Ventromedial Thalamus-Projecting DCN Neurons Modulate Associative Sensorimotor Responses in Mice

Abstract

The deep cerebellar nuclei (DCN) integrate various inputs to the cerebellum and form the final cerebellar outputs critical for associative sensorimotor learning. However, the functional relevance of distinct neuronal subpopulations within the DCN remains poorly understood. Here, we examined a subpopulation of mouse DCN neurons whose axons specifically project to the ventromedial (Vm) thalamus (DCN^Vm neurons), and found that these neurons represent a specific subset of DCN units whose activity varies with trace eyeblink conditioning (tEBC), a classical associative sensorimotor learning task. Upon conditioning, the activity of DCN^Vm neurons signaled the performance of conditioned eyeblink responses (CRs). Optogenetic activation and inhibition of the DCN^Vm neurons in well-trained mice amplified and diminished the CRs, respectively. Chemogenetic manipulation of the DCN^Vm neurons had no effects on non-associative motor coordination. Furthermore, optogenetic activation of the DCN^Vm neurons caused rapid elevated firing activity in the cingulate cortex, a brain area critical for bridging the time gap between sensory stimuli and motor execution during tEBC. Together, our data highlights DCN^Vm neurons’ function and delineates their kinematic parameters that modulate the strength of associative sensorimotor responses.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12264-021-00810-9.

Introduction

The ability to associate sensory stimuli from the environment with specific motor actions is critical for animals to produce motor responses with appropriate strength and timing. Trace eyeblink conditioning (tEBC) is an ideal model in which to investigate the neural mechanisms underlying associative sensorimotor learning [1]. In this paradigm, an animal is presented with a neutral conditioned stimulus (CS; e.g., a light flash or a pure tone) followed by an aversive unconditioned stimulus (US; e.g., a corneal air-puff to the eyelid) with a fixed CS–US time interval. Prior to conditioning, the CS does not elicit eyelid movement. After conditioning, the animal generates a well-timed conditioned eyeblink response (CR) in response to the CS [2].

It is recognized that the acquisition of tEBC relies primarily on the cerebellum [3–5], which is composed of the cerebellar cortex and deep cerebellar nuclei (DCN) [6]. During tEBC, the CS and US signals are conveyed to the cerebellum via the mossy and climbing fibers [7]. Convergence of the CS and the US signals results in synaptic and structural plasticity in the cerebellar cortex [8], which disinhibits the DCN neurons to drive the initial occurrence of CRs [9, 10]. Therefore, as the final output of the cerebellum, the signal arising from the DCN represents the convergence of various inputs to the cerebellum and plays an essential role in tEBC [3–5]. Nevertheless, the details of DCN neurons with distinct target zones and their functional relevance remain largely unclear due to the challenge of isolating individual DCN neuronal subpopulations.

Neuronal tracing experiments have demonstrated that DCN neurons project to several brain regions involved in associative sensorimotor learning [11]. For instance, one subpopulation of DCN neurons innervates the red nucleus [12, 13], which controls the kinematics of CRs. Another subpopulation of DCN neurons provides feedback signals to the cerebellar cortex and influences the CR amplitude [14–16]. Most recently, DCN neurons projecting to the ventral medullary reticular formation were found to be associated with the control of unconditioned eyeblink responses (URs) [17]. Therefore, the diversity of DCN target zones enables various DCN neuronal subpopulations to play distinct roles in associative sensorimotor learning. Interestingly, recent tracing experiments have shown that DCN axon terminals are also distributed in the ventromedial thalamus (Vm) [11, 18, 19], where abundant calbindin-positive cells send diffuse projections to entire cerebral cortical areas, including the cingulate cortex (Cg) [20–22]. The Cg plays a critical role in bridging the time-separated stimuli [23–25] and conveying the related signal to the cerebellum during tEBC [26–29]. It is thus reasonable to propose that the signal from the DCN to the Vm participates in associative sensorimotor learning by affecting the Cg neuronal activity. However, the requirement and unique function of Vm-projecting DCN (hereafter refers to DCN^Vm) neurons in associative sensorimotor learning have not been directly evaluated.

To address this issue, we traced a subpopulation of DCN neurons specifically projecting to the Vm, and provided electrophysiological evidence that the DCN^Vm neurons are a unique subset of neurons whose activity varies with tEBC training. Moreover, we showed that the DCN^Vm neurons play a critical role in amplifying the CR amplitude. Our findings highlight a subpopulation of Vm-projecting neurons in the mouse DCN, and show that it modulates the strength of associative sensorimotor responses by providing amplification signals to the Cg through the cerebello–Vm–cortical pathway.

Materials and Methods

Subjects

All experimental procedures were approved by the Animal Care Committee of Army Medical University and were conducted between 08:00 and 12:00. Wild-type C57/BL6 mice (3 months–5 months old, 20 g–25 g, both genders) were used as the subjects. Before experiments and between recording sessions, the mice were individually housed under a 12-h light-dark cycle with free access to food and water.

Virus Injection

The mice were fixed in a stereotaxic apparatus (RWD, China) under anesthesia with isoflurane (0.5%–0.8% by volume in O₂). Body temperature was kept stable throughout the procedure using a heating pad. The virus was injected using a Nanoject II injector (Drummond Scientific, USA) via a micropipette. For anterograde tracing of the projection from the DCN to the Vm, AAV2-Syn-MCS-mCherry-3FLAG (OBiO, China) was injected into the left DCN (n = 3; bregma, AP: −6.3 mm, ML: +1.45 mm, DV: −2.3 mm, volume: 80 nL). For retrograde tracing the DCN^Vm neurons, retro-beads (Lumafluor) were injected into the right Vm (n = 3 mice; bregma, AP: −1.5 mm, ML: −0.75 mm, DV: −4.1 mm, volume: 60 nL).

To determine the distribution of DCN^Vm neurons, 3 mice were injected with AAV2-Ef1α-DIO-mCherry in the left DCN (bregma, AP: −6.3 mm, ML: +2.3, +1.7, and +1.0 mm, DV: −2.3 mm, volume: 80 nL per site) and AAV-retro-Syn-CRE in the right Vm (bregma, AP: −1.5 mm, ML: −0.75 mm, DV: −4.0 mm, volume: 60 nL).

