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• W4229071878 abstract "•HS cells receive stride-coupled signals via ascending neurons•The stride-coupled signals reflect an internal motor context•Motor context modulates HS cells at multiple timescales•HS cells drive rapid steering depending on motor context Flexible mapping between activity in sensory systems and movement parameters is a hallmark of motor control. This flexibility depends on the continuous comparison of short-term postural dynamics and the longer-term goals of an animal, thereby necessitating neural mechanisms that can operate across multiple timescales. To understand how such body-brain interactions emerge across timescales to control movement, we performed whole-cell patch recordings from visual neurons involved in course control in Drosophila. We show that the activity of leg mechanosensory cells, propagating via specific ascending neurons, is critical for stride-by-stride steering adjustments driven by the visual circuit, and, at longer timescales, it provides information about the moving body’s state to flexibly recruit the visual circuit for course control. Thus, our findings demonstrate the presence of an elegant stride-based mechanism operating at multiple timescales for context-dependent course control. We propose that this mechanism functions as a general basis for the adaptive control of locomotion. Flexible mapping between activity in sensory systems and movement parameters is a hallmark of motor control. This flexibility depends on the continuous comparison of short-term postural dynamics and the longer-term goals of an animal, thereby necessitating neural mechanisms that can operate across multiple timescales. To understand how such body-brain interactions emerge across timescales to control movement, we performed whole-cell patch recordings from visual neurons involved in course control in Drosophila. We show that the activity of leg mechanosensory cells, propagating via specific ascending neurons, is critical for stride-by-stride steering adjustments driven by the visual circuit, and, at longer timescales, it provides information about the moving body’s state to flexibly recruit the visual circuit for course control. Thus, our findings demonstrate the presence of an elegant stride-based mechanism operating at multiple timescales for context-dependent course control. We propose that this mechanism functions as a general basis for the adaptive control of locomotion. Adaptive behavior—behavior that enhances survival in complex environments—depends on the capacity of the central nervous system to flexibly engage neural networks for motor control (Dickinson et al., 2000Dickinson M.H. Farley C.T. Full R.J. Koehl M.A. Kram R. Lehman S. How animals move: an integrative view.Science. 2000; 288: 100-106Crossref PubMed Scopus (1092) Google Scholar; Dürr, 2005Dürr V. Context-dependent changes in strength and efficacy of leg coordination mechanisms.J. Exp. Biol. 2005; 208: 2253-2267Crossref PubMed Scopus (38) Google Scholar; Wolpert and Ghahramani, 2000Wolpert D.M. Ghahramani Z. Computational principles of movement neuroscience.Nat. Neurosci. 2000; 3: 1212-1217Crossref PubMed Scopus (1370) Google Scholar). Importantly, this flexibility operates according to internal contexts that can be defined by physiological needs (Augustine et al., 2020Augustine V. Lee S. Oka Y. Neural control and modulation of thirst, sodium appetite, and hunger.Cell. 2020; 180: 25-32Abstract Full Text Full Text PDF PubMed Scopus (26) Google Scholar; Bargmann, 2012Bargmann C.I. Beyond the connectome: how neuromodulators shape neural circuits.BioEssays. 2012; 34: 458-465Crossref PubMed Scopus (280) Google Scholar), past experience (Palmer and Kristan, 2011Palmer C.R. Kristan W.B. Contextual modulation of behavioral choice.Curr. Opin. Neurobiol. 2011; 21: 520-526Crossref PubMed Scopus (49) Google Scholar; Khan and Hofer, 2018Khan A.G. Hofer S.B. Contextual signals in visual cortex.Curr. Opin. Neurobiol. 2018; 52: 131-138Crossref PubMed Scopus (35) Google Scholar; Maren et al., 2013Maren S. Phan K.L. Liberzon I. The contextual brain: implications for fear conditioning, extinction and psychopathology.Nat. Rev. Neurosci. 