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Cellular evidence for efference copy in Drosophila visuomotor processing

Nature Neuroscience volume 18, pages 1247–1255 (2015)Cite this article

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Abstract

Each time a locomoting fly turns, the visual image sweeps over the retina and generates a motion stimulus. Classic behavioral experiments suggested that flies use active neural-circuit mechanisms to suppress the perception of self-generated visual motion during intended turns. Direct electrophysiological evidence, however, has been lacking. We found that visual neurons in Drosophila receive motor-related inputs during rapid flight turns. These inputs arrived with a sign and latency appropriate for suppressing each targeted cell's visual response to the turn. Precise measurements of behavioral and neuronal response latencies supported the idea that motor-related inputs to optic flow–processing cells represent internal predictions of the expected visual drive induced by voluntary turns. Motor-related inputs to small object–selective visual neurons could reflect either proprioceptive feedback from the turn or internally generated signals. Our results in Drosophila echo the suppression of visual perception during rapid eye movements in primates, demonstrating common functional principles of sensorimotor processing across phyla.

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Figure 1: Patch-clamp recordings in tethered, flying Drosophila can reveal whether fly visual neurons receive motor-related inputs with voluntary turns.
Figure 2: Identified optic flow processing neurons in Drosophila receive motor-related inputs during saccades.
Figure 3: Saccade-related inputs to optic flow processing neurons persist in blind flies.
Figure 4: Saccade-related inputs to optic flow processing neurons have the correct sign and magnitude to cancel reafferent visual input during saccades.
Figure 5: Saccade-related inputs to small object–selective optic-glomeruli interneurons have the correct sign and magnitude to cancel reafferent visual input during saccades.
Figure 6: Visual and saccade-related inputs have similar latencies of arrival to fly visual neurons.
Figure 7: Analysis of tethered, flying flies that were free to move their heads shows that head movements slightly follow saccade associated changes in wing kinematics during spontaneous saccades.

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References

  1. Olveczky, B.P., Baccus, S.A. & Meister, M. Segregation of object and background motion in the retina. Nature 423, 401–408 (2003).

    PubMed  Google Scholar 

  2. Bridgeman, B., Hendry, D. & Stark, L. Failure to detect displacement of the visual world during saccadic eye movements. Vision Res. 15, 719–722 (1975).

    CAS  PubMed  Google Scholar 

  3. Burr, D.C., Morrone, M.C. & Ross, J. Selective suppression of the magnocellular visual pathway during saccadic eye movements. Nature 371, 511–513 (1994).

    CAS  PubMed  Google Scholar 

  4. von Holst, E. & Mittelstaedt, H. The principle of reafference. Naturwissenschaften 37, 464–476 (1950).

    Google Scholar 

  5. Crapse, T.B. & Sommer, M.A. Corollary discharge across the animal kingdom. Nat. Rev. Neurosci. 9, 587–600 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  6. Poulet, J.F. & Hedwig, B. The cellular basis of a corollary discharge. Science 311, 518–522 (2006).

    CAS  PubMed  Google Scholar 

  7. Bell, C.C. An efference copy which is modified by reafferent input. Science 214, 450–453 (1981).

    CAS  PubMed  Google Scholar 

  8. Kennedy, A. et al. A temporal basis for predicting the sensory consequences of motor commands in an electric fish. Nat. Neurosci. 17, 416–422 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  9. Tammero, L.F. & Dickinson, M.H. The influence of visual landscape on the free flight behavior of the fruit fly Drosophila melanogaster. J. Exp. Biol. 205, 327–343 (2002).

    PubMed  Google Scholar 

  10. Collett, T.S. Angular tracking and the optomotor response an analysis of visual reflex interaction in a hoverfly. J. Comp. Physiol. A Neuroethol. Sens. Neural Behav. Physiol. 140, 145–158 (1980).

    Google Scholar 

  11. Heisenberg, M. & Wolf, R. On the fine structure of yaw torque in visual flight orientation of Drosophila melanogaster. J. Comp. Physiol. A Neuroethol. Sens. Neural Behav. Physiol. 130, 113–130 (1979).