To optogenetically manipulate the activity of DCN^Vm neurons, mice were injected with AAV2-Ef1α-DIO-hChR2 (H134R)-mCherry (OBiO, China; n = 24) or AAV2-CAG-FLEX-ArchT-GFP (OBiO; n = 13) into the left DCN (bregma, AP: −6.3 mm, ML: +1.45 mm, DV: −2.3 mm; volume: 80 nL) and AAV-retro-Syn-CRE into the right Vm (bregma, AP: −1.5 mm, ML: −0.75 mm, DV: −4.0 mm, volume: 60 nL).

To chemogenetically manipulate the activity of DCN^Vm neurons, mice were microinjected with AAV2-Ef1α-DIO-hM3D(Gq)-mCherry (OBiO; n = 6) or AAV2-Ef1α-DIO-hM4D(Gi)-mCherry (OBiO; n = 6) into the left DCN. In these mice, AAV-retro-Syn-CRE was injected into the right Vm. The injection coordinates and volumes were the same as those used in the optogenetic manipulation experiments.

To trace Cg-projecting Vm neurons in DCN^Vm-ArchT mice (n = 2), retro-beads were injected into the right Cg (bregma, AP: +1.2 mm, ML: −0.32 mm; DV: −1.3 mm; AP: +1.4 mm, ML: −0.32 mm, DV: −1.4 mm; 80 nL per site).

Tetrodes and Optical Fiber Implant

To record and identify the activity of DCN^Vm neurons during associative sensorimotor learning, we implanted a diode-tetrode assembly in the left DCN of 10 mice after 4 weeks of post-injection viral expression. Fabrication of the diode-tetrode assembly has been described in detail [30]. Briefly, the tetrode was made of 4 individual tungsten wires (bare diameter: 20 μm; insulated diameter: 25 μm, California Fine Wire, USA). The impedance (200 kΩ–400 kΩ) of each wire was measured before implantation. A 200-μm optic fiber (0.37 N.A., FT200EMT, Thorlabs, Germany) was located in the center of the tetrode array with a power intensity of 5.0 mW/mm²–6.0 mW/mm² at the tip. The light power was measured with an optical power meter (PM100D, Thorlabs). A craniotomy was made above the left cerebellum. The diode-tetrode assembly then was implanted into the left DCN (bregma, AP: −6.3 mm; ML: +1.5 mm, DV: −2.3 mm). Low-viscosity silicone (Kwik-Cast^TM, WPI) was applied to cover the craniotomy. A pair of stainless-steel wires (bare diameter: 76 μm, insulated diameter: 140 μm, no.791000, A-M Systems, USA) was subcutaneously passed through the left upper orbicularis oculi muscle to record electromyography (EMG). During 7 days of postoperative recovery, the tetrode was moved down (~40 μm/day) until it reached the target DCN area.

To test the effects of DCN^Vm activation on Cg neuronal activity, we implanted tetrode arrays in the right Cg (bregma, AP: +1.1 mm; ML: −0.5 mm; DV: −1.2 to −1.4 mm) in 3 mice. In addition, a 200-μm optic fiber (0.37 N.A., FT200EMT, Thorlabs) was implanted into the left DCN (bregma, AP: −6.3 mm; ML: +1.5 mm; DV: −2.1 mm).

To evaluate the effect of DCN^Vm activity manipulation on CR performance, 25 mice were implanted with an optical fiber (diameter: 200 μm, 0.37 N.A., FT200EMT, Thorlabs) into the left DCN (bregma, AP: −6.3 mm; ML: +1.5 mm; DV: −2.1 mm). The optical fibers were secured to the skull surface using Metabond cement (Parkell, Japan). All mice were monitored for 7 days following surgery to ensure full recovery.

Trace Eyeblink Conditioning

After recovery, the mice were habituated to the experimental environment for 2 days, 1 h per day. During habituation, they were allowed to move freely in a light- and sound-attenuated chamber. The headstage was connected to a 16-channel preamplifier with an accelerometer (C3335, Intan Technologies, USA). After habituation, the mice received tEBC training for 5 consecutive days. As recently reported [31], we used 150-ms blue LED light as the CS delivered by a LED mounted on the headstage (Fig. S1). The US was a 100-ms air-puff directed to the left cornea delivered via a blunted 27-gauge needle placed ~5 mm away from the eye. During tEBC training, a CS was followed by an US with a 250-ms trace interval (Supplementary movie1). Daily training consisted of 100 CS-US paired presentation trials with an average inter-trial interval of 23 s (randomly varied between 18 and 28 s). The daily conditioning training lasted for 30 min.

Rotarod Test

To evaluate how the chemogenetic manipulation of DCN^Vm neuronal activity influences non-associative motor functions, we conducted the Rotarod test in DCN^Vm-hM4Di and DCN^Vm-hM3Dq mice. The Rotarod (RotaRod Series 8, IITC Life Science, USA) was set to increase from 4 r/min to 40 r/min over 3 min. Mice were trained for 4 days to maintain their position and to avoid falling from the rod. During daily training, the mice were allowed 5 trials with a 5-min interval between trials. The mean falling latency of 5 trials was calculated for each mouse across training days.

Optogenetic Manipulation

To identify the DCN^Vm neurons in vivo, we used a blue laser diode (PL450B, Osram) to emit optogenetic stimulation in the DCN during the first half-hour of the daily light phase (08:30–09:00). The diode was activated by pulse current (120 mA–150 mA) from a laser diode controller (LDC-205C, Thorlabs). Fifty trains of pulses (20 Hz, 450 nm wavelength, 10 ms light on and 40 ms light off, 500 ms train duration) were delivered. The inter-stimulation interval varied between 20 and 40 s with a mean value of 30 s.