2013; 14: 417-428Crossref PubMed Scopus (917) Google Scholar), and by predictions of the state of the body given the behavioral goals. Because movement is rarely executed as intended without online adjustments (Shadmehr et al., 2010Shadmehr R. Smith M.A. Krakauer J.W. Error correction, sensory prediction, and adaptation in motor control.Annu. Rev. Neurosci. 2010; 33: 89-108Crossref PubMed Scopus (991) Google Scholar), the internal context defined by signals associated with behavioral goals and the current body state, here defined as “motor context,” is critical for high-performance movement control. Motor context emerges from diverse streams of information across different timescales; however, how the central nervous system signals it to flexibly recruit circuits for online movement adjustments remains poorly understood (Figure 1A). The emergence of an internal motor context likely depends on recurrent interactions between brain premotor centers and the spinal cord across different timescales (Figure 1A). Coupling of ascending signals in the mammalian brain to individual strides suggests that supraspinal circuits receive immediate information about the walking state (Orlovsky et al., 1999Orlovsky G.N. Deliagina T.G. Grillner S. Neuronal Control of Locomotion: From Mollusk to Man. Oxford University Press, 1999Crossref Google Scholar). However, the exact nature and function of these modulations remains unknown, partly due to the highly distributed structure of mammalian brain premotor circuits and to the limited understanding of how activity within these circuits contributes to walking. The compact central nervous system of Drosophila melanogaster provides a powerful model in which to study the mechanisms and timescales through which motor context emerges and impacts neural activity and walking control. Importantly, and in contrast to internal physiological states, signals related to the state of the body can be directly measured by quantitative analysis of behavior and neural physiology, thus allowing to dissect the nature of motor context and its effect on motor control. In insects, the posterior slope (PS, Figure 1B), a premotor region with strong multisensory convergence (Strausfeld and Bacon, 1983Strausfeld N.J. Bacon J.P. Multimodal convergence in the central nervous system of dipterous insects.Fortschr. Zool. 1983; 28: 47-76Google Scholar), provides output to several types of descending neurons (DNs) involved in steering (Namiki and Kanzaki, 2016Namiki S. Kanzaki R. Comparative neuroanatomy of the lateral accessory lobe in the insect brain.Front. Physiol. 2016; 7: 244Crossref PubMed Scopus (29) Google Scholar; Rayshubskiy et al., 2020Rayshubskiy A. Holtz S. D’Alessandro I. Li A. Vanderbeck Q. Haber I. Gibb P. Wilson R. Neural circuit mechanisms for steering control in walking Drosophila.BioRxiv. 2020; : 1-50Google Scholar). The PS receives inputs from higher-order centers, such as the lateral accessory lobe (LAL), from the ventral nerve cord (VNC, the insect analog of the spinal cord) via ascending neurons (ANs), and from visual pathways, including the lobula plate (LP) (Figure 1B) (Namiki and Kanzaki, 2016Namiki S. Kanzaki R. Comparative neuroanatomy of the lateral accessory lobe in the insect brain.Front. Physiol. 2016; 7: 244Crossref PubMed Scopus (29) Google Scholar; Pierantoni, 1976Pierantoni R. A look into the cock-pit of the fly. The architecture of the lobular plate.Cell Tissue Res. 1976; 171: 101-122Crossref PubMed Scopus (80) Google Scholar; Scheffer et al., 2020Scheffer L. Xu C.S. Januszewski M. Lu Z. Takemura S. Hayworth K. Huang G. Shinomiya K. Maitin-Shepard J. Berg S. et al.A connectome and analysis of the adult Drosophila central brain.eLife. 2020; 9: e57443Crossref PubMed Google Scholar; Strausfeld, 1976Strausfeld N.J. Atlas of an Insect Brain. Springer-Verlag, 1976Crossref Google Scholar). Therefore, neurons projecting to PS are likely involved in brain-body interactions for context-dependent motor control, but their activity has not been characterized at multiple timescales in relation to the task at play, behavioral goals, or the body state. One class of such premotor neurons projecting to the PS is the population of horizontal system (HS) cells in the LP, visual motion sensitive neurons that are well poised to detect head and body yaw rotations (Hausen, 1984Hausen K. The Lobula-complex of the fly: structure, function and significance in visual behavior.Photoreception and Vision in Invertebrates. Plenum Press, New York and London1984Crossref Google Scholar; Schnell et al., 2010Schnell B. Joesch M. Forstner F. Raghu S.V. Otsuna H. Ito K. Borst A. Reiff D.F. Processing of horizontal optic flow in three visual interneurons of the Drosophila brain.J. Neurophysiol. 