Visual Control of Walking Speed in Drosophila

Abstract

An animal's self-motion generates optic flow across its retina, and it can use this visual signal to regulate its orientation and speed through the world. While orientation control has been studied extensively in Drosophila and other insects, much less is known about the visual cues and circuits that regulate translational speed. Here, we show that flies regulate walking speed with an algorithm that is tuned to the speed of visual motion, causing them to slow when visual objects are nearby. This regulation does not depend strongly on the spatial structure or the direction of visual stimuli, making it algorithmically distinct from the classic computation that controls orientation. Despite the different algorithms, the visual circuits that regulate walking speed overlap with those that regulate orientation. Taken together, our findings suggest that walking speed is controlled by a hierarchical computation that combines multiple motion detectors with distinct tunings. VIDEO ABSTRACT.

Keywords: Drosophila; behavioral algorithms; navigation; neural circuits; optomotor behavior; speed tuning; temporal frequency tuning; visual motion detection; visual processing; walking speed.

Figure 1.. Flies turn and slow in response to visual motion

Error patches represent standard error of the mean. Icons in the bottom left indicate the stimulus presented (outside) and the behavioral response measured (inside). (A) Behavioral responses were measured by tethering the fly above an air suspended ball and monitoring the rotation of the ball as visual stimuli were presented on 3 screens surrounding the fly. (B, C) Diagram of the stimuli and fly behavioral response for (B) rotational and (C) translational motion stimuli. (D) Fly turning velocity over time in response to clockwise (green, n=69), counterclockwise (orange, n=69), and counterphase (purple, n=19) sine wave gratings. Counterphase gratings are equal to the sum of clockwise and counterclockwise stimuli. Stimulus is presented during gray shaded region. (E) As in D but measuring the fly’s walking speed. (F) Fly turning velocity over time in response to front-to-back (FtB, green, n=18), back-to-front (BtF, brown, n=14) and counterphase (purple, n=19) sine wave gratings. Counterphase gratings are equal to the sum of FtB and BtF stimuli. Stimulus is presented during gray shaded region. (G) Same as in F but measuring the fly’s walking speed. (H) Mean fly turning to rotational sine wave gratings (green, orange, n=69) and counterphase gratings (purple, n=19) at a variety of temporal frequencies. Data colored as in (D). (I) Same as in H but measuring the fly’s walking speed. (J) Mean fly turning to FtB (green, n=18) and BtF (brown, n=14) sine wave gratings and counterphase gratings (purple, n=19) at a variety of temporal frequencies. Data colored as in (E). (K) Same as in J but measuring the fly’s walking speed. Throughout, error patches represent standard error of the mean. See also Figure S1 and Supplemental Movie M1.

Figure 2.. Slowing to visual motion stabilizes walking speed

Error patches represent standard error of the mean. (A) Flies were presented with translational sine wave gratings with velocity determined by the walking speed of the fly. The gain relating the visual stimulus to the walking speed of the fly was set to 1 during the pre-stimulus interval, and then transiently changed to ±1/9 or ±9 during the stimulus presentation. Different gains correspond to different visual stimulus speeds for a given walking speed (top). Gain of 1 corresponded to 18 °/s for 1 mm/s walking speed and was changed during gray shaded region (bottom). Dotted lines indicate negative gains. n=29. (B) Flies were placed in a one-dimensional closed-loop environment, consisting of a hallway with an hourglass narrowing (top). Mean fly locations are plotted every 400 ms (top). Fly walking speed is plotted as a function of position in the hallway (bottom). n=35. (C) Schematic of the model of fly walking behavior in closed-loop. Walking forward generates a visual flow field that is determined by distances in the environmental. The fly changes its walking speed based on the visual flow. (D) Simple model of fly walking behavior in closed-loop. Open-loop slowing responses (Fig. 1K) for FtB (green) and BtF (brown) are plotted as a function of stimulus velocity. Natural stimulus gain (indicating the visual velocity experienced for a given fly walking speed) for environments with distant (pink), intermediate (blue), and close (yellow) objects. Stable fixed points are indicated by black circles. Black arrows indicate the change in walking speed for fluctuations near the intermediate distance fixed point. See STAR Methods for a detailed analysis. (E) Predictions of the closed-loop model of fly behavior, colored as in (A). (F) Prediction of the closed-loop model of fly behavior for the hourglass hallway experiment in (B). See also Figure S2 and Supplemental Movie M2.

Figure 3.. The slowing response is speed-tuned while the turning response is temporal-frequency-tuned

(A) Lines of equal temporal frequency (TF) (orange) and velocity (purple) shown in log-log spatiotemporal frequency space. Darker lines indicate greater velocities and temporal frequencies. (B) Spatiotemporal response of a TF-tuned model. Black circles mark the TF of the maximal response for each wavelength. Gold line is the spatiotemporal slope (STS) (see STAR Methods). (C) Spatiotemporal response of a speed-tuned model. Plot features are as in B. (D) Mean fly turning (i) and slowing (ii, iii) to sine wave gratings as a function of spatial and temporal frequency. Positive/negative spatial frequencies indicate rightward/leftward (i, ii) or front-to-back/back-to-front (iii) sine waves. Icons on the left indicate the stimulus presented (outside) and the behavioral response measured (inside). Black isoresponse lines are plotted every 10 °/s for turning (i) and every 0.2 fold change for walking speed (ii, iii). Black circles mark the TF of the maximal response for each wavelength and only reported when the maxima occurs within the TF range measured. Gold line is the spatiotemporal slope (STS). (i, ii) n=467. (iii) FtB n=124. BtF n=104. (E) TF at which the response is maximal plotted as a function of spatial wavelength. Error bars are standard error of the mean. Dashed lines indicate average TF or average velocity across all maxima. When plotting TF against spatial wavelength, lines of equal TF have slope 0 while lines of equal velocity are proportional to inverse spatial wavelength. (F) The log likelihood ratio of TF-tuned to speed-tuned models (see STAR Methods). Positive values indicate that a TF-tuned model is more likely while negative values indicate that a velocity-tuned model is more likely. Error bars are 95% confidence intervals and asterisks represent significant difference from 0 at α=0.05. (G) STS of plots in D, where a value of 0 corresponds to perfect TF-tuning and 1 corresponds to perfect speed-tuning (see STAR Methods). Error bars are 95% confidence intervals. See also Figures S3 and S4.