To evaluate how the optogenetic activation of DCN^Vm neurons influences the CR performance, we used a blue laser diode (PL450B) to emit 150-ms pulse stimulation (5.0 mW/mm²–6.0 mW/mm² measured at the fiber tip) in DCN^Vm-ChR2 mice. The stimulation was triggered by the onset of CS with a 250-ms delay. To evaluate how the optogenetic inhibition of DCN^Vm-ArchT neurons influences the CR performance, we used a green laser diode (PL520B, Osram) to emit 250-ms stimulation (10.0-15.0 mW/mm² measured at the fiber tip). The stimulation was triggered by the onset of CS with a 150-ms delay.

To evaluate the effect of optogenetic activation of DCN^Vm neurons on the neuronal activity in the cingulate cortex, each stimulation trial consisted of 20-Hz blue laser pulse trains (450 nm wavelength, 10 ms light on and 40 ms light off, 500 ms duration). Fifty trains of blue laser pulses were delivered. The inter-train interval was randomly distributed between 20 and 40 s.

Multiple Channel Recording and Optogenetic Identification of DCN^Vm Units

As we recently described [32, 33], multiple-unit signals were continuously recorded at 20 kHz using an RHD2000 neural data acquisition board (C3100, Intan Technologies, USA) and stored for offline analysis. The recorded spikes were extracted from high-pass filtered signals (cutoff frequency: 800 Hz), and their waveforms were projected onto a common template obtained by principal component analysis of the filtered data [34]. Single-unit spikes were isolated off-line using both semi-automatic clustering by the software KlustaKwik [35] and manual clustering with the software Klusters [36]. The accuracy of unit clustering was verified by confirming the existence of a 2-ms refractory period devoid of spikes in the autocorrelogram of a given single unit. A clustered unit was identified as a DCN^Vm-ChR2 neuron if its spikes were reliably evoked by laser pulses with short first-spike latency (≤6 ms) and with waveforms of the laser-evoked and spontaneous spikes highly similar (correlation coefficient ≥0.98) [37].

Chemogenetic Manipulation

Four weeks after virus injection, the DCN^Vm-hM4Di and DCN^Vm-hM3Dq mice were allowed to habituate to the training environment for 4 days. On the test days, CNO (5 μmol/L) or vehicle (0.9% NaCl) was injected intraperitoneally at zeitgeber time (ZT 0, 08:00 a.m.). The injections were performed on 2 consecutive days in a random arrangement. Two hours after injection, the motor coordination of mice was evaluated by the Rotarod test.

Data Analysis

Analysis of eyeblink responses

As we reported recently [38], the EMG activity of the mouse orbicularis oculi muscle was rectified and integrated with a 1-ms time constant. For each trial, we quantified the EMG activity for the baseline period (1 ms–350 ms before the CS onset) across 100 daily trials. The baseline EMG activity was averaged, and the standard deviation (s.d.) was calculated. The average value plus 4 times the s.d. was defined as the threshold. Each trial with the maximum baseline EMG activity exceeding the threshold was defined as an invalid trial. The CR (51 ms–400 ms after the CS onset) and UR (1 ms–350 ms after US onset) were exclusively measured in valid trials. An eyeblink response was defined as exceeding the average baseline by 4 s.d. of the baseline activity for at least 25 ms. Any significant eyeblink response during these periods was counted as a CR or a UR [38].

Categorical analysis of neuronal responses during tEBC

For each DCN neuron, the spikes recorded during each daily trial session were assigned to a series of 50-ms bins 1-s before and 1-s after CS onset. The average number of spikes in 20 bins before CS onset was used as the baseline activity for that trial. The firing rate (FR) of each bin was normalized by using the Z score as follows (#bin refers to arbitrary time bin):

$$Z=\left(F{R}_{\#bin}-meanF{R}_{\mathit{baseline}}\right)/s.d.\left(F{R}_{\mathit{baseline}}\right)$$

Changes in spike activity were considered significant if their Z scores differed from the normalized baseline firing levels by >2. A DCN unit with increased firing was defined by its significantly increased spike activity (i.e., Z >2) during the CS–US period, while a DCN unit with decreased firing was defined by its significant decrease in spike activity (i.e., Z ≤2). The remaining DCN neurons were classified as non-responsive units because of their insignificant changes in activity during the CS–US period.

Histological Verification

To visualize the tip locations of tetrodes, electrolytic lesions (30 μA DC for 10 s) were made at the end of multiple channel recordings. The mice were deeply anesthetized with 3% pentobarbital (100 mg/kg intraperitoneal) and transcardially perfused with saline followed by 4% paraformaldehyde (PFA; prepared in 0.01 mol/L phosphate buffer, pH 7.4). The brain was removed and post-fixed in 4% PFA for 8 h. The brain was transferred to 30% sucrose in PBS overnight for cryoprotection. Coronal sections were cut at 30 μm on a freezing microtome (CM1900, Leica, Germany) and collected in phosphate buffered saline (PBS; 0.01 mol/L, pH 7.4) for later staining. After three washes (5 min each), the sections were mounted in Fluoromount medium with DAPI fluorescence (F6057, Sigma-Aldrich). The tip placements of tetrodes in either the DCN or the cingulate cortex were checked using a fluorescence microscope (BX53, Olympus, Tokyo, Japan). Histological processing was also applied to locate the sites of optical fiber implantation. Data were excluded if the locations were not correct.

To stain calbindin-expressing neurons in the ventral thalamus, 30-μm coronal sections were cut using the procedure described above. The sections were washed three times for 5 min each with PBS (pH 7.4). Free-floating sections were permeabilized (0.2% Triton X-100) for 40 min, followed by blocking for 1.5 h (5% normal goat serum in 0.01% PBS) at room temperature. The sections were then incubated with calbindin antibody (1:100, Santa Cruz, Sc-7691 goat polyclonal) overnight at 4 °C. After three washes (10 min each), the sections were washed and then incubated with secondary antibody (donkey anti-goat 488, Thermo Fisher Scientific, Cat no. A11055) for 2 h at room temperature. After washing with PBS, the sections were mounted with coverslips. Nuclei were stained with DAPI. Fluorescence images were captured using an Olympus BX53 microscope.