    Google Scholar 

  12. Mischiati, M. et al. Internal models direct dragonfly interception steering. Nature 517, 333–338 (2015).

    CAS  PubMed  Google Scholar 

  13. Webb, B. Neural mechanisms for prediction: do insects have forward models? Trends Neurosci. 27, 278–282 (2004).

    Article  CAS  PubMed  Google Scholar 

  14. Collett, T. & Land, M. How hoverflies compute interception courses. J. Comp. Physiol. A Neuroethol. Sens. Neural Behav. Physiol. 125, 191–204 (1978).

    Google Scholar 

  15. 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).

    CAS  PubMed  Google Scholar 

  16. Censi, A., Straw, A.D., Sayaman, R.W., Murray, R.M. & Dickinson, M.H. Discriminating external and internal causes for heading changes in freely flying Drosophila. PLOS Comput. Biol. 9, e1002891 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  17. Maye, A., Hsieh, C.-H., Sugihara, G. & Brembs, B. Order in spontaneous behavior. PLoS ONE 2, e443 (2007).

    PubMed  PubMed Central  Google Scholar 

  18. Schnell, B. et al. Processing of horizontal optic flow in three visual interneurons of the Drosophila brain. J. Neurophysiol. 103, 1646–1657 (2010).

    CAS  PubMed  Google Scholar 

  19. Haikala, V., Joesch, M., Borst, A. & Mauss, A.S. Optogenetic control of fly optomotor responses. J. Neurosci. 33, 13927–13934 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  20. Haag, J. & Borst, A. Active membrane properties and signal encoding in graded potential neurons. J. Neurosci. 18, 7972–7986 (1998).

    CAS  PubMed  PubMed Central  Google Scholar 

  21. Joesch, M., Plett, J., Borst, A. & Reiff, D.F. Response properties of motion-sensitive visual interneurons in the lobula plate of Drosophila melanogaster. Curr. Biol. 18, 368–374 (2008).

    CAS  PubMed  Google Scholar 

  22. Muijres, F.T., Elzinga, M.J., Iwasaki, N.A. & Dickinson, M.H. Body saccades of Drosophila consist of stereotyped banked turns. J. Exp. Biol. 218, 864–875 (2015).

    PubMed  Google Scholar 

  23. Huston, S.J. & Krapp, H.G. Visuomotor transformation in the fly gaze stabilization system. PLoS Biol. 6, e173 (2008).

    PubMed  PubMed Central  Google Scholar 

  24. Mamiya, A., Straw, A.D., Tomasson, E. & Dickinson, M.H. Active and passive antennal movements during visually guided steering in flying Drosophila. J. Neurosci. 31, 6900–6914 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  25. Cosens, D. & Briscoe, D. A switch phenomenon in the compound eye of the white-eyed mutant of Drosophila melanogaster. J. Insect Physiol. 18, 627–632 (1972).

    Google Scholar 

  26. Schnell, B., Weir, P.T., Roth, E., Fairhall, A.L. & Dickinson, M.H. Cellular mechanisms for integral feedback in visually guided behavior. Proc. Natl. Acad. Sci. USA 111, 5700–5705 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  27. Zaretsky, M. & Rowell, C.H. Saccadic suppression by corollary discharge in the locust. Nature 280, 583–585 (1979).

    CAS  PubMed  Google Scholar 

  28. Otsuna, H. & Ito, K. Systematic analysis of the visual projection neurons of Drosophila melanogaster. I. Lobula-specific pathways. J. Comp. Neurol. 497, 928–958 (2006).

    PubMed  Google Scholar 

  29. Strausfeld, N.J., Sinakevitch, I. & Okamura, J.-Y. Organization of local interneurons in optic glomeruli of the dipterous visual system and comparisons with the antennal lobes. Dev. Neurobiol. 67, 1267–1288 (2007).

    PubMed  Google Scholar 

  30. 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).

    CAS  PubMed  PubMed Central  Google Scholar 

  31. Gohl, D.M. et al. A versatile in vivo system for directed dissection of gene expression patterns. Nat. Methods 8, 231–237 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  32. Nordström, K., Barnett, P. & O'Carroll, D. Insect detection of small targets moving in visual clutter. PLoS Biol. 4, e54 (2006).

