Neuromodulatory selection of motor neuron recruitment patterns in a visuomotor behavior increases speed

Summary

Animals generate locomotion at different speeds to suit their behavioral needs. Spinal circuits generate locomotion at these varying speeds by sequential activation of different spinal interneurons and motor neurons. Larval zebrafish can generate slow swims for prey capture and exploration by activation of secondary motor neurons and much faster and vigorous swims during escapes and struggles via the additional activation of primary motor neurons. Neuromodulators are known to alter motor output of spinal circuits yet their precise role in speed regulation is not understood well. Here, in the context of optomotor response (OMR), an innate, evoked locomotor behavior, we show that dopamine (DA) provides an additional layer to regulation of swim speed in larval zebrafish. Activation of D1-like receptors increases swim speed during OMR in free-swimming larvae. By analysing tail bend kinematics in head-restrained larvae, we show that the increase in speed is actuated by larger tail bends. Whole cell patch clamp recordings from motor neurons reveal that during OMR, typically only secondary motor neurons are active while primary motor neurons are quiescent. Activation of D1-like receptors increases intrinsic excitability and excitatory synaptic drive in primary and secondary motor neurons. These actions result in greater recruitment of motor neurons during OMR. Our findings provide an example of neuromodulatory reconfiguration of spinal motor neuron speed modules such that members are selectively recruited and motor drive is increased to effect changes in locomotor speed.

Graphical abstract.

Introduction

Survival for most animals depends on their ability to adapt speed, gait and direction of movement quickly in response to sensory stimuli. In vertebrates, these processes are controlled by the concerted activity of distributed circuits in the brain and the spinal cord. In particular, the regulation of speed by spinal locomotor circuits has received much attention recently. The ability to genetically label specific neuronal populations and to target them for imaging or electrophysiology has allowed us to identify recruitment patterns of interneurons and motor neurons at different speeds. Studies in mice and zebrafish have identified subtypes of spinal interneurons and motor neurons that are selectively recruited at different speeds of locomotion [1–8]. These interneurons and motor neurons make selective synaptic connections among them and are thought to constitute ‘slow’ or ‘fast’ network modules, that are sequentially recruited as the locomotor speed increases [9,10]. Thus, behaviors such as escapes, which involve fast swimming, are generated by the fast module, and spontaneous swimming behaviors, occurring at much lower swim frequencies are controlled by the slow module [11].

Although this modular view of spinal network operation is widely acknowledged [12,13], we also know that the spinal network is the target of a variety of neuromodulators [14–17]. Neuromodulators have been shown to fuse independent circuits and to construct ‘de novo’ circuits from cells belonging to disparate circuits [18,19]. We wished to understand if swim speed regulation in zebrafish larvae is subject to neuromodulation and if yes, whether the rules for modular recruitment are altered by neuromodulators.

Dopamine has long been known to be a key neuromodulator of motor circuits [17,20] and is critical for activation, maturation and modulation of locomotor patterns across invertebrates and vertebrates [21–26]. In most previous studies, the effect of dopamine on locomotor circuits was studied in isolated spinal cord preparations using ventral root recordings of fictive locomotion (eg., lamprey: [27]; Xenopus: [28]; mouse: [29–31]). However, little is known about the effects of dopaminergic modulation on the activity of identified spinal neurons, and about the role of dopamine modulation of spinal locomotor networks in a behavioral context.

We chose to study speed regulation and its dopaminergic modulation, during the optomotor response (OMR), an innate behaviour evoked by whole-field visual motion, to which zebrafish larvae respond by turning towards and moving in the direction of perceived motion. By adjusting their locomotor speed to match the speed of the perceived motion, larvae try to maintain a stable position with respect to their surroundings [32,33]. In zebrafish, dopaminergic input from the diencephalon to the spinal cord develops early [34] and is known to regulate developmental maturation of swim motor patterns [24]. However, the spinal mechanisms by which speed is controlled during OMR have thus far not been investigated.

We used a combination of behavioral monitoring in free-swimming larvae, kinematic characterization in head-restrained larvae and whole-cell patch clamping in immobilized larvae to ask how speed is controlled during OMR and how it is modulated at the neuronal level. Here, we show that dopamine acting via D1-like receptors (D1-like-R) increases the speed of swimming during OMR by increasing the extent of tail bending. This in turn is caused by two factors: (1) increased firing of action potentials in motor neurons of the slow module, typically recruited during OMR and (2) novel recruitment of motor neurons belonging to the fast module, not typically active during OMR. The observed increased motor neuronal recruitment is a result of modulation of intrinsic and synaptic properties of motor neurons. Thus, dopamine selectively activates and recruits neurons from disparate spinal modules to increase speed. Our results suggest that activity and recruitment pattern of neurons in these circuit modules are not only defined by their cellular properties and synaptic connectivity. Neuromodulatory inputs can dramatically alter the dynamics of these modules by recruiting neurons that would have otherwise not participated under a given context.

Results

D1-like-R activation increases swim speed during OMR

OMR was evoked in freely swimming zebrafish larvae between 6-7 days post fertilization (dpf) by presenting square-wave gratings moving in a clockwise direction from below (Figure 1A, Video S1). Zebrafish larvae respond by following the direction of the stimulus and matching their swim speed with that of the moving grating [33]. Larval centroid was tracked to extract kinematic parameters.

Figure 1. D1-like-R activation increases swim speed during OMR in free-swimming zebrafish larvae.

(A) Schematic of experimental set up. OMR was evoked in freely swimming zebrafish larvae (6-7 dpf) by presenting radial gratings moving in a clockwise direction on a screen below the arena. Zebrafish larvae respond to the stimulus by swimming in the direction of moving grating. Videos were acquired from above and larval centroid was tracked. (B) Left, instantaneous speed of a representative larva during a trial. Right, zoomed view of region marked with the orange rectangle showing characteristic intermittent swimming pattern. Brief period of activity represents individual swim bouts (highlighted by line on top) and is followed by a period of no tail movement. (C) Overlaid tracked centroid for a trial duration of 60 seconds showing trajectory of a representative larva before (Control) and after bath application of 20 μM D1-like-R agonist, SKF-38393. Scale bar represents 10 mm. (D-F) Paired plots for average speed, average bout speed and average bout distance respectively, before (black) and after (blue) application of D1-like-R agonist. (G) Overlaid tracked centroid of a representative larva for a trial duration of 60 seconds before (Control) and after bath application of 20 μM D1-like-R antagonist, SCH-23390. Scale bar represents 10 mm. (H-J) Paired plots for average speed, average bout speed and average bout distance respectively, before (black) and after (red) application of D1-like-R antagonist. N_SKF-38393=14 larvae, N_SCH-23390=9 larvae, Wilcoxon signed-rank test; ** p<0.01. See also Video S1.