2010; 103: 1646-1657Crossref PubMed Scopus (98) Google Scholar) and that are accessible to physiological recordings and manipulations during walking (Figure 1B) (Fujiwara et al., 2017Fujiwara T. Cruz T.L. Bohnslav J.P. Chiappe M.E. A faithful internal representation of walking movements in the Drosophila visual system.Nat. Neurosci. 2017; 20: 72-81Crossref PubMed Scopus (54) Google Scholar; Kim et al., 2015Kim A.J. Fitzgerald J.K. Maimon G. Cellular evidence for efference copy in Drosophila visuomotor processing.Nat. Neurosci. 2015; 18: 1247-1255Crossref PubMed Scopus (92) Google Scholar; Schnell et al., 2014Schnell 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. 2014; 111: 5700-5705Crossref PubMed Scopus (49) Google Scholar; Suver et al., 2012Suver M.P. Mamiya A. Dickinson M.H. Octopamine neurons mediate flight-induced modulation of visual processing in Drosophila.Curr. Biol. 2012; 22: 2294-2302Abstract Full Text Full Text PDF PubMed Scopus (105) Google Scholar). Consistent with their proposed role on course and gaze stabilization, the activity of HS cells is suppressed in anticipation to voluntary rapid turns (Fenk et al., 2021Fenk L.M. Kim A.J. Maimon G. Suppression of motion vision during course-changing, but not course-stabilizing, navigational turns.Curr. Biol. 2021; 31: 4608-4619Abstract Full Text Full Text PDF PubMed Scopus (5) Google Scholar; Kim et al., 2015Kim A.J. Fitzgerald J.K. Maimon G. Cellular evidence for efference copy in Drosophila visuomotor processing.Nat. Neurosci. 2015; 18: 1247-1255Crossref PubMed Scopus (92) Google Scholar, Kim et al., 2017Kim A.J. Fenk L.M. Lyu C. Maimon G. Quantitative Predictions Orchestrate Visual Signaling in Drosophila.Cell. 2017; 168: 280-294.e12Abstract Full Text Full Text PDF PubMed Scopus (44) Google Scholar; Cruz et al., 2021Cruz T.L. Malagón Pérez S. Chiappe M.E. Fast tuning of posture control by visual feedback underlies gaze stabilization in walking Drosophila.Curr. Biol. 2021; 31 (4596.e5–4607.e5)Abstract Full Text Full Text PDF Scopus (3) Google Scholar), suggesting that HS cells contribute to behavior in a task-specific manner. Rapid turns are only one of many maneuvers the fly executes while walking. More recently, we found that in the context of slower rotations during forward walking, HS cells respond to the direction of the angular velocity (Va) of the fly (Fujiwara et al., 2017Fujiwara T. Cruz T.L. Bohnslav J.P. Chiappe M.E. A faithful internal representation of walking movements in the Drosophila visual system.Nat. Neurosci. 2017; 20: 72-81Crossref PubMed Scopus (54) Google Scholar) and integrate this extra-retinal information with visual motion signals to faithfully estimate body rotations (Figure 1B). Moreover, unilateral activation of HS cells promotes ipsilateral steering (Busch et al., 2018Busch C. Borst A. Mauss A.S. Bi-directional control of walking behavior by horizontal optic flow sensors.Curr. Biol. 2018; 28: 4037-4045.e5Abstract Full Text Full Text PDF PubMed Scopus (13) Google Scholar; Fujiwara et al., 2017Fujiwara T. Cruz T.L. Bohnslav J.P. Chiappe M.E. A faithful internal representation of walking movements in the Drosophila visual system.Nat. Neurosci. 2017; 20: 72-81Crossref PubMed Scopus (54) Google Scholar; Haikala et al., 2013Haikala V. Joesch M. Borst A. Mauss A.S. Optogenetic control of fly optomotor responses.J. Neurosci. 2013; 33: 13927-13934Crossref PubMed Scopus (52) Google Scholar), suggesting a direct contribution to course control. However, at which timescales and in which motor contexts activity in HS cells is recruited for course control has not been explored yet. Interestingly, HS cell activity also correlates with the fly’s forward velocity (Vf) (Fujiwara et al., 2017Fujiwara T. Cruz T.L. Bohnslav J.P. Chiappe M.E. A faithful internal representation of walking movements in the Drosophila visual system.Nat. Neurosci. 