate r/v values (a) 14, (b) 40, and (c) 70 ms. Genotype: w+ GF-split-GAL4 UAS-GFP.

Supplementary Figure 6 Dual circuit, size threshold model.

(a) The time of wing elevation for GF silenced flies (red circles, mean ± standard deviation, n=57, 58, 99, 61 for r/v=8, 14, 40, and 70 ms, respectively) or GF spikes (red squares, n=8, 12, 7 for r/v=14, 40 and 70 ms, respectively) with respect to r/v. The neural delay (δ) for each pathway was taken directly from the y-intercept of the linear fit (R2 > 0.999 in both cases). Inset: The stimulus size (mean ± standard deviation) at the fixed neural delay preceding wing elevation or GF spiking. (b) The standard deviation of wing elevation or GF spiking increased linearly with r/v (R2 = >0.999 and 0.9977 while slopes = 1.353 and 1.213 for GF spike or GF Kir wing timing, respectively). The slopes were used to derive the standard deviation for the size threshold (θthresh). (c) Model schematic displaying the 4 variables, drawn from their respective distributions, used to select the circuit and determine the timing of escape on a per fly basis.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–6 (PDF 971 kb)

Supplementary Methods Checklist

(PDF 497 kb)

Supplementary Video 1

Example of short duration escape; time corresponds to start of video. (MP4 294 kb)

Supplementary Video 2

Example of long duration, wing-raised, escape; time corresponds to start of video. (MP4 432 kb)

Supplementary Video 3

Example of escape upon light activation of CsChrimson expressing GFs. (MOV 183 kb)

Supplementary Video 4

Front view of escape in a tethered prep while recording whole-cell spiking responses from the GF. (MP4 508 kb)

Supplementary Video 5

Side view of escape in a tethered prep while recording whole-cell spiking responses from the GF. (MP4 910 kb)

Supplementary Video 6

Side view of no escape in a tethered prep while recording whole-cell subthreshold responses from the GF. (AVI 1614 kb)

Supplementary Video 7

Fly capture during a damselfly predation. (MP4 256 kb)

Supplementary Video 8

Successful fly escape from a damselfly predation attempt. (MP4 681 kb)

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von Reyn, C., Breads, P., Peek, M. et al. A spike-timing mechanism for action selection. Nat Neurosci 17, 962–970 (2014). https://doi.org/10.1038/nn.3741

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