We first compared average swim speed (total distance swum/trial duration of 60s) during OMR before and after bath application of 20 μM D1-like-R agonist, SKF-38393. Larvae swam with higher average swim speed post D1-like-R activation (Figure 1C, D, Video S1). Zebrafish larvae swim intermittently in a beat-and-glide pattern where brief periods of discrete tail oscillations (bout) are followed by a period of no tail movement [35]. To ask if modulation of speed occurred during bouts, we further segmented tracked data to identify individual swim bouts (Figure 1B, see Methods). We then asked if D1-like-R activation increases speeds achieved during bouts and compared average bout speed before and after bath application of D1-like-R agonist. Average bout speed increased (Figure 1E) resulting in greater distance travelled per bout (Figure 1F) post application of D1-like-R agonist.

To ascertain that swim speed during OMR in free swimming larvae was indeed modulated by D1-like-R’s, we also compared these parameters before and after bath application of 20 μM D1-like-R antagonist, SCH-23390. Average swim speed decreased post application of D1-like-R antagonist (Figure 1G, H). Consistently, a decrease in average bout speed (Figure 1I) and average distance travelled per bout (Figure 1J) were observed post application of D1-like-R antagonist. These results indicate that locomotory speed during an innate and reflexive behavior is subject to neuromodulation via D1-like-R activation.

D1-like-R signaling controls swim speed by modulating tail beat amplitude

We sought to further understand which kinematic variables are altered by D1-like-R signaling to bring about the increase in bout speed we observe. For characterization of kinematic variables, we evoked OMR in a head-restrained preparation which allows for a more accurate and detailed tracking of tail kinematics.

In response to caudal-to-rostral moving gratings, partially restrained larvae reliably performed forward OMR characterized by mostly symmetrical, alternating left-right tail beats (Figure 2A, Video S2). Tail-tip position was tracked to extract tail beat amplitudes, tail beat frequency and duration of bouts (Figure 2B). To activate D1-like-Rs, 100μM of the D1 agonist SKF-38393 was used. This relatively higher concentration was necessary in the agarose-embedded, skin-intact preparation as compared to either the freely swimming or the skin-peeled preparations (see below). As DA has been shown to modulate swim initiation in larval zebrafish [36], we also quantified the number of swim bouts initiated.

Figure 2. D1-like-R signaling modulates tail beat amplitude during forward OMR in head restrained larvae.

(A) Schematic representation of experimental set-up. Z-projection of a swim bout showing characteristic alternating left-right tail beats evoked in a head-restrained larval zebrafish (top) in response to caudal-to-rostral moving gratings (bottom). Tail-tip position was tracked for measurement of kinematic variables. (B) Left, representative tracked tail-position for a trial. Right, zoomed view of highlighted bout showing kinematic variables used for behavioral quantification. (C) Overlaid tracked tail-tip position for a representative trial before (top) and after (bottom) application of 100 μM D1-like-R agonist, SKF-38393. Summary data of (D) average tail beat amplitude, (E) average tail beat frequency, (F) average bout duration and (G) number of bouts initiated before (black) and after (blue) bath application of D1-like-R agonist. (H) Overlaid tracked tail-tip position for a representative trial before (top) and after (bottom) application of 100 μM D1-like -R antagonist, SCH-23390. Summary data of (I) average tail beat amplitude, (J) average tail beat frequency, (K) average bout duration and (L) number of bouts initiated before (black) and after (red) bath application of D1-like-R antagonist. Scale bar represents 1mm. N_SKF-38393=37 larvae, N_SCH-23390=18 larvae, Wilcoxon signed rank test; ***p<0.00001, *p<0.05, ns: not significant. See also Videos S2 and S3 and Figures S1 and S2.

Activation of D1-like-R increased mean tail beat amplitude and tail beat frequency of forward swims (Figure 2C-E, Video S2). However, no difference in duration of bouts or number of bouts initiated was observed post application of 100 μM D1-like-R agonist, SKF-38393 (Figure 2F, G). In contrast, application of 100 μM D1-like-R antagonist, SCH-23390, decreased mean tail beat amplitude of forward locomotion (Figure 2H, I). Tail beat frequency, bout duration and number of swim bouts initiated did not change significantly (Figure 2J-L).

Free swimming OMR behavioural assay required larvae to swim both in a straight trajectory as well as make routine turns (Video S1). To investigate the role of D1-like-R signaling in modulation of turning behavior, we presented leftward and rightward moving gratings to head-restrained larvae (Figure S1A). Larvae responded to the stimuli with asymmetric tail deflections in the direction of grating movement (Figure S1A, Video S3). Tail-tip position was tracked and maximum tail bend angle was measured before and after application of 100 μM D1-like-R agonist and antagonist (Figure S1B). Larvae performed turns with larger tail bend angles post application of D1-like-R agonist (Figure S1C, E, Video S3). In contrast, application of the D1-like-R antagonist showed a decrease in the magnitude of the tail bend angle (Figure S1D, F). Taken together, these results indicate that D1-like-R activation modulates the extent of tail bends during both forward locomotion and turns resulting in greater displacement.

To understand how D1-like-R signaling affects spinal motor output, we recorded fictive motor bouts evoked by OMR stimulus in paralyzed larvae in the absence and presence of D1-like-R agonist (Figure S2). Activation of D1-like-Rs increased the amplitude of evoked fictive motor bouts (Figure S2A–C). This could result either from novel recruitment of larger motor neurons or from temporal summation of action potentials from an enlarged active motor neuron pool. There was no change in the burst duration (mean ± SEM: control=11 ± 0.57 ms, agonist=11 ± 0.64 ms, p=1; paired t-test), tail beat frequency, number of bouts initiated or bout duration (Figure S2D–F).