2017; 20: 72-81Crossref PubMed Scopus (54) Google Scholar), but the function of this signal has remained unclear (Figure 1B). One possibility is that the speed-related signal provides information about motor context, either related to the behavioral goals of the fly (“run forward”) or to the current state of the body (“walking at high speed”), or both. We therefore propose that this visuomotor circuit is very well suited to study the nature of motor context and its effect on neural activity and behavior. Here, we combine whole-cell patch recordings in walking flies with optogenetics and targeted suppression of chemical synapses to examine the emergence of motor context and its role on the mapping between neural activity dynamics and specific aspects of walking control. We show that a single source, the stride, operating at multiple timescales provides an elegant solution to flexibly engage a functional network in online movement adjustments within a continuous behavior that is rarely in steady state. These findings represent a general mechanism by which bidirectional interactions between the peripheral nervous system and brain visual circuits contribute to an adaptive and high-performance control of locomotion. HS cells are thought to contribute to course control when the fly actively maintains the direction of locomotion during walking at high speed (Figure 1B). If a Vf-related signal in HS cells functions as a motor context modulation, two properties should be observed. First, the selectivity of HS cells should not change with Vf. Second, manipulating HS-cell activity should lead to steering in a Vf-dependent manner. To test the first prediction, we examined the extra-retinal direction-selective properties of HS cells at different Vf by performing the whole-cell recordings of flies walking in darkness. We excluded visual stimulation in these experiments, since its presence influences the walking speed of the fly (Creamer et al., 2018Creamer M.S. Mano O. Clark D.A. Visual control of walking speed in drosophila.Neuron. 2018; 100 (1460.e6–1473.e6)Abstract Full Text Full Text PDF PubMed Scopus (28) Google Scholar). The activity of HS cells was selective to the fly’s direction of rotations independent of Vf, but the cells were more depolarized under high versus low Vf (Figure 1C). Thus, Vf modulates the activity of HS cells without changing their tuning. To test the second prediction, a Vf-dependent effect of the activity of HS cells on their behaviors, we leveraged previous work showing that unilateral activation induces ipsiversive rotations (Busch et al., 2018Busch C. Borst A. Mauss A.S. Bi-directional control of walking behavior by horizontal optic flow sensors.Curr. Biol. 2018; 28: 4037-4045.e5Abstract Full Text Full Text PDF PubMed Scopus (13) Google Scholar; Fujiwara et al., 2017Fujiwara T. Cruz T.L. Bohnslav J.P. Chiappe M.E. A faithful internal representation of walking movements in the Drosophila visual system.Nat. Neurosci. 2017; 20: 72-81Crossref PubMed Scopus (54) Google Scholar) and reasoned that the opposite, unilateral silencing, should induce a contraversive rotation. To induce unilateral silencing, we expressed the histamine-gated chloride channel ort (Liu and Wilson, 2013Liu W.W. Wilson R.I. Transient and specific inactivation of Drosophila neurons in vivo using a native ligand-gated ion channel.Curr. Biol. 2013; 23: 1202-1208Abstract Full Text Full Text PDF PubMed Scopus (18) Google Scholar) in HS cells and locally applied histamine at the right-side axon terminals in the PS, contingent on Vf (Figure 1D). Histamine application led to a prominent inhibition in right HS cells both at high and low Vf. However, in 9 out of 11 flies, the inhibition of HS cells led to an overt contraversive rotation only when flies walked at high Vf (Figure 1E). Importantly, the perturbation in neural activity and the effect on behavior was observed exclusively in experimental and not in control flies, in which HS cells did not exogenously express Ort (Figures 1F and S1A). Thus, these results cannot be explained by endogenous histamine receptor activity within the PS. Finally, the effect on behavior was not induced by inhibiting other neurons also labeled in the transgenic line (Figures S1B and S1C). We conclude that the Vf-related modulation in HS cells represents a motor context that flexibly recruits the neurons’ activity to steering adjustments. In a continuous behavior such as walking, Vf can fluctuate at different timescales, reflecting either slow (over seconds) changes in motor programs or behavioral goals or faster fluctuations (at a stride timescale) in reactive forces due to inevitable perturbations (Figure 1A) (Chun et al., 2021Chun C. Biswas T. Bhandawat V. Drosophila uses a tripod gait across all walking speeds, and the geometry of the tripod is important for speed control.eLife. 