Statistics

Data are expressed as the mean ± SEM. We first tested each dataset for normality using the Shapiro-Wilk test. Parametric tests were used if the dataset passed the normality test. Otherwise, non-parametric tests were used. The change in neuronal activity across tEBC training was determined by an independent t test (two-tailed). The effects of optogenetic/chemical manipulations on CR performance or motor coordination were determined by paired t tests (two-tailed). The Wilcoxon rank sum test was used when the data were not normally distributed. All statistical analyses were performed using SPSS or MatLab software as needed. Significance levels of data are denoted as *P <0.05, **P <0.01, and ***P <0.001. P >0.05 was considered not significant and denoted as n.s.

Results

The DCN Projects to the Vm in Mice

To assess the innervation of the ventral thalamus by DCN axons in the mouse brain, we used anterograde tracing of DCN neurons followed by brain imaging in the ventral thalamus (Fig. 1A). For this purpose, AAV2-Syn-MCS-mCherry-3FLAG was injected into the left DCN spanning the interpositus and lateral cerebellar nuclei (Fig. 1B). We found that mCherry⁺ fibers were evident in the right ventral thalamic area, including both the Vm and ventrolateral thalamus (VL) (Fig. 1C). The Vm and VL could be separated by the distribution of calbindin⁺ cells, with calbindin⁺ cells in the Vm and Calbindin⁻ cells in the VL (Fig. S2). After summarizing mCherry⁺ fibers across 3 mice, we found that the distribution pattern of mCherry⁺ fibers differed between the anterior and posterior Vm, with more mCherry⁺ fibers in the posterior Vm (Figs 1C and S2).

Fig. 1.

The DCN projects to the ventral thalamus in mice. A Schematic of viral injections for anterograde tracing of DCN axons in the ventral thalamus. B Representative images showing the distribution of mCherry⁺ neurons (red) in the interpositus (Int) and lateral (Lat) cerebellar nuclei (scale bar, 500 μm). Med, medial cerebellar nucleus. Inset, magnified view of the DCN neurons in the same panel (scale bar, 100 μm). C The distribution of DCN axons (red) in the Vm and VL. Inset, magnified view of the DCN axon terminals in the same panel (scale bar, 100 μm). Vm, ventromedial thalamus; VL, ventrolateral thalamus. D Schematic of viral injections for retrograde tracing the Vm-projecting DCN neurons (DCN^Vm). E Left, representative fluorescence image of showing retrograde tracer retro-beads in the Vm; right, distribution of DCN^Vm neurons (red) in the interpositus (Int) and lateral (Lat) cerebellar nuclei (scale bar, 500 μm or 200 μm). Inset, magnified view of the labeled DCN^Vm neurons (scale bar, 100 μm).

As the mCherry⁺ fibers could be fibers of passage in the Vm, we further examined whether the DCN axons formed synaptic contact with Vm neurons by employing a retrograde tracing method. To do this, we injected retrograde tracer retro-beads into the right Vm (Fig. 1D) and found that Vm-projecting neurons (DCN^Vm neurons) labeled with retro-beads were located in the left DCN, including both the interpositus and lateral cerebellar nuclei (Fig. 1E). Together, these results showed that the DCN innervates the Vm in mice.

Optogenetic Identification of DCN^Vm Neurons in vivo

Specifically tracing and manipulating DCN^Vm neurons are the prerequisites for determining their roles in associative sensorimotor learning. To specifically trace the DCN^Vm neurons, we injected AAV with Cre-dependent expression of red fluorescent protein (AAV2-Ef1α-DIO-mCherry) into the left DCN, in combination with the injection of a retrograde AAV coding for cyclization recombination enzyme (AAV-retro-Syn-CRE) in the right Vm (Fig. 2A). These procedures labeled a group of mCherry⁺ DCN^Vm neurons (Fig. 2B, left). Quantification of their cell body distribution indicated that 70 ± 4% of traced DCN^Vm neurons were located in the interpositus nucleus, with 18 ± 2% in the lateral nucleus and 12 ± 4% in the medial nucleus (averaged from 3 mice). The overwhelming majority of DCN^Vm neuronal terminals were located in the Vm (Fig. 2B, right). Therefore, our results verified an effective method to trace DCN^Vm neurons.

Fig. 2.

Tracing neurons in the DCN projecting to the Vm. A Schematic of viral injections for retrograde tracing of DCN neurons projecting to the Vm (DCN^Vm). B Left, representative fluorescence image showing DCN^Vm neurons expressing mCherry in the medial (Med), interpositus (Int), and lateral (Lat) DCN; right, representative fluorescence image of showing the axon terminals of DCN^Vm neurons in the Vm (scale bar, 100 μm). VL, ventrolateral thalamus; Vm, ventromedial thalamus.

Combing this tracing method with multi-channel recording, we then identified DCN^Vm neurons in vivo. We injected AAV2-Ef1α-DIO-hChR2 (H134R)-mCherry into the left DCN and AAV-retro-Syn-CRE into the right Vm (Fig. 3A, top). Using this approach, the excitatory opsin ChR2 was specifically expressed on DCN^Vm neurons (Fig. 3A, lower). The axons of DCN^Vm neurons were carefully examined in the Vm and were found not to spread to the adjacent VL (Fig. S3). We then implanted a diode-tetrode assembly into the cerebellum and applied 20-Hz blue laser pulses (450 nm wavelength, 10-ms laser on, 40-ms laser off per pulse, 10 pulses per train) to activate the ChR2-expressing DCN^Vm neurons. A unit was identified as a DCN^Vm neuron if spikes were reliably evoked by blue laser pulses with a short first-spike latency (Fig. 3B, C), and with highly similar waveforms of the laser-evoked and spontaneous spikes (correlation coefficient >0.98, Fig. 3D). We isolated a total of 537 DCN units in 10 mice. Among these units, 81 were identified as DCN^Vm neurons by laser-evoked spiking at 4.2 ± 0.2 ms first-spike latency (Fig. 3C). The average firing rate of optogenetically-identified DCN^Vm neurons was 17.8 ± 1.8 Hz (n = 81 units from 10 mice, Fig. 3B, lower).

Fig. 3.