Activation of D1-like-R intensifies drive from ‘slow’ motor neurons

D1-like-R mediated increase in swim speed could result from an increase in the firing of active motor neurons and/or by the recruitment of new cells to the active pool [1]. Zebrafish axial motor neurons can be broadly divided into two classes: primary and secondary [37]. Early born, dorsally located primary motor neurons innervate fast muscle fibres and are active during fast swimming, struggle and escape responses whereas later born, ventral secondary motor neurons are active during slower swimming [1,38]. Besides anatomical position and axonal innervation pattern, the two classes of motor neurons can also be clearly distinguished based on their cellular properties and response to injected current [39] (Figure S3A,B). As secondary motor neurons are active during low-frequency swimming such as those observed in OMR, we first asked if they are modulated by D1-like-R. We obtained whole-cell patch clamp recordings from dorsal secondary motor neurons (soma position 0.41-0.65; Figure S3C) while presenting moving gratings from below to evoke forward OMR (Figure 3A). In response to moving grating presentation, 7/12 dorsal secondary motor neurons recorded were active and fired several action potentials under control conditions (Figure 3B), while the rest were quiescent (Figure 3D). Both the active and quiescent groups increased the total number of action potentials fired during OMR after the application of 20 μM D1-like-R agonist (Figure 3C, E), and such increases were nullified by subsequent application of D1-like-R antagonist (Figure 3F; control: 21 ± 7; agonist: 44 ± 14; antagonist: 5 ± 2; Tukey HSD following mixed effects model; p<0.05). To understand if the increase in the total number of action potentials fired during OMR reflected a higher degree of recruitment in every bout, we normalized this number to the bout duration. The number of action potentials normalized to bout duration was significantly higher after application of D1-like-R agonist (Figure 3G), indicating greater recruitment of dorsal secondary motor neurons during OMR. These D1-like-R agonist mediated effects were antagonized in 7/7 secondary motor neurons post subsequent application of D1-like-R antagonist (Figure 3F, G). The number of action potentials generated during stationary grating presentation (spontaneous swims) did not differ significantly before and after application of D1-like-R agonist (Figure S4A).

Figure 3. D1-like-R activation enhances drive from secondary motor neurons during OMR.

(A) Schematic representation of experimental set-up. Whole-cell patch clamp recordings from secondary motor neurons were obtained while presenting 10s of stationary gratings alternating with 10s of forward moving gratings. Motor neurons were targeted in the region marked by the red rectangle. Zoomed view of the same region is shown on the right. (B) Left, recording from a representative secondary motor neuron during a trial. Region under small black line is shown in a zoomed view on the right. Shaded areas represent timing of moving gratings presentation. (C) Left, recording from the same neuron as in (B) post application of 20 μM D1-like-R agonist, SKF-38393. Region under the small blue line is shown expanded on the right . (D) Representative recording from a secondary motor neuron that was quiescent during moving gratings presentation before any drug application (black). (E) Recording from the same secondary motor neuron as in (D) after subsequent application of D1-like-R agonist (blue) and (F) D1-like-R antagonist (red). (G) Paired plot of average number of action potentials fired within a fictive swim bout divided by its duration during moving grating presentation before (black), after application of D1-like-R agonist (blue) and post subsequent application of D1-like-R antagonist (red). N = 12 cells in control and agonist, and 7 cells in antagonist; Tukey HSD following mixed effects model; **p<0.01. (H) Paired plot of average number of action potentials per cycle before (black), after application of D1-like-R agonist (blue) and post subsequent application of D1-like-R antagonist (red). Tukey HSD following mixed effects model; *p<0.05, **p<0.01. (I) Paired plot of total number of supra-threshold cycles (active cycles) during moving gratings presentation before (black), after (blue) application of D1-like-R agonist, and post subsequent application of D1-like-R antagonist (red). Tukey HSD following mixed effects model; *p<0.05, **p<0.01. (J) Top, representative recordings from a secondary motor neuron during moving grating representation before (black) and after (blue) application of D1-like-R agonist. Bottom, zoomed view of region marked with black rectangle showing voltage cycles (highlighted in pink, see Methods). (K) Average frequency of voltage cycles before (black) and after (blue) application of D1-like-R agonist. Wilcoxon signed-rank test; p=0.9. N=12 cells from 12 larvae. ns: not significant. See also Figures S3 and S4.

To correlate the changes observed in the activity of single secondary motor neuron to observed changes in swimming kinematic variables, we next analyzed number of action potentials fired per tail beat cycle of the motor rhythm. D1-like-R activation resulted in an increase in the number of action potentials per cycle (Figure 3H) as well as an increase in the number of supra-threshold cycles (Figure 3I). These changes were abolished by subsequent application of D1-like-R antagonist (Figure 3H, I). Frequency of these sub-threshold as well as supra-threshold cycles reflect synaptic drive to these motor neurons from the CPG (Figure 3J; [39]). Average frequency of these cycles did not differ significantly post application of D1-like-R agonist (Figure 3K).

These results indicate that activation of D1-like-R signaling increases swim speed by enhancing drive from secondary motor neurons. This in turn is mediated by recruitment of quiescent neurons and increased firing per swim cycle of already active neurons. These changes point to D1-like-R mediated increase in the excitability of secondary motor neurons, although an increase in synaptic drive during OMR cannot be ruled out.

D1-like-R activation reduces spike latency and action potential threshold of secondary motor neurons

To test if D1-like-R signaling directly affects the excitability of secondary motor neurons, we asked if secondary motor neurons show changes in firing behavior in response to direct current injection when D1-like R agonist is applied. We analyzed firing responses of secondary motor neurons to a series of depolarizing current steps (25 pA-400pA, 25 pA step size) before and after application of 20 μM D1-like-R agonist (Figure 4A). D1-like-R agonist significantly reduced first spike latency (Figure 4B, C). The decrease in spike latency was observed for all current steps and was less pronounced when injected currents were high (Figure 4D). D1-like-R activation also reduced the voltage threshold for the first action potential generated (Figure 4B, E). We observed no significant effect of D1-like-R activation on rheobase, input resistance and instantaneous firing rate of first two spikes (Figure 4F–H). Resting membrane potential, spike afterhyperpolarization (AHP) and spike-width did not change post application of D1-like-R agonist (Figure S5A-C).

Figure 4. D1-like-R activation reduces spike latency and action potential threshold of secondary motor neurons.