2021; 10: 1-47Crossref Scopus (3) Google Scholar; DeAngelis et al., 2019DeAngelis B.D. Zavatone-Veth J.A. Clark D.A. The manifold structure of limb coordination in walking Drosophila.eLife. 2019; 8: 1-34Crossref Google Scholar; Mendes et al., 2013Mendes C.S. Bartos I. Akay T. Márka S. Mann R.S. Quantification of gait parameters in freely walking wild type and sensory deprived Drosophila melanogaster.eLife. 2013; 2: e00231PubMed Google Scholar). Thus, if HS cells are recruited for rapid steering adjustments, their activity should not only be modulated over seconds, reflecting the overall state of Vf, but also at timescales of a stride. When the fly occasionally maintained a stable heading with high Vf and low Va during spontaneous walking (Figures 2A and 2B , gray shadow), the activity of HS cells mapped onto these virtual straight paths revealed fast periodic oscillations (Figure 2C). This observation suggested the presence of a fast modulation by Vf, an idea we tested by calculating the coherence between neural activity dynamics (Vm) and Vf or Va, a measure of power transfer between signals. At high-speed walking frequencies on the ball, with a period of about 160 ms (>5 Hz), the coherence was dominated by Vf, while at lower frequencies (<5 Hz) it was dominated by Va (Figure 2D). These results show that Vf-related signals are present in the activity dynamics of HS cells at both a stride timescale (>5 Hz) and over seconds (Figure 1). Because spontaneous walking on the ball is variable, we developed an optogenetics-based paradigm to promote high-speed walking (Figures 2E and 2F). We expressed the light-gated cation channel CsChrimson in interneurons promoting forward runs, the bolt protocerebral neurons (BPNs, Figure 2E) (Bidaye et al., 2020Bidaye S.S. Laturney M. Chang A.K. Liu Y. Bockemühl T. Büschges A. Scott K. Two brain pathways initiate distinct forward walking programs in drosophila.Neuron. 2020; 108 (469.e8–485.e8)Abstract Full Text Full Text PDF PubMed Scopus (17) Google Scholar). To prevent any visual response that might confound the Vf-related modulation, we used blind flies (Bloomquist et al., 1988Bloomquist B.T. Shortridge R.D. Schneuwly S. Perdew M. Montell C. Steller H. Rubin G. Pak W.L. Isolation of a putative phospholipase C gene of Drosophila, norpA, and its role in phototransduction.Cell. 1988; 54: 723-733Abstract Full Text PDF PubMed Scopus (508) Google Scholar). BPN activation induced high-speed walking with low Va (absolute mean ± SEM = 73.6 ± 3.0°/s, n = 19 flies). We will refer to this induced walking as “opto-runs.” Similar to that in spontaneous walking, during opto-runs HS-cell activity co-varied at high frequencies (5–10 Hz) with Vf and at low frequencies with Va. In addition, Va displayed a high-frequency (5–10 Hz) component (Figure 2G), which we will revisit later (Figure 5). Under visual feedback, opto-runs displayed lower course variability relative to darkness in flies with normal sight (Figure S2A), suggesting that these high-speed runs reflect an (induced) intention to walk straight (Cruz et al., 2021Cruz T.L. Malagón Pérez S. Chiappe M.E. Fast tuning of posture control by visual feedback underlies gaze stabilization in walking Drosophila.Curr. Biol. 2021; 31 (4596.e5–4607.e5)Abstract Full Text Full Text PDF Scopus (3) Google Scholar). Therefore, unexpected deviations from a stable course should recruit activity in steering-control networks, including HS cells. Together, these observations show that the opto-run paradigm is suitable to examine the interaction between activity in HS cells and strides during high-speed walking. The correlation between Vm and Vf at high frequencies suggests that HS cells are modulated at stride timescale. To determine the relationship between the stride cycle and activity in HS cells, we tracked the three legs from the left side (Mathis et al., 2018Mathis A. Mamidanna P. Cury K.M. Abe T. Murthy V.N. Mathis M.W. Bethge M. DeepLabCut: markerless pose estimation of user-defined body parts with deep learning.Nat. Neurosci. 