Figure 4.. Visual control of slowing and turning requires overlapping circuits

Synaptic transmission was silenced acutely by expression of shibire^ts using the GAL4/UAS system. (A) Schematic of the fly optic neuropils, with silenced neuron types crossed out. In this diagram, light is detected by photoreceptors (PRs) at top and visual information is transformed as it moves down through the neuropils. (B) Average fly response as a function of spatial and temporal frequency. Control is the average of the neuron-GAL4/+ and UAS-shibire/+ genetic controls (see STAR Methods). Black isoresponse lines are plotted every 0.2 fold change in walking speed. Black circles mark the TF of the maximal response for each wavelength. The gold line is the spatiotemporal slope (STS). Shibire control FtB n=274, BtF n=247 (i-iv). GAL4 control: (i) FtB n=109, BtF n=115. (ii) FtB n=83, BtF n=98. (iii) FtB n=121, BtF n=116. (iv) FtB n=95, BtF n=105. (C) Fly response when each cell type is silenced by expressing shibire under the GAL4 driver. (i) FtB n=126, BtF n=146. (ii) FtB n=134, BtF n=126. (iii) FtB n=120, BtF n=131. (iv) FtB n=99, BtF n=96. (D) Maximal slowing response of each genotype across all spatiotemporal frequencies, where 0 represents no walking speed modulation and 1 represents stopping completely. GAL4/+ is in dark gray, shibire^ts/+ is in light gray, and GAL4>shibire^ts is in red. Error bars are 95% confidence intervals and asterisks represent significant difference from both controls at α=0.05. (E) Spatiotemporal slope (STS) for each map, where 0 corresponds to perfect TF-tuning and 1 corresponds to perfect speed-tuning. GAL4/+ is in dark gray, shibire^ts/+ is in light gray, and GAL4>shibire^ts is in gold. Error bars are 95% confidence intervals and asterisks represent significant difference from both controls at α=0.05. See also Figure S4 and Table S3.

Figure 5.. Elementary motion detectors T4 and T5 are temporal-frequency-tuned

(A) Diagram of two-photon imaging setup. (B) Image of the lobula plate with T4 and T5 FtB and BtF regions of interest (ROIs) highlighted. (C, D) Responses of T4 (C, n=7) and T5 (D, n=8) to rotational sine wave gratings measured with GCaMP6f. Legend denotes the temporal frequency (TF) of the sine wave stimulus. (E, F) Mean calcium response of T4 and T5 (F, n=22) when presented with sine wave gratings of different spatiotemporal frequencies. Black isoresponse lines are plotted every 0.2 ΔF/F. Black circles mark the TF of the maximal response for each wavelength. Gold line is the spatiotemporal slope (STS). (G) The log likelihood ratio of TF-tuned and speed-tuned models of T4 and T5 responses (see STAR Methods). Positive values indicate that the TF-tuned model is more likely. Error bars are 95% confidence intervals and asterisks represent significant difference from 0 at α=0.05. (H) Spatiotemporal slope (STS) for T4 and T5 responses, where 0 represents to perfect TF-tuning and 1 represents to perfect speed-tuning (see STAR Methods). Error bars are 95% confidence intervals. (i) Imaging without pharmacological stimulation. T4, n = 20; T5, n=22. (ii) Imaging in the presence of octopamine agonist chlordimeform (CDM). T4, n = 13; T5, n=12. See also Figures S4 and S5.

Figure 6.. A model with multiple detectors is sufficient to explain the slowing response

Black isoresponse lines are plotted every 0.2-fold change for walking speed. Black circles mark the TF of the maximal response for each wavelength. Gold line is the spatiotemporal slope (STS). (A) Diagram of the behavioral setup from Fig. 1A. (B) Mean fly responses to sine wave gratings as a function of spatial and temporal frequency. Data is from Fig. 2D. Positive/negative spatial frequencies indicate front-to-back/back-to-front sine waves. FtB n=124. BtF n=104. (C) Mean fly walking to FtB (green, n=18) and BtF (brown, n=14) sine wave gratings and counterphase gratings (purple, n=19) at a variety of temporal frequencies. Error patches represent standard error of the mean. Data is from Fig 1G. (D) Schematic of the model consisting of two Hassenstein-Reichardt correlators (HRC) summed together, marked as 1 and 2. Their sum is marked as 3. Distance between the two visual inputs for each correlator is denoted by Φ. τ indicates a first-order low-pass filter. M denotes a multiplication of the two inputs. Σ indicates summation of the inputs. ∣·∣ indicates taking full-wave rectifying the signal. (E) The model’s average response as a function of spatial and temporal frequency. Positive/negative spatial frequencies indicate front-to-back/back-to-front sine waves. (F) Mean model response to FtB sine wave, BtF sine wave, and counterphase gratings at a spatial wavelength of 45°. Colors the same as (C). (G) Average spatiotemporal frequency response of each of the two HRC’s individually (left, center). Average spatiotemporal frequency response of the two correlators summed before taking the magnitude (right). Red indicates a positive response, blue indicates a negative response. Numbers correspond to (D). See also Figures S4 and S6 and Table S5.