(A) Schematic of experimental set up. Region marked by the red rectangle is shown on the right. Responses of secondary motor neurons to a series of depolarizing current steps were compared before and after application of 20 μM D1-like-R agonist, SKF-38393. Right, example traces from a cell showing responses to sub-threshold (bottom), threshold (middle) and supra-threshold (top) current steps before (Control) and after application of D1-like-R agonist. (B) Representative traces before (black) and after (blue) application of D1-like-R agonist. Vertical dotted lines indicate spike latency and horizontal dotted lines mark threshold for action potential generation before (black) and after (blue) D1-like-R agonist application. (C) Summary data for first spike latency. Wilcoxon signed-rank test; **p<0.01 (D) Scatter plot of spike latency for each step of depolarizing current injected before (black) and after application of D1-like-R agonist (blue). Solid lines represent mean latency for each current with minimum three values. Mixed-Effects model; **p<0.01 (E) Summary data for threshold of action potential generation. Wilcoxon signed-rank test; *p<0.05. (F) Summary data for rheobase. Paired t-test, p=0.34 (G) Summary data for input resistance. Wilcoxon signed-rank test; p= 0.10 (H) Instantaneous firing frequency of the first two spikes measured in response to series of current steps before (black) and after (blue) application of D1-like-R agonist. Solid lines represent mean firing frequency for each current with minimum three values. Mixed-Effects model; p= 0.41. ns: not significant. N=10 secondary motor neurons recorded from 10 larvae. See also Figures S3, S5 and S6.

These results show that D1-like-R activation increases secondary motoneuronal excitability by reducing spike latency and action potential threshold.

Quiescent primary motor neurons are recruited during OMR by D1-like-R activation

As primary motor neurons are active only during fast and vigorous swimming [1,38], we next examined if D1-like-R signaling can modulate the recruitment of primary motor neurons as well to bring about faster locomotion. We obtained whole-cell patch clamp recordings from primary motor neurons (Figure S3) while presenting drifting gratings from below to evoke OMR (Figure 5A). Primary motor neurons usually showed little to no spiking activity during visual stimulus presentation (Figure 5B). Post application of D1-like-R agonist, 7/13 primary motor neurons recorded showed an increase in the total number of action potentials fired during OMR (Figure 5C), which was then nullified by subsequent application of D1-like-R antagonist (Figure 5D; control: 0.6 ± 0.5; agonist: 21 ± 6; antagonist: 3 ±1; Tukey HSD following mixed effects model; p<0.001). The number of action potentials fired normalised to bout duration also increased after application of D1-like-R agonist and decreased after application of the antagonist (Figure 5E). Primary motor neurons are further classified as caudal primary (CaP), middle primary (MiP) and rostral primary (RoP) based on the rostrocaudal position of their somata. Of the 7 primary motor neurons that were recruited, 3 were identified as CaP, 3 as RoP and 1 as MiP. The number of action potentials generated during stationary grating presentation did not differ significantly before and after application of D1-like-R agonist (Figure S4B).

Figure 5. Quiescent primary motor neurons are recruited during OMR by D1-like-R activation.

(A) Schematic representation of experimental set-up. Whole-cell patch clamp recordings from primary motor neurons were obtained while presenting 10 s of stationary gratings alternating with 10 s of forward moving gratings. Motor neurons were targeted in the region marked by the red rectangle. Zoomed view of the same region is shown on the right. (B-D) Representative recordings from a rostral primary motor neuron (RoP) before any drug application (black), after application of D1-like-R agonist (blue) followed by D1-like-R antagonist (red) application. Shaded areas represent timing of moving gratings presentation. (E) Paired plot of average number of action potentials fired within a fictive swim bout divided by its duration during moving grating presentation before (black), after application of D1-like-R agonist (blue) and post subsequent application of D1-like-R antagonist (red). N= 13 cells in control and agonist, and 5 cells in antagonist; Tukey HSD following mixed effects model; **p<0.01, *p<0.05. (F) Paired plot of average number of action potentials per cycle before (black), after application of D1-like-R agonist (blue) and post subsequent application of D1-like-R antagonist (red). Tukey HSD following mixed effects model; ***p<0.001, **p<0.01. (G) Paired plot of number of supra-threshold cycles (active cycles) during moving gratings presentation before (black), after (blue) application of D1-like-R agonist, and post subsequent application of D1-like-R antagonist (red). Tukey HSD following mixed effects model; *p<0.05, **p<0.01. (H) Left, recordings from a middle primary motor neuron (MiP) before any drug application (black) and (I) after application of D1-like-R agonist (blue). Right, zoomed view of the regions bounded by the black boxes showing rhythmic voltage oscillations (marked in pink, see Methods). (J) Average frequency of voltage oscillations before (black) and after (blue) application of D1-like-R agonist from all the primary motor neurons that were recruited (7/13 cells) post application of D1-like-R agonist. Wilcoxon signed-rank test; p=0.09. ns: not significant; N=13 primary motor neurons recorded from 13 larvae. See also Figures S3 and S4.

Similar to secondary motoneurons, primary motor neurons increased the number of action potentials per cycle (Figure 5F) and the number of supra-threshold cycles (Figure 5G) when D1-like-R agonist was applied. The average frequency of voltage cycles in primary motor neurons did not change significantly after application of D1-like-R agonist (Figure 5H-J). These results show that D1-like-R signaling recruits novel neurons from the ‘fast’ motor pool to increase the speed of locomotion during OMR.

D1-like-R activation increases excitability of primary motor neurons

Next, we investigated the mechanism by which D1-like-R activation recruits primary motor neurons during OMR. Responses to a series of depolarizing current steps were obtained from primary motor neurons. Bath application of 20 μM D1-like-R agonist was associated with an increase in the number of evoked action potentials (Figure 6A). D1-like-R activation modulated several membrane properties to increase the excitability of primary motor neurons. Spike analysis revealed a decrease in first spike latency (Figure 6B, C). Significant reduction in spike latencies were observed for all current steps injected (Figure 6D).

Figure 6. D1-like-R activation increases excitability of primary motor neurons.