In vivo optogenetic identification of DCN^Vm neurons. A Upper, schematic of optogenetic identification of DCN^Vm neurons in vivo; lower, representative fluorescence image of showing a recording site in the DCN (scale bar, 200 μm). Inset, magnified view of the recording site in the same panel (scale bar, 100 μm). B Upper, example recording from an optogenetically-identified DCN^Vm neuron; lower, averaged blue laser-evoked firing activity in optogenetically-identified DCN^Vm neurons (averaged from 81 units in 10 mice). C Distribution of latency of laser-evoked spiking for all optogenetically-identified DCN^Vm neurons (n = 81 units from 10 mice). D Distribution of Pearson correlation coefficients between blue laser-evoked and spontaneous spike waveforms for all optogenetically-identified DCN^Vm neurons (n = 81 units from 10 mice) (scale bars, 0.5 ms and 0.1 mV).

DCN^Vm Neuronal Activity is Modulated by Associative Sensorimotor Learning.

We then explored how the optogenetically-identified DCN^Vm neurons respond during learning an associative sensorimotor task. The freely-moving mice were trained to learn a tEBC task, in which a LED CS was paired with an air-puff US (Fig. 4A). To avoid the aversive air-puff US, the mice had to respond to the LED CS and adaptively close their upper eyelid just before the presentation of the US (Fig. 4B). We found that the CR incidence remained relatively low on days 1 and 2, and reached an asymptotic level on days 4 and 5 (Fig. 4C). These results indicated that the CS–US association was learned in the tested mice across 5 training days. Based on the CR level, we separated behavioral training into two stages: the early-learning stage with relatively few CRs (days 1 and 2) and the late-learning stage with an asymptotic CR level (days 4 and 5, Fig. 4C).

Fig. 4.

CS-evoked DCN^Vm neuronal activity is modulated by tEBC training. A Overview of the experimental design. Before daily training, 450-nm blue laser pulses are presented to optogenetically identify DCN^Vm neurons in vivo (Epoch #1). Then, the mice (n = 10) are subjected to trace eyeblink conditioning (tEBC) training (Epoch #2). B Averaged eyelid responses in a representative mouse across 5 consecutive training days [arrowheads, conditioned eyeblink response (CR); scale bar, 250 ms]. C CR incidence measured from 10 mice across 5 consecutive training days. The mice show a clear increase in CR incidence across tEBC training (F _{(4, 36)} = 5.267, P = 0.002, one-way ANOVA with repeated measures). The CR incidence at the late-learning stage (days 4 and 5) is significantly higher than that at the early-learning stage (t ₍₁₈₎ = −2.709, P = 0.014, independent t test). D Pseudo-color map showing the Z-score-transformed firing activity of DCN^Vm neurons across distinct learning stages (early, n = 28 vs late, n = 34). E Stacked bar graphs illustrating the proportions of DCN^Vm neurons with significantly altered CS-evoked activity (both increased and decreased) and those with no response. A greater proportion of DCN^Vm neurons show CS-evoked elevated activity at the late-learning stage than at the early-learning stage [late, 44.1% (15/34) vs early, 28.6% (8/28)]. F Average CS-evoked DCN^Vm activity in the early-learning (n = 28, blue trace) and late-learning (n = 34, red trace) stages. G CS-evoked activity of DCN^Vm neurons (n = 34, red circles) at the late-learning stage is significantly greater than at the early-learning stage (n = 28, blue circles; Z = −2.1288, P = 0.0333, Wilcoxon rank sum test). H US-evoked activity of DCN^Vm neurons (n = 34, red circles) at the late-learning stage are comparable to that at the early-learning stage (n = 28, blue circles; Z = 0.4314, P = 0.6662, Wilcoxon rank sum test). Data are expressed as the mean ± SEM; *P <0.05, n.s., not significant. CS, conditioned stimulus (blue bar); US, unconditioned stimulus (gray bar); LD, laser diode.

Intriguingly, we found that only a few optogenetically-identified DCN^Vm neurons responded to presentation of the CS at the early stage of learning (Fig. 4D, left). By contrast, a greater proportion of DCN^Vm neurons exhibited significantly elevated firing activity after the presentation of CSs at the late stage of learning (Fig. 4D, E). In particular, the elevated activity mainly occurred 150 ms–250 ms before presentation of the USs (Fig. 4D, F). Our statistical analysis revealed that the DCN^Vm neurons had significantly greater CS-evoked activity at the late than at the early stage of learning (Fig. 4F, G). Nevertheless, we found no significant difference in the US-evoked DCN^Vm activity between the early- and late-learning stages (Fig. 4F, H). These results indicated that the CS-evoked DCN^Vm activity varied with CR performance during the acquisition of tEBC.

CS-evoked DCN^Vm Neuronal Activity Signals Associative Sensorimotor Learning Responses

To further quantify the co-variation of CS-evoked DCN^Vm activity with CR performance, we compared CS-evoked DCN^Vm activity between the CR and no-CR states when the CRs were learned on days 4 and 5. We found that the CS-evoked activity of DCN^Vm neurons in the CR trials was significantly greater than that in the no-CR trials (Fig. 5A, B). By contrast, no difference in US-evoked DCN^Vm activity was found between the CR- and no-CR states (Fig. 5A, C). These results provided further evidence that the CS-evoked activity of DCN^Vm neurons signals associative sensorimotor learning responses in conditioned mice.

Fig. 5.

DCN^Vm neuronal activity in the CR vs no-CR trials. A Averaged CS-evoked activity of DCN^Vm neurons (n = 30) in the CR vs no-CR trials. CR, conditioned eyelid response; CS, conditioned stimulus (blue); US, unconditioned stimulus (gray). B CS-evoked DCN^Vm firing activity in CR trials is significantly greater than in no-CR trials (t ₍₂₉₎ = 2.8739, P = 0.0075, paired t test). C US-evoked DCN^Vm firing activity in CR trials is comparable to that in no-CR trials (t ₍₂₉₎ = −0.1062, P = 0.9161, paired t test). For B and C, 4 DCN^Vm neurons were excluded from analysis because they generated too few spikes to normalize their firing in the no-CR state. Data are expressed as the mean ± SEM; **P <0.01, n.s., not significant.