    PubMed  PubMed Central  Google Scholar 

  33. Muijres, F.T., Elzinga, M.J., Melis, J.M. & Dickinson, M.H. Flies evade looming targets by executing rapid visually directed banked turns. Science 344, 172–177 (2014).

    CAS  PubMed  Google Scholar 

  34. Van Hateren, J.H. & Schilstra, C. Blowfly flight and optic flow. II. Head movements during flight. J. Exp. Biol. 202, 1491–1500 (1999).

    Google Scholar 

  35. Fox, J.L. & Frye, M.A. Figure-ground discrimination behavior in Drosophila. II. Visual influences on head movement behavior. J. Exp. Biol. 217, 570–579 (2014).

    PubMed  PubMed Central  Google Scholar 

  36. Palka, J., Lawrence, P.A. & Hart, H.S. Neural projection patterns from homeotic tissue of Drosophila studied in bithorax mutants and mosaics. Dev. Biol. 69, 549–575 (1979).

    CAS  PubMed  Google Scholar 

  37. Egelhaaf, M. Dynamic properties of two control systems underlying visually guided turning in house-flies. J. Comp. Physiol. A Neuroethol. Sens. Neural Behav. Physiol. 161, 777–783 (1987).

    Google Scholar 

  38. Kim, H.R., Angelaki, D.E. & DeAngelis, G.C. A novel role for visual perspective cues in the neural computation of depth. Nat. Neurosci. 18, 129–137 (2015).

    CAS  PubMed  Google Scholar 

  39. Bender, J.A. & Dickinson, M.H. A comparison of visual and haltere-mediated feedback in the control of body saccades in Drosophila melanogaster. J. Exp. Biol. 209, 4597–4606 (2006).

    PubMed  Google Scholar 

  40. Straw, A.D., Rainsford, T. & O'Carroll, D.C. Contrast sensitivity of insect motion detectors to natural images. J. Vis. 8, 32 (2008).

    PubMed  Google Scholar 

  41. Wolpert, D.M. & Ghahramani, Z. Computational principles of movement neuroscience. Nat. Neurosci. 3, 1212–1217 (2000).

    CAS  PubMed  Google Scholar 

  42. Tammero, L.F., Frye, M. & Dickinson, M.H. Spatial organization of visuomotor reflexes in Drosophila. J. Exp. Biol. 207, 113–122 (2004).

    PubMed  Google Scholar 

  43. Maimon, G., Straw, A.D. & Dickinson, M.H. A simple vision-based algorithm for decision making in flying Drosophila. Curr. Biol. 18, 464–470 (2008).

    CAS  PubMed  Google Scholar 

  44. Agrawal, S., Safarik, S. & Dickinson, M.H. The relative roles of vision and chemosensation in mate recognition of Drosophila melanogaster. J. Exp. Biol. 217, 2796–2805 (2014).

    PubMed  Google Scholar 

  45. Chan, W.P., Prete, F. & Dickinson, M.H. Visual input to the efferent control system of a fly's “gyroscope”. Science 280, 289–292 (1998).

    CAS  PubMed  Google Scholar 

  46. Sommer, M.A. A pathway in primate brain for internal monitoring of movements. Science 296, 1480–1482 (2002).

    CAS  PubMed  Google Scholar 

  47. Suver, M.P., Mamiya, A. & Dickinson, M.H. Octopamine neurons mediate flight-induced modulation of visual processing in Drosophila. Curr. Biol. 22, 2294–2302 (2012).

    CAS  PubMed  Google Scholar 

  48. Longden, K.D. & Krapp, H. State-dependent performance of optic-flow processing interneurons. J. Neurophysiol. 102, 3606–3618 (2009).

    PubMed  Google Scholar 

  49. Chiappe, M.E., Seelig, J., Reiser, M. & Jayaraman, V. Walking modulates speed sensitivity in Drosophila motion vision. Curr. Biol. 20, 1470–1475 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  50. Borst, A. Fly visual course control: behaviour, algorithms and circuits. Nat. Rev. Neurosci. 15, 590–599 (2014).