(A) Schematic of experimental set up. Region marked by the red rectangle is shown on the right. Responses of a representative primary motor neuron to a series of depolarizing current steps were compared before (Control) and after application of 20 μM D1-like-R agonist, SKF-38393. (B) Representative traces before (black) and after (blue) application of D1-like-R agonist. Vertical dotted lines indicate spike latency, horizontal dotted lines mark threshold for action potential generation and lines on top indicate first inter-spike interval (Finst) before (black) and after (blue) D1-like-R agonist application. (C) Summary data for first spike latency. Wilcoxon signed-rank test; *p<0.05 (D) Scatter plot of spike latency for each step of depolarizing current injected before (black) and after application of D1-like-R agonist (blue). Solid lines represent mean latency for each current step with minimum three values. Mixed-Effects model; *p<0.05 (E) Summary data for threshold of action potential generation. Wilcoxon signed-rank test; ***p<0.001. (F) Summary data for rheobase. Wilcoxon signed-rank test; *p<0.05. (G) Summary data for input resistance. Wilcoxon signed-rank test; *p<0.05. (H) Instantaneous firing frequency of the first two spikes measured in response to a series of current steps before (black) and after (blue) application of D1-like-R agonist. Solid lines represent mean firing frequency for each current step with minimum three values. p=0.6; Mixed effects model; ns: not significant. N=12 primary motor neurons recorded from 12 larvae. See also Figures S3, S5 and S6.

D1-like-R activation also reduced threshold for action potential generation (Figure 6B,E) and rheobase (Figure 6F). However, a decrease in input resistance was observed post application of D1-like-R agonist (Figure 6G). Nevertheless, the instantaneous firing rate of first two spikes did not change significantly upon addition of D1-like-R agonist (Figure 6H). Resting membrane potential, action potential half-width and the amplitude of spike after hyperpolarization also did not change significantly after adding D1-like-R agonist (Figure S5D-F).

To further test if the increased excitability observed after adding D1-like-R agonist was due to actions on spinal or supra-spinal targets, we measured firing properties of motor neurons in spinalized larvae (Figure S6). Application of D1-like-R agonist reduced first spike latency and spike threshold significantly, similar to what was observed in the intact preparation (Figure S6A-C, G-K). Application of D1-like-R antagonist decreased excitability of primary and secondary motor neurons even in the spinalized larvae (Figure S6D-F, L-P). These results show that activation of D1-like-Rs in the spinal cord increases the excitability of primary and secondary motor neurons.

Excitatory synaptic drive to motor neurons increases after activation of D1-like-Rs

Besides increasing excitability, activation of D1-like-Rs could also recruit motor neurons by enhancing synaptic drive during OMR. To test if this is true, we performed voltage clamp experiments on primary and secondary motor neurons during OMR. We measured excitatory synaptic currents at a holding potential of - 75mV and inhibitory synaptic currents by holding at +10mV [40]. The average charge transferred by excitatory synaptic currents during OMR increased following application of D1-like-Rs (Figure 7A,B,E) while the average charge transferred by inhibitory synaptic currents did not change (Figure 7C,D,F).

Figure 7. D1-like-R activation increases excitatory drive to motor neurons.

(A)Left, voltage-clamp recordings (holding potential V_h = -75 mV) of excitatory currents were obtained while presenting 10 s of stationary gratings alternating with 10 s of forward moving gratings. Zoomed-in view of highlighted region is shown on the right. Shaded areas represent timing of moving gratings presentation. (B) Recording from the same motor neuron as in (A) after subsequent application of D1-like-R agonist. (C) Left, voltage-clamp recordings (holding potential Vh = +10 mV) of inhibitory currents were obtained while presenting 10 s of stationary gratings alternating with 10 s of forward moving gratings. Zoomed-in view of the highlighted region is shown on the right. Shaded areas represent timing of moving gratings presentation. (D) Recording from the same motor neuron as in (C) after subsequent application of D1-like-R agonist. (E) Summary data for excitatory drive. N_Primary=8 cells from 8 larvae, N_Secondary= 7 cells from 7 larvae; Wilcoxon signed-rank test; *p<0.05. (F) Summary data for inhibitory drive. N_Primary=7 cells from 7 larvae, N_Secondary= 4 cells from 4 larvae; Wilcoxon signed-rank test; p=0.36. See also Figure S3.

Together, our analysis of secondary and primary motor neurons during OMR reveal a stimulatory effect of D1-like-R signaling. Activation of D1-like-R decreases spike latency and spike threshold and increases excitatory synaptic drive in motor neurons. The net effect of these changes in intrinsic and synaptic properties is to increase the number of spikes per cycle in ‘slow’ secondary motor neurons and to recruit previously quiescent ‘fast’ primary motor neurons to spike during OMR. These additional spikes fired per burst summate to increase the extent of tail bends, thus increasing the displacement generated in the same amount of time. While not ruling out actions of D1-like-R elsewhere in the motor hierarchy, these effects provide a parsimonious mechanism for the speed regulation observed during OMR.

Discussion

Neuromodulatory selection of novel neurons

Zebrafish larvae generate slow swims when presented with slowly drifting gratings. During this behavior they activate secondary motor neurons belonging to the ‘slow’ module, while primary motor neurons belonging to the ‘fast’ module are quiescent. However, when D1-like receptors are activated, primary motor neurons are recruited and secondary motor neurons fire more action potentials, resulting in larger tail bends and therefore greater displacement and faster swims. Our results demonstrate that even under conditions where the sensory input is unaltered, neuromodulators can remap sensorimotor transformations, such that the behavioral output is altered. In addition, our experiments underline the fact that the pattern of recruitment of neurons during behaviors is heavily dependent on the neuromodulatory context. Recent advances in microscopy and the development of novel neuronal activity sensors have allowed us to map neuronal circuits that are active during a variety of behaviors. Our study serves as a reminder that such maps are a function of the neuromodulatory status of the animal.

Dopaminergic modulation of motor neuronal recruitment

In zebrafish, spinal dopaminergic projections arise solely from the A11 cluster, also known as dopaminergic diencephalospinal neurons (DDNs) [34,36]. Dopaminergic neuromodulation underlies developmental maturation of swim motor patterns [23] and in particular, the DDNs have been shown to mediate the switch from long to short swim bouts [24]. DDNs are more likely to fire bursts of action potentials during swim bouts and fire tonically during periods of rest [36]. Since burst firing could potentially lead to higher calcium influx into presynaptic terminals, more dopamine is likely to be released by bursting DDNs onto their spinal targets during periods of active locomotion. These findings lend support to our view that endogenous dopamine is capable of altering locomotor speeds in vivo in the freely moving animal.

Tyrosine hydroxylase (TH) immunoreactive fibers in the spinal cord make contact with both primary and secondary motor neurons [41] implying direct modulation of motoneuronal excitability by A11 dopaminergic neurons. We show that activation of D1-like receptors enhances the excitability of primary and secondary motor neurons, most likely by acting directly on them. Importantly, we show that both spike latency and threshold are decreased, suggestive of direct dopaminergic modulation of the transient A-type potassium conductance (I_A). Indeed, dopaminergic reduction of I_A leading to a decrease in first spike latency has been reported in invertebrate [42] and vertebrate [43] motor neurons.