To determine whether the correlation between CS-evoked activity and CR performance only occurred in DCN^Vm neurons, we further evaluated the CS-evoked activity in the other DCN neurons that were not significantly modulated by the optogenetic stimulation (n = 456 non-DCN^Vm units from 10 mice, Fig. S4). In contrast to the increase in CR incidence across tEBC training, the non-DCN^Vm neurons had decreased CS-evoked responses at the late learning stage (Fig. S5). In addition, the non-DCN^Vm neurons showed relatively lower CS-evoked activity than the DCN^Vm units (Z = −1.1593, P = 0.2464, Wilcoxon rank sum test, Figs 4 and S5), although the difference did not reach a significant level. Considering the decrease in CS-evoked responses of non-DCN^Vm neurons, our results suggested that the CS-evoked activity of DCN^Vm neurons, but not that of the non-DCN^Vm neurons, was most likely modulated by associative sensorimotor learning responses.

DCN^Vm Neurons are Involved in Amplifying Associative Sensorimotor Learning Responses

The CS-evoked DCN^Vm activity developed across sensorimotor learning and was correlated with the behavioral outcome in terms of CR and no-CR states, implying that it may contribute to the performance of the CR. Consequently, we set out to quantify this contribution by acutely activating this firing response during the performance of learned CRs. For this purpose, we tested another group of mice in which the opsin ChR2 was virally expressed in the DCN^Vm neurons (Fig. 6A, left). Moreover, to mimic the temporal pattern of DCN^Vm firing during tEBC, a 150-ms blue laser pulse was presented just before the onset of the US (Fig. 6A, right). We found that acute activation of DCN^Vm neurons during this period resulted in significant increases in the incidence and amplitude of learned CRs (Fig. 6B–E). Moreover, acute activation of DCN^Vm neurons tended to shift the CR peak from 248.6 ± 18.0 ms to 281.8 ± 20.5 ms after the CS onset (Fig. 6F). Meanwhile, optogenetic activation of DCN^Vm neurons without a CS did not induce an apparent eyeblink response in naïve mice (Fig. S6 and Supplementary movie 2), making it unlikely that the optogenetically ChR2-driven amplification effects described above resulted from non-specific eyelid motor responses.

Fig. 6.

Optogenetic activation of DCN^Vm neurons improves CR performance. A Left, coronal section of a mouse brain showing ChR2-mCherry expression (red) stained with DAPI (blue) in DCN^Vm neurons (scale bar, 200 μm); right, overview of the experimental design. Two groups of mice (n = 9 for ChR2-expressing and n = 7 for mCherry-expression in DCN^Vm neurons) received CS–US paired presentations for 5 consecutive days. B Averaged eyeblink responses illustrating the effect of optogenetic DCN^Vm activation on the performance of learned CRs. The optogenetic stimulation is trigged by the CS, and is presented 1 ms–150 ms before the onset of the US. C Left, smoothed orbicularis oculi electromyography (O.O.EMG) recorded from the left upper eyelid during tEBC. Each line represents O.O.EMG activity from individual trials (1–100, with Trial 1 at the bottom and Trial 100 at the top). Right, smoothed O.O.M. EMG recorded from the left upper eyelid. During tEBC, the optogenetic stimulation was trigged by the CS, and are presented 150 ms before the onset of the US. For B and C, CS, conditioned stimulus (blue); US, unconditioned stimulus (gray). D–F CR incidence (D), CR amplitude (E), and latency to the CR peak (F) measured from DCN^Vm-ChR2 (n = 9, blue bars) and DCN^Vm-mCherry (n = 7, open bars) mice. Optogenetic activation of DCN^Vm neurons increases the CR incidence and peak amplitude in DCN^Vm-ChR2 mice (CR incidence, t ₍₈₎ = −3.419, P = 0.009; increase in CR peak amplitude: t ₍₈₎ = −3.013, P = 0.017, paired t tests). Data are expressed as the mean ± SEM; **P <0.01, *P <0.05, n.s., not significant.

If the CS-evoked DCN^Vm activity contributed to CR performance by providing amplification signals, this contribution should also be quantified by acutely inhibiting these signals during the performance of learned CRs. We therefore tested another group of well-trained mice in which the inhibitory opsin ArchT was virally expressed in the DCN^Vm neurons (Fig. 7A, left). Optogenetically suppressing the activity of DCN^Vm neurons for 250 ms with green light (520-nm wavelength ) before the US onset (Fig. 7A, right) resulted in a significant reduction in the CR amplitude, but not of the CR incidence (Fig. 7B–D). These results suggest that the CS-evoked DCN^Vm activity does contribute to amplifying the learned CR.

Fig 7.

Optogenetic inhibition of DCN^Vm neurons impairs CR performance. A Left, coronal section of a mouse brain showing ArchT-GFP expression (green) stained with DAPI (blue) in DCN^Vm neurons (scale bar, 200 μm); right, overview of the experimental design. Two groups of mice (n = 6 for ArchT-expression and n = 5 for GFP-expression in DCN^Vm neurons) receive CS–US paired presentations for 5 consecutive days. B Averaged eyeblink responses illustrating the effect of optogenetic DCN^Vm inhibition on CR performance. An optogenetic stimulus is trigged by the CS, and is presented 1 ms–250 ms before the onset of the US. C, D CR amplitude (C) and CR incidence (D) measured from DCN^Vm-ArchT (n = 6, green bars) and DCN^Vm-GFP (n = 5, open bars) mice. Optogenetic inhibition of the DCN^Vm neurons significantly diminishes the CR peak amplitude in DCN^Vm-ArchT mice (t ₍₅₎ = 2.663, P = 0.037, paired t test). In contrast, optogenetic inhibition of DCN^Vm neurons has no effect on the CR incidence in DCN^Vm-ArchT mice (t ₍₅₎ = 0.858, P = 0.430, paired t test). Data are expressed as the mean ± SEM; *P <0.05, n.s., not significant.

