Walking strides direct rapid and flexible recruitment of visual circuits for course control inDrosophila

Abstract

Flexible mapping between activity in sensory systems and movement parameters is a hallmark of successful motor control. This flexibility depends on 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 to control movement across timescales, we performed whole-cell patch recordings from visual neurons involved in course control in Drosophila. We demonstrate that the activity of leg mechanosensory cells, propagating via specific ascending neurons, is critical to provide a clock signal to the visual circuit for stride-by-stride steering adjustments and, at longer timescales, information on speed-associated motor context to flexibly recruit visual circuits for course control. Thus, our data reveal a stride-based mechanism for the control of high-performance walking operating at multiple timescales. We propose that this mechanism functions as a general basis for adaptive control of locomotion.

Ascending neurons convey behavioral state to integrative sensory and action selection centers in the brain

“…We expected that, unlike primary limb mechanosensory neurons, second-and higher-order ANs would more likely integrate and process proprioceptive and tactile sensory signals to encode high-level behavioral states. This remained unknown because previous studies of AN encoding [21][22][23] did not quantify movements at high enough resolution, or study more than a few ANs in total. To address this gap, with the data from our large-scale functional screen, we performed a linear regression analysis to quantify the degree to which the movements of individual joints, legs, pairs of legs, or epochs of high-level behaviors could explain the time-course of AN activity.…”

“…and that LAL-PS-ANs convey walking signals to the visual system [22]. Second, artificial activation of pairs of PER in ANs [23], and Moonwalker ANs [24] regulates action selection and behavioral persistence, respectively.…”

“…These studies support the hypothesis that ANs are a prominent source of behavioral state signals in the brain. First, microscopy recordings of AN terminals in the brain have shown that Lco2N1 and Les2N1D ANs are active during walking [21], and that LAL-PS-ANs convey walking signals to the visual system [22]. Second, artificial activation of pairs of PER in ANs [23], and Moonwalker ANs [24] regulates action selection and behavioral persistence, respectively.…”

Visual and motor signatures of locomotion dynamically shape a population code for feature detection in Drosophila

“…Recent work demonstrates that locomotor signals are prevalent throughout the Drosophila brain, including in the visual system (Aimon et al, 2019;Brezovec et al, 2022;Schaffer et al, 2021), but has been examined most extensively in circuits involved in elementary motion detection and widefield motion encoding. Behavioral activity has been shown to modulate response gain in widefield motion detecting lobula plate tangential cells (LPTCs) and some of their upstream circuitry (Chiappe et al, 2010;Kohn et al, 2021;Maimon et al, 2010;Strother et al, 2018;Suver et al, 2012), and LPTC membrane potential tightly tracks walking behavior, even in the absence of visual stimulation (Cruz et al, 2021;Fujiwara et al, 2017;Fujiwara et al, 2022). During flight, efference-copy based modulation of LPTC membrane potential has been proposed to cancel expected visual motion due to self-generated turns (Fenk et al, 2021;Kim et al, 2015;Kim et al, 2017).…”

“…For example, the motor commands that initiate primate saccades produce efference copy signals that are associated with neural gain changes and a perceptual decrease in sensitivity called saccadic suppression (Binda and Morrone, 2018;Bremmer et al, 2009;Wurtz, 2018). In flies, efference copy signals can cancel expected motion in widefield motion sensitive neurons during flight (Fenk et al, 2021;Kim et al, 2015), but can also provide independent information about intended movements (Fujiwara et al, 2017;Fujiwara et al, 2022;Cruz et al, 2021). In this way, neural response gain is modulated so that motion sensitive neurons encode unexpected deviations in motion signals after accounting for behavior.…”