Our results complement previous studies on mechanistic bases of speed control. The ‘size principle’ states that neurons are sequentially recruited as speed increases such that the smaller, high input resistance secondary motor neurons get recruited at slow speeds and the larger, low input resistance primary motor neurons are recruited at high speeds. To match this recruitment order, gradations in endogenous rhythmicity have also been observed [39]. In addition, at higher speeds, primary motor neurons preferentially receive enhanced excitation from pre-motor interneurons to enable their recruitment [40]. We find that activation of D1-like-Rs increases excitatory synaptic drive to motor neurons during OMR. Such an increase could be mediated by presynaptic and/or postsynaptic mechanisms and needs to be investigated further in future studies. The net effect of the dopaminergic modulation of intrinsic and synaptic properties of primary and secondary motor neurons is to increase their participation in OMR behavior. As shown by our suction electrode recordings, the enhanced recruitment of motor neurons leads to greater amplitude of ventral root motor neuronal bursts resulting in larger tail bend amplitudes. These larger amplitude tail beats result in greater displacement per beat cycle [44,45].

Divergent actions of D1-like-R activation on motor neurons

We find that D1-like-R activation in primary motor neurons decreases rheobase and input resistance while not having such effects in secondary motor neurons. These results are interesting in two ways: first, while a decrease in input resistance would be predicted to increase rheobase, we observed the opposite; second, while most other effects of D1-like-Rs were similar between primary and secondary motor neurons, the effect on rheobase and input resistance are cell-class specific. Both of these points can be understood in terms of divergent actions of neuromodulators. Neuromodulators can have distinct effects on different neuronal types, and even within the same neuronal type, they can act on distinct conductances by specific expression of receptor subtypes and by how they are coupled to intracellular signaling pathways [46]. We speculate that D1-like-R activation acts concomitantly on both voltage-dependent and leak conductances in primary motor neurons to alter rheobase and input resistance independently and that these channels may be differently coupled to D1-like signaling in secondary motor neurons.

Regulation of speed during OMR by spinal interneurons

The recruitment patterns of spinal pre-motor interneurons during OMR have thus far not been documented. Nevertheless, recruitment patterns across a range of locomotor speeds in other contexts have been reported in both larval and adult zebrafish. In adult zebrafish, premotor V2a interneurons connect preferentially to slow, intermediate or fast motor neurons forming distinct speed modules that are sequentially recruited as speed increases [8–10]. However, in larval zebrafish, premotor interneurons active at slow speeds are silenced as swim speed increases, and distinct sets of interneurons are recruited from quiescence at faster speeds [2]. Such a phenomenon has also been reported for speed-related gait changes during limbed locomotion in mice [3–5,47]. A recent study shows that type I and type II subclasses of ‘fast’ V2a interneurons connect preferentially to higher order interneurons and primary motor neurons, respectively [48]. Such connectivity enables specific control of movement timing by the type I subclass and movement amplitude by the type II subclass. We show that the excitatory synaptic drive to motor neurons is increased following activation of D1-like-Rs. Whether this is mediated via the selective strengthening of type II V2a to primary motor neuron synapses needs to be investigated. Further, D1-like-R modulation of motor neuronal excitability is likely to propagate to V2a interneurons via their gap-junctional connectivity [49]. Whether D1-like-Rs have direct actions on V2as and other members of the CPG is an exciting question to probe in the future.

In addition to CPG neurons, spinal mechanosensory neurons may also be targets of dopaminergic modulation. We observed an increase in tail beat frequency after addition of D1-like-R agonists in the head-restrained, free tail preparation (Figure 2) but not in the paralyzed preparation (Figures S2, 3 and 5). Mechanosensitive Rohon-Beard neurons and cerebro spinal fluid contacting neurons (CSF-cNs) can increase tail beat frequency during ongoing locomotion via their projections onto spinal premotor interneurons [50–52]. While it is not known if these neurons receive dopaminergic inputs, or if they express D1-like-Rs, our results suggest that the increase in tail beat frequency observed only when there is active swimming could likely be induced by D1-like-R actions on these mechanosensors.

Supraspinal circuits governing the OMR behavior

OMR relies on circuits distributed across the nervous system. Retinal input, including responses from direction-selective RGCs, arrives in arborization fields (AF) 5 and 6, which are innervated by the dendrites of pre-tectal neurons. Pretectal neurons show direction-selective tuning, respond to binocular optic flow and send long range projections to the cerebellum and the hindbrain reticular formation [53,54], in turn leading to the generation of the appropriate swim command in the spinal cord. Several hindbrain neurons are activated when the fish perform OMR [55]. Among these, neurons in the nucleus of the medial longitudinal fasciculus (nMLF) are active during forward OMR and the ventromedial spinal projection neurons (vSPNs) are active during turns [56,57]. The nMLF makes direct synaptic contacts with primary and secondary motor neurons [58], regulates swim speed during OMR [33] and receives dense innervation from TH-positive fibers [59].

Recently, neurons in the posterior tubercular nucleus (PTN), a sub-group of the A11 dopaminergic cluster, were identified to show large calcium transients in response to forward moving gratings in larval zebrafish [60]. The activation of PTN dopaminergic neurons was delayed by many seconds after optic flow started and lasted for several seconds after it was turned off, suggesting a slow build-up of the modulatory drive. Further, activity in the PTN neurons was suppressed following motor bouts implying a feedback mechanism that limits the dopaminergic modulation. Projections from PTN are restricted to the hindbrain and could potentially be the source of TH-fibers projecting to nMLF. In lamprey, dopamine released from the posterior tuberculum activates through a D1 receptor dependent mechanism the neurons of the mesencephalic locomotor region, which in turn activate reticulospinal cells to increase locomotor output [61–63]. Taken together, our results, in the context of the above studies, suggest that during OMR, dopaminergic neurons in the A11 cluster act to increase swim speed via their concomitant modulatory actions at the spinal and supraspinal levels.

Star⋆Methods

Lead Contact and Materials Availability

This study did not generate new unique reagents. Further information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact, Vatsala Thirumalai (vatsala@ncbs.res.in).