    CAS  PubMed  Google Scholar 

  51. Reiser, M.B. & Dickinson, M.H. A modular display system for insect behavioral neuroscience. J. Neurosci. Methods 167, 127–139 (2008).

    PubMed  Google Scholar 

  52. Bender, J.A. & Dickinson, M.H. Visual stimulation of saccades in magnetically tethered Drosophila. J. Exp. Biol. 209, 3170–3182 (2006).

    PubMed  Google Scholar 

  53. Heisenberg, M. & Wolf, R. Vision in Drosophila: Genetics of Microbehavior (Springer-Verlag, 1984).

  54. Barry, P.H. & Lynch, J.W. Liquid junction potentials and small cell effects in patch-clamp analysis. J. Membr. Biol. 121, 101–117 (1991).

    CAS  PubMed  Google Scholar 

  55. Johnson, E.C. & Pak, W.L. Electrophysiological study of Drosophila rhodopsin mutants. J. Gen. Physiol. 88, 651–673 (1986).

    CAS  PubMed  Google Scholar 

  56. Straw, A.D. & Dickinson, M.H. Motmot, an open-source toolkit for realtime video acquisition and analysis. Source Code Biol. Med. 4, 5 (2009).

    PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We would like to thank members of the lab and M. Dickinson for comments on the manuscript. We would like to acknowledge A. Adachi for help with immunohistochemistry and M. Siles, D. Gohl and T. Clandinin for the gift of the InSITE Gal4 lines. M. Desouto drew the fly schematic in Figure 1d. P. Polidoro designed the IR photodiode circuit that allowed for the analysis in Supplementary Figure 6. G.M. is a New York Stem Cell Foundation – Robertson Investigator. J.K.F. is funded by the Life Sciences Research Foundation. Research reported in this publication was supported by the New York Stem Cell Foundation (grant NYSCF-R-NI13), Searle Scholars Foundation and the National Institute on Drug Abuse of the US National Institutes of Health (grant DP2DA035148). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

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  1. Laboratory of Integrative Brain Function, The Rockefeller University, New York, New York, USA

    Anmo J Kim, Jamie K Fitzgerald & Gaby Maimon

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Contributions

A.J.K. and G.M. conceived the project. A.J.K., J.K.F. and G.M. devised the experiments, developed experimental protocols and analyzed the data. A.J.K. and G.M. collected the data and wrote the manuscript.

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Correspondence to Gaby Maimon.

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Integrated supplementary information

Supplementary Figure 1 Horizontal System North (HSN) cells respond best, and in a direction-selective manner, to horizontally moving gratings or long bars.

(a) Responses of a single HSN cell, recorded in the right lobula plate, to gratings, long bars, and small spots moving in four directions. Single trials are shown in color and the average responses are shown in black (5-6 trials per condition). The gratings had a spatial wavelength of 18 ˚/cycle and a temporal frequency of 1.25 cycles/s. Bars (9˚ wide x 75˚ high) and spots (9˚ x 9˚) moved at 22.5˚/s. (b) Averaged responses of 7 HSN cells, all recorded in the right lobula plate.

Supplementary Figure 2 Vertical System (VS) 1-2 cells respond best, and in a direction-selective manner, to vertically moving gratings or long bars.

(a) Responses of a single VS1 cell, recorded in the right lobula plate, to gratings, long bars, and small spots moving in four directions. Single trials are shown in color and the average responses are shown in black (5-6 trials per condition). The gratings had a spatial wavelength of 18 ˚/cycle and a temporal frequency of 1.25 cycles/s. Bars (9˚ wide x 75˚ high) and spots (9˚ x 9˚) moved at 22.5˚/s. (b) Averaged responses of 8 VS1-2 cells, all recorded in the right lobula plate.