Optogenetic Activation of DCN^Vm Neurons Increases Firing Activity in the Cingulate Cortex

Sensorimotor learning relies on the association between time-separated CSs and USs. The Cg has been suggested to bridge the time gap between the CS and US during tEBC [23–25]. Considering that Vm neurons send diffuse projections to cerebral cortical areas including the Cg [22], we thus wondered whether and how the activation of DCN^Vm neurons influenced neuronal activity in the Cg. To address this, we made multi-channel unit recordings in the Cg (Fig. 8A, upper). Meanwhile, DCN^Vm neurons expressed the excitatory opsin ChR2 (Fig. 8A, lower) and we measured the effect of optogenetic activation of DCN^Vm neurons on the Cg neuronal activity. We found that optogenetic activation of the DCN^Vm neurons resulted in increased firing in 31.8% (50/157) of the recorded Cg units, while it also suppressed the activity in 20.4% (32/157) of the recorded Cg units (Fig. 8B, upper and 8C). The average firing rates of Cg units activated by DCN^Vm stimulation were significantly higher than those of the Cg units suppressed by DCN^Vm activation (Fig. 8B, lower). In particular, the Cg units activated by DCN^Vm stimulation had elevated CS-evoked firing activity during the acquisition of tEBC (Fig. 8D). By contrast, the Cg units suppressed by DCN^Vm stimulation did not show a CS-evoked increase in firing activity (Fig. 8D). In addition, we confirmed that those Vm neurons receiving DCN inputs send axons to the Cg region where multi-channel recordings were made (Fig. S7). These results indicated that the activation of DCN^Vm neurons enhances CS-associated information processing in the Cg.

Fig. 8.

Optogenetic activation of DCN^Vm neurons alters firing activity in cingulate cortical neurons. A Upper, schematic of tetrode recording in the cingulate cortex (Cg) and the optogenetic activation of DCN^Vm neurons; lower, representative DAPI image showing a tetrode recording site in the Cg (scale bar, 500 μm). B Upper, heatmap rows represent Z-score-transformed average peristimulus time histograms for individual Cg units (n = 157 units from 3 mice), and columns represent time bins relative to the onset of optogenetic stimulation (10-ms bin width); lower, plot shows the average firing responses of Cg units activated (n = 50, red trace) or suppressed (n = 32, blue trace) by DCN^Vm. The average firing rates of Cg units activated by DCN^Vm activation were significantly higher than those suppressed by DCN^Vm activation (Z = 3.7190, P = 0.0002, Wilcoxon rank sum test). C Proportions of increased firing (31.8%, red), decreased firing (20.4%, blue) and not significantly modulated (47.8%, gray) evoked in Cg units by DCN^Vm activation. D Plot showing CS-evoked firing responses of Cg units activated (n = 50, red trace) or suppressed (n = 32, blue trace) by DCN^Vm activation. The CS responsiveness of Cg units with increased firing was significantly higher than those with decreased firing evoked by DCN^Vm activation (Z = 4.2056; P = 2.6045 × 10^-5, Wilcoxon rank sum test). Data are expressed as the mean ± SEM; shaded areas indicate SEM; ***P <0.001.

Chemogenetic Manipulation of DCN^Vm Neurons Has No Effects on Non-associative Motor Function

To determine whether the DCN^Vm neurons are also involved in non-associative motor functions, we assessed their role in motor coordination by the Rotarod test (Fig. 9A). The mice were subjected to Rotarod training for 4 consecutive days and showed an increased latency to falling from the rotating rod across training days (Fig. 9B, D). Nevertheless, we found that chemogenetic inhibition of the DCN^Vm neurons had no effect on motor coordination as evidenced by comparable fall latencies between the CNO- and saline-injected DCN^Vm-hM4Di mice on days 5 and 6 (Fig. 9C). Likewise, chemogenetic activation of the DCN^Vm neurons had no apparent influence on motor coordination, supported by the evidence that there was no difference in the latency to fall between the CNO- and saline-injected DCN^Vm-hM3Dq mice on days 5 and 6 (Fig. 9E). Together, these data suggest that DCN^Vm neurons are involved in associative sensorimotor learning but not in non-associative motor functions.

Fig. 9.

Chemogenetic manipulation of DCN^Vm neurons has no effects on motor coordination. A Upper, schematic for the chemogenetic manipulation of DCN^Vm neurons; lower, coronal section of a representative mouse brain showing hM4Di (or hM3Dq)-mCherry expression (red) stained with DAPI (blue) in DCN^Vm neurons (scale bar, 1 mm). B Mean latency to fall from the rod in DCN^Vm-hM4Di mice increased from day 1 to day 4 (F _{(3, 15)} = 3.413, P = 0.045, n = 6 mice, one-way ANOVA with repeated measures). C Effects of CNO and saline injection on motor coordination in DCN^Vm-hM4Di mice. There is no significant difference in the mean latency to fall between the CNO (red) and saline (open) injections (n = 6, t ₍₅₎ = −1.041, P = 0.346, paired t test). D Mean latency to fall from the rod in DCN^Vm-hM3Dq mice likewise, increased from day 1 to day 4 (F _{(3, 15)} = 4.242, P = 0.023, n = 6 mice, one-way ANOVA with repeated measures). E Effects of CNO and saline injections on motor coordination in DCN^Vm-hM3Dq mice. There is no significant difference in the mean latency to fall between the CNO (red bar) and saline (open bar) injections (t ₍₅₎ = −0.622, P = 0.561, paired t test). Data are expressed as the mean ± SEM; n.s., not significant.

Discussion

Deconstructing the DCN neurons concerning their axon terminal targets among motor circuitry provides a powerful framework for uncovering the detailed mechanisms underlying associative sensorimotor learning. Here, we used virus-based genetic techniques to define a subpopulation of neurons in the DCN with direct inputs to the Vm and explore their functional relevance in tEBC. We found that the DCN^Vm neurons were highly modulated by tEBC training. Optogenetic activation of the DCN^Vm neurons amplified the CR, whereas optogenetic inhibition of the DCN^Vm neurons diminished the CR. Moreover, optogenetic activation of the DCN^Vm neurons resulted in a rapid increase in Cg neuronal activity. Our data delineate a novel pathway through which the DCN modulates the strength of associative sensorimotor responses.