Experimental Model and Subject Details

All experiments were approved by the institutional animal ethics committee and the institutional biosafety committee. Experiments were performed on Indian wild type zebrafish (Danio rerio) larvae between 6 and 7 days post fertilization (dpf) at room temperature (25-28 °C). Larvae have not undergone sex specification at these stages. Larvae were maintained in 14:10 light-dark cycle at 28 °C in E3 medium (composition in mM: 5 NaCl, 0.17 KCl, 0.33 CaCl₂, and 0.33 MgSO₄, pH 7.8).

Method Details

Free swimming behavior assay

Zebrafish larvae swam freely in a circular arena 55 mm in diameter. A block of agarose in the centre of the arena restricted swimming in a narrower lane 20 mm in width. Videos were acquired at 120 fps using a CMOS camera (FL3-U3-13-S2M-CS, Point Grey, Richmond, USA) with IR illumination provided from below. A long pass filter (715 nm colored glass filter, Thorlabs, New Jersey, USA) was placed in front of the camera to remove the visual stimulus. Radially spinning square wave gratings were displayed on a screen underneath the arena (Figure 1A, Video S1). Stimulus presentation was performed using Processing [64]. Acquisition of videos and tracking of larval centroid was performed using Bonsai [65].

Average speed was calculated as total distance travelled in trial duration of 60 s. Bout start indices were identified from a plot of instantaneous speed vs time using a threshold-based event detection method, where the threshold was manually set. Bout ends were detected as frames following which the instantaneous velocity fell below threshold for at least 7 frames (Figure 1B). Distance travelled within a bout was calculated as bout distance and was divided by duration of respective bout to calculate bout speed. Average of these parameters across all bouts per larva was then calculated to give average bout distance and average bout speed.

Head-restrained behavior assay

Larvae were embedded in 1.5% low gelling agarose (Sigma-Aldrich; Missouri, USA). E3 medium was added after the agarose had congealed. Agarose around the tail leaving pectoral fins free was removed for observing tail movements. Optomotor response was evoked by presenting black and white gratings moving with spatial period 10 mm and temporal period 10 mm/s. Visual stimulus was projected on a screen below the larva using a DLP projector (Acer C120; Acer Inc., New Taipei City, Taiwan) after reflection by a cold mirror (FM203; Thorlabs, New Jersey, USA). The arena was IR illuminated from below. Videos were acquired at 500 fps using a high-speed camera (Phantom Miro eX4; Vision research, New Jersey, USA) fitted with a zoom lens (AF Nikkor 60 mm f/2.8D, Nikon, Tokyo, Japan) and infrared pass filter (768 nm, Pixelteq, Florida, USA). Each trial consisted of linearly drifting grating presentation for 12s. Three trials before and four trials after the drug application were performed (Videos S2 and S3).

Data were analyzed using custom written scripts in ImageJ, IPython [66] and MATLAB (Mathworks, Natick, USA). Videos were processed in Fiji [67] to obtain larval mid-line. A* search algorithm was used to track tail-tip position using custom written macros in ImageJ. Tail-tip position was used for extracting kinematic parameters. Analysis of kinematic variables was performed offline. Struggles were identified as vigorous body movements with large tail bends and were removed from subsequent analyses. Tracking data was segmented into swim bouts (Figure 2B, left). Amplitude was defined as the maximum (peak-to-trough) tail tip displacement in a bout. Time difference between movement onset and offset of a bout was defined as bout duration (Figure 2B, right). These variables were extracted for individual bouts and average values across all bouts per larva were calculated. Tail beat frequency was defined as the time taken to perform a complete oscillation and was calculated using fast fourier transform. Tail bend angle was calculated using head and tail-tip coordinate. Maximum tail bend angle for each turn was extracted (Figure 3B) and average maximum tail bend angle per larva was calculated.

Electrophysiology

Whole-cell patch clamp recordings from motor neurons were obtained while presenting caudal-to-rostral moving gratings on a screen below the stage. Larvae were anesthetized in 0.01% MS-222 (Sigma-Aldrich; Missouri, USA) and transferred to a recording chamber. The larvae were pinned dorsoventrally in the head and laterally in the tail through the notochord using fine tungsten wire (California Fine Wire, CA, USA). The MS222 was then replaced by external solution (composition in mM: 134 NaCl, 2.9 KCl, 1.2 MgCl₂, 10 HEPES, 10 glucose, 2.1 CaCl₂, 0.01 D-tubocurarin; pH 7.8; 290 mOsm) and skin along the tail was carefully removed using forceps (Fine Science Tools, Foster City, USA). Muscles in a hemi-segment (between the 10^th and 13^th myotomes) were carefully removed to expose the spinal cord. Cells were targeted at 4X magnification with a 60X/1.0 numerical aperture (NA) water-immersion objective (LUMPlanFL) on a compound microscope (BX61WI, Olympus; Tokyo, Japan) with differential interference optics (DIC). Patch pipettes were made using thick walled borosilicate capillaries (1.5 mm OD;0.86 mm ID; Warner Instruments, Hamden, CT, United States) pulled to 1-1.5 μm tip diameter using a Flaming brown P-97 pipette puller (Sutter Instruments, Novato, CA, United States). Pipettes were backfilled with K-gluconate internal solution (composition in mM: 115 K gluconate, 15 KCl, 2 MgCl₂, 10 HEPES, 10 EGTA, 4 ATP Disodium salt; pH 7.2; 290 mOsm) and typically had resistances between 8 and 10 MΩ. Sulforhodamine was added to the patch internal solution for visualization of cell-morphology and axon tracts.

Motor neurons were targeted blind and classified as primary or secondary post hoc based on their axonal arborization pattern, cellular properties and responses to current injections (Figure S3). Primary motor neurons fired tonically whereas the dorsal secondary motor neurons showed chattering response to current injections (Figure S1). Six trials of visual stimulation were presented, for each condition (control, agonist application and antagonist application), with each trial consisting of 10s of stationary gratings alternating with 10s of forward moving gratings. Visual stimuli were displayed on an LCD screen (Waveshare, Hongkong) driven by Raspberry Pi (Model B RASP-PI-3, Raspberry Pi Foundation, Cambridge, UK). Visual stimulus presentation and electrophysiological recordings were triggered simultaneously and acquired using Multiclamp 700B amplifier, Digidata 1440A digitizer and pCLAMP software (Molecular Devices, San Jose, USA). Corrections for bridge balance were applied in current clamp mode. Membrane potentials are reported without correction for liquid junction potential which was measured to be +8 mV for the external and internal solutions mentioned above. The data were low-pass filtered at 2kHz using a Bessel filter and sampled at 20kHz at a gain of 1.