2018; 21: 1281-1289Crossref PubMed Scopus (883) Google Scholar) and recorded in simultaneous the membrane potential of HS cells (Vm), Vf and Va during opto-runs (Figures 3A, S2B, and S2C; Video S1). Vm was strongly coupled to the stride cycle (Figures 3B, S2D, and S2E), with a peak-to-trough amplitude ranging from 2 to 6 mV, which was never observed in quiescence (Figure 3C). Hereafter, to analyze the phase relation between the oscillatory dynamics in HS cells, Vf, and the stride cycle, we used Vm|5 Hz, the high-frequency component of Vm (Figure 2; see STAR Methods). https://www.cell.com/cms/asset/221e5fa8-c2d6-49d3-91c9-aa19542b0b79/mmc2.mp4Loading ... Download .mp4 (0.67 MB) Help with .mp4 files Video S1. Tracking of leg joints during opto-runs, related to Figures 3 and S2Example video showing the labels used to track two joints from the fly’s three legs of the left side. Color code indicates different labels: orange, hindleg femur-tibia joint; red, hindleg tibia-tarsus joint; light-green, middle leg femur-tibia joint; yellow, middle leg tibia-tarsus joint; dark-blue, foreleg femur-tibia joint; light-blue, foreleg tibia-tarsus joint. Vm|5 Hz oscillations were also observed in spontaneous walking under visual feedback (Figure 3D), and both in spontaneous- and opto-runs, each leg displayed a specific phase relation with Vm|5 Hz, which depended on the neural recording side (Figures 3D–3F and S2D–S2F). For example, the early stance phase of the left front leg coincided with the peak of the right side and the trough of the left side HS cells’ oscillations (Figures 3D–3F). The phase relation of the front versus middle legs with the contralateral Vm|5 Hz was shifted by about 120° (Figure 3E), consistent with a tetrapod-like gait configuration (DeAngelis et al., 2019DeAngelis B.D. Zavatone-Veth J.A. Clark D.A. The manifold structure of limb coordination in walking Drosophila.eLife. 2019; 8: 1-34Crossref Google Scholar; Mendes et al., 2013Mendes C.S. Bartos I. Akay T. Márka S. Mann R.S. Quantification of gait parameters in freely walking wild type and sensory deprived Drosophila melanogaster.eLife. 2013; 2: e00231PubMed Google Scholar; Wosnitza et al., 2013Wosnitza A. Bockemühl T. Dübbert M. Scholz H. Büschges A. Inter-leg coordination in the control of walking speed in Drosophila.J. Exp. Biol. 2013; 216: 480-491Crossref PubMed Scopus (90) Google Scholar). The hind leg movement was less correlated to Vm|5 Hz (Figures 3E and S2G–S2I) and therefore was not the focus of further analysis. Altogether, these observations revealed a fixed relation between a specific leg’s stride cycle and the contralateral Vm|5 Hz, and an antiphase relation between the activity of left and right HS cells. The oscillations in Vm|5 Hz could originate from a mechanical coupling between forces exerted by legs and brain motion, or as a direct consequence of BPN activation. To address the first possibility, we recorded the activity in the vertical system (VS) cells, which reside close by HS cells but display no modulation by Vf (Fujiwara et al., 2017Fujiwara T. Cruz T.L. Bohnslav J.P. Chiappe M.E. A faithful internal representation of walking movements in the Drosophila visual system.Nat. Neurosci. 2017; 20: 72-81Crossref PubMed Scopus (54) Google Scholar). We found that their activity was not coupled to the stride cycle (Figures S2J–S2L). To test whether activation of BPNs directly induces oscillations in HS cells, we momentarily decoupled BPN activity from walking by stopping the airflow of the ball while activating BPNs. Stopping the ball induced uncoordinated leg movements, which were revealed by a decrease in the periodicity of the autocorrelation of the leg signal (“leg motion coupling,” Figure S3). When walking was interrupted, Vm oscillations (for comparison, measured as the autocorrelation of the Vm signal, “Vm coupling”) decreased (Figure S3B). Overall, Vm coupling was strongly correlated with leg motion coupling (Figures S3A–S3C), indicating that activity of BPNs or postsynaptic neurons per se was not driving the rhythmic neural activity. Rather, the oscillations in HS cells may reflect leg kinematic parameters, such as joint positions. Indeed, HS cells were more depolarized when the femur-tibia or tibia-tarsus joint position at stance onset was more anterior (Figures S3D and S3E). These results suggest that oscillations in HS cells originate from periodic leg movements. A stride consists of sequential left and right steps typically coordinated in antiphase (DeAngelis et al., 2019DeAngelis B.D. Zavatone-Veth J.A. Clark D.A. The manifold structure of limb coordination in walking Drosophila.eLife. 