As the cerebellum’s final and common output, the DCN plays a critical role in associative sensorimotor learning [3–5, 39]. Nevertheless, the role of distinct subpopulations of DCN neurons in this context needs to be further elucidated. It has been suggested that the cerebello–rubro–spinal pathway is associated with the coordination of large movements of the extremities [40–42]. In contrast, the cerebello–thalamo–cortical pathway is more associated with the refinement of motor responses by integrating sensory information and internal motor commands [19]. Here, we found a subpopulation of DCN neurons whose axons specifically project to the Vm. The DCN^Vm neurons occupied ~15% of recorded DCN neurons, and their CS-evoked firing activity was associated with the CR performance. These characteristics prompted us to test further whether DCN^Vm neurons are a critical cellular component of the DCN in tEBC. We found that optogenetic activation of the DCN neurons significantly amplified the magnitude of the CR in trained mice. Of note, this amplification effect was unlikely to result from non-specific eyelid motor responses directly induced by laser stimulation. A previous study reported that electrical stimulation or chemical inhibition of the DCN modulates the amplitude of evoked CRs in alert behaving cats [43]. Extrapolating from previous studies, our current data further revealed the role of a specific Vm-projecting subpopulation of DCN neurons in modulating associative sensorimotor responses. Nevertheless, it is necessary to determine and clarify whether the functions of the three cerebellar nuclei (interpositus, lateral, and medial) differ in tEBC since all three nuclei have neurons projecting to the Vm.

How do the DCN^Vm neurons participate in the modulation of CR performance? Previous studies have demonstrated that the prefrontal cortex (PFC) plays critical roles in the proper timing of the CR [44] and its appropriate release [45]. Interestingly, a pharmacological study revealed that inactivation of the DCN causes a reduction in PFC neuronal activity during tEBC [46], indicating a DCN contribution to PFC activity during sensorimotor learning. Nevertheless, the specific pathway by which DCN signals reach the PFC has not been determined. It has been documented that neurons in the Vm diffusely project to cerebral cortical areas, including the PFC [19, 22]. Our tracing and in vivo electrophysiological experiments showed further evidence that DCN^Vm neurons influence a fast-conducting class of PFC-projecting Vm neurons, since the optogenetic activation of DCN^Vm neurons can cause a rapid elevation in neuronal responsiveness in a PFC subregion (i.e., the Cg area). Considering that neurons in the Cg area of the PFC selectively activate a short-latency modulatory pathway for tEBC [27–29], it is reasonable to propose that the DCN may provide a positive feedback circuit element to elevate the Cg neuronal responsiveness indirectly via the Vm, and then improve the CR performance. However, there is a possibility that the DCN^Vm neurons project to other brain regions, particularly those involved in tEBC. The increased firing rate of Cg neurons induced by DCN^Vm activation may be indirectly caused by the activation of the projections to other brain regions.

In this study, we discovered that the optogenetic inhibition of DCN^Vm neurons resulted in ~30% reduction in the amplitude of CRs in well-trained mice. This result suggests that DCN^Vm neurons are unlikely to be the cellular component essential for driving the initial occurrence of CRs. Instead, the DCN^Vm neurons may preferentially function to improve the performance of learned CRs, similar to the contribution of motor cortex projection neurons [47]. Interestingly, it has been reported that a subpopulation of glutamatergic DCN neurons innervates the granule cells in the cerebellar cortex and indirectly inhibits the Purkinje cells to improve CR performance [16]. Therefore, our current results indicate that there is diversity in the intra- and extra-cerebellar connections by which the modulation of CR performance is ensured. Nevertheless, future experiments using neuronal tracing and optogenetic techniques will provide further insights into whether and how these two subpopulations of DCN neurons interact during associative sensorimotor learning.

Although it is well-recognized that the cerebellum critically participates in non-associative motor coordination [48, 49], no data are currently available on whether DCN^Vm neurons are inevitably involved in this process. Here, we showed that chemogenetic manipulation of the DCN^Vm neurons had no effect on the Rotarod test score, as evidenced by comparable falling latencies between the CNO- and saline-injected mice. This result suggested that, unlike the DCN units projecting to the spinal cord [41] and the inferior olivary nuclei [50], the DCN^Vm neurons play a minimal role in non-associative motor coordination. Together with the involvement of DCN neurons projecting to the ventral medullary reticular formation in controlling the performance of URs [17], we propose that target selectivity among neuronal subpopulations within the DCN may offer specialized control of various aspects of sensorimotor learning responses.

Here, we focused on the role of DCN^Vm neurons in associative sensorimotor learning. However, it should be noted that the DCN innervates more in the VL than in the Vm [15, 18, 19, 51]. It has been suggested that the DCN interacts with the primary motor cortex via glutamatergic neurons in the VL to participate in motor planning [52]. Unlike the VL, there are abundant calbindin⁺ neurons in the Vm [20, 21]. In addition, the Vm thalamus sends diffuse projections to the superficial layer (layer I) of wide cerebral cortical areas [22]. We speculate that distinct cerebello–thalamo–cerebral pathways have different impacts on motor modulation. Considering that the diffuse Vm has been implicated in several non-motor functions [52–55], it will be interesting to investigate the additional roles of DCN^Vm neurons in the regulation of wakefulness and social behaviors, which may expand our knowledge of the cerebellum’s non-motor functions.

It also should be noted that the firing rates of DCN^Vm neurons significantly increased during the US period. Moreover, optogenetic inhibition of the DCN^Vm neurons appeared to diminish UR amplitude. Recent work has reported that the outputs from the medial part of DCN fine-tune the performance of URs [17]. Indeed, we found that ~15% of DCN^Vm neurons were distributed in the medial part of the DCN. Therefore, our current results hint that the DCN^Vm neurons may also participate in the modulation of UR performance. However, more experiments are required to verify the involvement of DCN^Vm neurons in UR performance.

Previous studies have mainly focused on how the DCN as a whole is involved in associative sensorimotor learning [56]. Based on their transmitters, efforts have been made to elucidate various types of DCN neurons in associative sensorimotor leaning [57, 58]. However, the roles of subpopulations of DCN neurons with distinct target zones have been largely neglected. Our findings advance the understanding of precise ways by which the DCN modulates diverse aspects of associative sensorimotor responses.

Supplementary Information

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Conflict of interest

The authors declare that they have no conflicts of interest.