Extracellular suction recordings of fictive motor patterns were performed as described in [23]. Briefly, larvae were pinned and prepared for recording as described above. Micropipette (1.5 MΩ) filled with external solution was positioned close to myotomal boundary and mild suction was applied to record activity from peripheral nerves.

Voltage clamp recordings were performed as described in [40]. Briefly, motor neurons were clamped at -75 mV to isolate EPSCs and at +10 mV to isolate IPSCs. Recordings were performed using cesium based internal (122 mM CsMeSO₃, 0.5 mM QX314-Cl, 1 mM TEA-Br, 3 mM MgCl₂, 10 mM HEPES, 1 mM EGTA, 4 mM Na₂-ATP; pH:7.2; 290 mOsm).

For tail-only preparations, a fine razor blade was used to make a transection caudal to the hindbrain and the brain was completely removed from the spinal cord.

Data were analyzed using Clampfit (Molecular Devices, San Jose, USA) and MATLAB (Mathworks, Natick, USA). Clampfit was used to identify spikes. Bouts and bursts were identified from the sub-threshold membrane potential depolarization. To calculate the frequency of oscillations underlying bursts, recordings for trials where forward grating was presented, was first filtered to remove spikes (filtered trace in pink shown in Figure 3J and Figure 5F). Frequency with maximum power post fast fourier transform of the filtered recording was used to estimate oscillation frequency for a trial.

To determine intrinsic firing pattern of motor neurons, 200 ms long depolarizing current pulses in the range (25-400 pA, step size 25 pA) were applied in absence of visual stimulus presentation. First spike latency was defined as the time between onset of the current step and the peak of the first spike. Spike threshold was defined for the first spike at rheobase as the membrane potential where the speed of voltage change reaches 5mV/ms. Rheobase was defined as the minimum current required to elicit an action potential. Input resistance was calculated by injecting 200 ms long hyperpolarizing pulses (-100pA to -25 pA).

Bouts and bursts in suction recordings were detected as described in (5). Amplitude was defined as peak signal. Tail beat frequency was calculated as the inverse of the time difference between two successive bursts. Total number of bouts during forward moving grating presentation is reported as bout number. Time difference between bout onset and offset was used to calculate bout duration. Average of these parameters across trials per larva was calculated.

Charge transfer for voltage clamp recordings was calculated as the time integral of the baseline-adjusted currents for the duration of forward moving grating presentation.

Drugs

Drug concentrations for each experiment was determined in pilot experiments (data not shown). Drugs were dissolved in E3 for behavioral experiments and in external solution for electrophysiological experiments. Measurements were taken between 2 and 25 minutes after drug was added. For the experiments in Figures 3 and 5, measurements were first taken in normal saline, then followed by saline containing agonist, which was then washed off with saline containing antagonist.

Quantification and Statistical Analysis

Data were tested for normality using one sample Kolmogorov-Smirnov test. Paired t-test or Wilcoxon signed rank test were performed for comparisons between the two groups in MATLAB. Mixed effects model using nlme package [68] in R was used for repeated measures design. Significance level was defined as 0.05. Details on statistical test, p values and sample size can be found in figure legend.

KEY RESOURCES TABLE

KEY RESOURCES TABLE.

REAGENT or RESOURCE	SOURCE	IDENTIFIER
Chemicals, Peptides, and Recombinant Proteins
SKF-38393 hydrochloride	SIGMA-ALDRICH	D047; CAS:62717-42-2
SCH-23390 hydrochloride	SIGMA-ALDRICH	D054; CAS:125941-87-9
Adenosine 5’-triphosphate disodium salt	SIGMA-ALDRICH	A2383; CAS:34369-07-8
Potassium D-gluconate	SIGMA-ALDRICH	G4500; CAS:299-27-4
Sulforhodamine B	SIGMA-ALDRICH	230162; CAS:3530-42-1
Tubocurarine chloride pentahydrate	SIGMA-ALDRICH	93750; CAS:6989-98-6
EGTA	SIGMA-ALDRICH	03777; CAS:67-42-5
Agarose, low gelling temperature	SIGMA-ALDRICH	A9414; CAS:39346-81-1
Ethyl 3-aminobenzoate methanesulfonate (MS-222)	SIGMA-ALDRICH	E10521; CAS:888-86-2
Magnesium chloride	Fisher Scientific	M33500; CAS:7791-18-6
Glucose	Fisher Scientific	D16500; CAS:50-99-7
HEPES	HIMEDIA	RM380; CAS:7365-45-9
Sodium chloride	HIMEDIA	GRM853; CAS:7647-14-5
Potassium chloride	Qualigens	Product#13305
Caesium methanesulphonate	SIGMA-ALDRICH	C1426; CAS:2550-61-O
Tetraethylammonium bromide	SIGMA-ALDRICH	241059; CAS: 71-91-0
Experimental Models: Organisms/Strains
Danio rerio (zebrafish); Indian wild type	Lab bred	N/A
Software and Algorithms
Matlab	Mathworks, Natick, USA	RRID:SCR_001622
Processing	[64]	https://processing.org
Bonsai	[65]	http://www.open-ephys.org/bonsai
Ipython	[66]	https://ipython.org; RRID:SCR_001815
Fiji	[67]	http://fiji.sc; RRID:SCR_002285
nlme package in R	[68]	httos://CRAN.R-proiectorg/üackage=nlme
Tail tracking analysis	This study	https://github.com/vtlab-ncbs/DopamineOMR
Fictive swim analysis	This study	https://github.com/vtlab-ncbs/DopamineOMR
Patch clamp analysis	This study	https://github.com/vtlab-ncbs/DopamineOMR

Supplementary Material

Supplementary Videos:

Video S1: Freely swimming larva performing OMR in normal saline (control) and in D1-like-R agonist. Related to Figure 1.

Video S2: Head-restrained larva performing forward swims during OMR in normal saline (control) and in D1-like-R agonist. Related to Figure 2.

Video S3: Head-restrained larva performing turns during OMR in normal saline (control) and in D1-like-R agonist. Related to Figure 2 and Figure S1.

Data and Code Availability

Raw data from the current study were not deposited into a public repository due to the large size, but are available from the corresponding author on request. Analysis codes can be downloaded from: https://github.com/vtlab-ncbs/DopamineOMR.