2019; 8: 1-34Crossref Google Scholar; Mendes et al., 2013Mendes C.S. Bartos I. Akay T. Márka S. Mann R.S. Quantification of gait parameters in freely walking wild type and sensory deprived Drosophila melanogaster.eLife. 2013; 2: e00231PubMed Google Scholar; Wosnitza et al., 2013Wosnitza A. Bockemühl T. Dübbert M. Scholz H. Büschges A. Inter-leg coordination in the control of walking speed in Drosophila.J. Exp. Biol. 2013; 216: 480-491Crossref PubMed Scopus (90) Google Scholar). When the fly walks straight, the left-right pair contributes equally to acceleration, thus creating two peaks in Vf during the stride cycle (Figure S4A). In contrast, HS-cell activity displayed only a single peak per stride (Figure S4A), suggesting that one leg predominantly modulates their activity. To evaluate which leg (i.e., left versus right) is the major contributor, we focused on front legs since they modulated HS cells stronger than the middle legs (Figures S4B and S4C). When the fly drifted from a straight course, the relation between the stride cycle and Vf was single peaked. The peak of Vf occurred at the stance phase of the side dominating the acceleration and driving angular drifts (Figure S4D) and coincided with the peak of Vm|5 Hz only when the contralateral front leg dominated the acceleration (e.g., during contraversive rotations) (Figures S4D–S4F). Thus, the oscillations in HS cells seemed to reflect contralateral leg movement rather than fluctuations in Vf (Figure 2). Given the phase relation between Vm|5 Hz and the left front leg’s stride cycle (Figure 3F), HS cells may be hyperpolarized during the stance phase of the contralateral leg (Model 1; Figure S4G, left) or depolarized during the stance phase of the ipsilateral leg (Model 2; Figure S4G, right). Model 1 predicts that oscillations in HS cells and Vf should correlate strongly during left drifts, whereas the converse is predicted by Model 2. By design, simulations showed that either model replicated the observed phase relation between the stride cycle and Vm|5 Hz (Figure S4I; STAR Methods). However, Model 1 and not Model 2 replicated the relation between Vf and Vm|5 Hz under angular drift as observed in the data (Figures S4J and S4K). These results support a model in which a unilateral leg-related sensorimotor network configures activity in the contralateral HS cells to respond rapidly. To directly examine if neural signals from leg sensorimotor circuits contribute to the stride-coupled activity in HS cells, we perturbed chemical synaptic transmission in a large population of leg mechanosensory neurons via selective expression of tetanus toxin (Mendes et al., 2013Mendes C.S. Bartos I. Akay T. Márka S. Mann R.S. Quantification of gait parameters in freely walking wild type and sensory deprived Drosophila melanogaster.eLife. 2013; 2: e00231PubMed Google Scholar) (Figure 4A). Recordings from HS cells in experimental flies during spontaneous high-speed walking (>5 mm/s) showed that the stride-coupled dynamics were largely degraded, although not fully abolished (Figures 4B and 4C). Perturbations in signal transmission within leg sensorimotor circuits can lead to deficits in leg coordination that might indirectly perturb oscillations in Vm|5 Hz (Fujiwara et al., 2017Fujiwara T. Cruz T.L. Bohnslav J.P. Chiappe M.E. A faithfu" @default.
• W4229071878 created "2022-05-08" @default.
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• W4229071878 date "2022-07-01" @default.
• W4229071878 modified "2023-10-12" @default.
• W4229071878 title "Walking strides direct rapid and flexible recruitment of visual circuits for course control in Drosophila" @default.
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• W4229071878 doi "https://doi.org/10.1016/j.neuron.2022.04.008" @default.
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