Supplementary Figure 3 Visualizing wingstroke amplitude statistics and an explanation of how we detect saccades

(a) Histograms of L-R WBA from 10 recording sessions with HSN cells (red) and 21 sessions with VS1-2 cells (blue). Light lines represent histograms from individual flies and the dark lines are averages across flies. The L-R WBA signal was high-pass-filtered before computing histograms, to eliminate slow drift. (b) Auto-correlation functions of L-R WBA for the same set of cells, depicted in the same color scheme as in panel a. (c) Cumulative distribution functions (cdfs) of L-R WBA for all flies studied. L-R WBA was high-pass filtered with a 1 Hz cut-off before plotting cdfs so as to eliminate slow drift in the L–R WBA trace. To get further analyzed, putative saccades had to cross an amplitude threshold in the last step of the saccade detection algorithm. This amplitude threshold was set at the 90th percentile of the L-R WBA cdf from that session (thin arrows indicate the smallest and largest thresholds used; thick arrow indicates the mean threshold used across all sessions). (d) Detecting saccades in a sample trace. Top row: a sample L-R WBA trace (gray) and a low-pass filtered version (6 Hz cut-off frequency) are shown. Second row: the derivative of the low-pass-filtered L-R WBA is shown, with putative rightward saccades marked by red dots and putative leftward saccades marked by blue dots. Putative saccades were detected from local maxima and minima in the L-R WBA derivative trace whose magnitude exceeded a positive or negative threshold (magenta lines), respectively. Third row: putative saccades are shown as red and blue dots on the low-pass filtered L-R WBA trace. Bottom row: same as the third row except we highlight saccades that were analyzed further in this manuscript by coloring the L–R WBA trace––red for rightward saccades; blue for leftward saccades––to indicate the onset moment, end moment, and duration of each analyzed saccade. To be analyzed, saccades had to cross an amplitude threshold, described in panel c, and also had to have a stable L–R WBA signal prior to saccade onset, so that we could assign a clear onset time to the saccade (Online Methods).

Supplementary Figure 4 Optic-glomeruli interneurons (OGINs) respond best to small spots, in a non-directional manner, and only weakly to long bars or gratings.

(a) Responses of a single OGIN, recorded in the right half of the brain, to gratings, long bars, and small spots moving in four directions. Single trials are shown in color and the average responses are shown in black (5-6 trials per condition). The gratings had a spatial wavelength of 18 ˚/cycle and a temporal frequency of 1.25 cycles/s. Bars (9˚ wide x 75˚ high) and spots (9˚ x 9˚) moved at 22.5˚/s. (b) Average responses of 18 OGINs recorded on the right side of the brain. Out of 21 spot-selective OGINs analyzed in Figure 5, three cells were excluded in this analysis because we did not maintain the recording long enough to obtain complete receptive field measurements. (Note that all 21 cells in Figure 5 were tested with a reduced set of stimuli, early in the recording session, which were sufficient to determine spot selectivity and receptive-field width.)

Supplementary Figure 5 Optic-glomeruli interneurons (OGINs) arborize in the lateral protocerebrum.

These representative images illustrate the anatomy of the recorded neurons. (a) Schematic of an OGIN. Black box highlights the region shown in panels b and c. (b) Six z-slices of a filled OGIN in the right hemisphere, 5 µm spacing. Z-slices are arranged clockwise from posterior or neuraxis dorsal (closer to the protocerebral bridge) to anterior or neuraxis ventral (closer to the antennal lobe.). Immunoamplified neuropil signal is shown in magenta (nc82 anti-Bruchpilot antibody) and biocytin filled neurites in green. The GFP channel is not shown.) Dashed circles highlight regions with neurite arborizations. (c) Same as in panel b, but for a second cell.

Supplementary Figure 6 An IR photodiode signal to monitor wingbeat motion confirms the precision of the video-based analysis of saccade onset times.

(a) A photodiode placed beneath the fly’s left wing showed oscillations in its signal as the wing swept back and forth during each wingstroke. While the shape and magnitude of the photodiode signal were not calibrated to any specific kinematic parameter of the wing’s trajectory, we noticed that the envelope of the signal changed amplitude briefly with each saccade. Thus, the photodiode signal could provide a second measure of the onset times of saccades, beyond the estimate derived from analyzing video images. We calculated the maximum of the photodiode trace in a 6-ms sliding-window, which generated an envelope signal. (6 ms is slightly longer than the longest inter-wingstroke interval.) Saccades were clearly evident in this envelope signal as negative deviations for rightward saccades (shown here) and positive deviations for leftward saccades (shown in panel b). (b) Average photodiode and L–R WBA traces associated with saccades for 15 flies. Saccades were culled from the L–R WBA trace (Online Methods and Supplementary Figure 3). Individual-fly averages are shown in gray. Averages across experiments are shown in magenta or black. Insets show the same traces at a higher temporal resolution.

Supplementary Figure 7 We observed, during non-flight, examples where the HSN membrane potential was dynamically modulated in a manner that resembled saccade related potentials.

(a) The membrane potential (Vm) of a single HSN cell during flight and immediately after the fly stopped flying. After the cessation of flight, we observed SRP-like changes in Vm (red arrows), which were most obvious during a presentation of a grating moving in the cell’s preferred direction. The unfiltered Vm is shown in gray and a low-pass filtered version (20-Hz cut-off) is shown in black. The unfiltered L–R WBA is shown in gray and a low-pass filtered version (10-Hz cut-off) is shown in black. (b) Same as in panel a for a second HSN cell. The non-flight trace in this example starts ~10 s after the cessation of flight. These example traces suggest that SRPs in HSN cells do not require flight-associated wing movements.

Supplementary Figure 8 Summary diagram of motor-related silencing of visual neurons in Drosophila.

A command to perform a saccade is generated by a hypothesized voluntary saccade generator. This command is sent to the flight motor system (blue line). The sensory consequences of the command are internally computed by a putative forward model of unknown complexity and these predictions are sent to the visual system (red and green lines). Visual neurons receive motor related inputs (red and green arrows) that oppose the expected reafferent visual input from the saccade. Black τn’s represent the visual response latency of each cell. Red and green τn’s represent the latency of motor-related inputs to each cell, which are tailored to the visual response latency. Because saccadic motor-related inputs to OGINs arrive 69-70 ms after the wings move, it is possible that the motor related signals to these cells originate as a sensory, perhaps mechanosensory, feedback from the act of turning; we indicate the possibility of OGIN silencing arising from either sensory feedback or an internal/forward model by the two question marks overlaying green lines that indicate the two possible feedback routes.

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Supplementary Figures 1–8 and Supplementary Table 1 (PDF 7278 kb)

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Saccade related potentials in a recording from a horizontal system north (HSN) cell in the context of a uniformly lit screen.

This video shows the membrane voltage (Vm) of an HSN cell, recorded in the right lobula plate, as the fly performs spontaneous saccades while viewing a uniformly lit screen. The HSN cell shows hyperpolarizing saccade related potentials (SRPs) during leftward saccades and depolarizing SRPs during rightward saccades. L-R WBA: left minus right wingbeat amplitude. (MOV 3379 kb)

Saccade related potentials in a recording from a horizontal system north (HSN) cell in the context of a steady state grating stimulus.

This video shows the membrane voltage (Vm) of an HSN cell, recorded in the right lobula plate, as the fly performs spontaneous saccades while viewing a squarewave grating that moved with a temporal frequency of 1 Hz. The first grating stimulus presented moved to the right, in the preferred direction of the neuron. The second stimulus moved to the left, in the null direction. Before and after each grating stimulus, the fly viewed a uniformly lit screen at mean luminance. The HSN cell shows hyperpolarizing saccade related potentials (SRPs) during leftward saccades made in the context of the rightward moving grating and depolarizing SRPs during rightward saccades made in the context of the leftward moving grating. There is a brief, ∼1 s, error in tracking ∼7 s into this movie. L-R WBA: left minus right wingbeat amplitude. (MOV 17168 kb)

Saccade related potentials in a recording from an optic-glomeruli interneuron (OGIN).

This video shows the membrane voltage (Vm) of an OGIN, recorded in the right side of the brain, as the fly performs spontaneous saccades while viewing a uniformly lit screen and a moving small spot. The OGIN shows clear, hyperpolarizing, saccade related potentials (SRPs), when the spot is in the receptive field and depolarizing the neuron. L-R WBA: left minus right wingbeat amplitude. (MOV 5509 kb)

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Kim, A., Fitzgerald, J. & Maimon, G. Cellular evidence for efference copy in Drosophila visuomotor processing. Nat Neurosci 18, 1247–1255 (2015). https://doi.org/10.1038/nn.4083

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