Superior Colliculus Controls the Activity of the Substantia Nigra Pars Compacta and Ventral Tegmental Area in an Asymmetrical Manner

Kamil Pradel; Adrian Tymorek; Martyna Marzec; Łukasz Chrobok; Wojciech Solecki; Tomasz Błasiak

doi:10.1523/JNEUROSCI.1976-22.2024

Abstract

Dopaminergic (DA) neurons of the substantia nigra pars compacta (SNc) and ventral tegmental area (VTA) play a crucial role in controlling animals’ orienting and approach behaviors toward relevant environmental stimuli. The ventral midbrain receives sensory input from the superior colliculus (SC), a tectal region that processes information from contralateral receptive fields of various modalities. Given the significant influence of dopamine release imbalance in the left and right striatum on animals’ movement direction, our study aimed to investigate the lateralization of the connection between the lateral SC and the midbrain DA system in male rats. We explored the circuit's anatomy using transsynaptic viral tract-tracing and its physiology using in vivo single-unit and ex vivo multi-electrode array recordings of SNc and VTA neuronal activity combined with optogenetic stimulation of either the ipsilateral or contralateral SC or its terminals. During the experiments, DA neurons were identified optogenetically (in vivo recordings) or pharmacologically (ex vivo recordings). Anatomical findings revealed a bilateral innervation pattern of the lateral SC to the ventral midbrain, with a significantly stronger ipsilateral connection, particularly evident in the SNc, involving both DA and non-DA neurons. This anatomical asymmetry was also expressed during in vivo and ex vivo recordings, which showed a predominance of ipsilateral connections, especially within the SNc. Ex vivo recordings also confirmed that this lateralized pathway is direct. The described features of the SC→VTA/SNc neuronal circuit, particularly its anatomical and physiological asymmetry, suggest its involvement in orienting and approach behaviors guided by the direction of incoming sensory stimuli.

Significance Statement

The direction of animals’ behavior is a manifestation of asymmetry in dopamine (DA) release between the left and right striatum—unilateral activation of DA neurons biases movement toward the contralateral side. Our study demonstrates that such activation is induced by the ipsilateral superior colliculus (SC), which processes sensory information from the contralateral side of the body. Notably, our previous findings indicate that the SC innervates and activates the rostromedial tegmental nucleus, a primary inhibitory input to the DA system, albeit in the contralateral hemisphere. Thus, our research describes an SC-originating neuronal circuit that directly enhances the activity of ipsilateral DA neurons while simultaneously diminishing the activity of contralateral DA neurons, thereby amplifying the imbalance in DA release between hemispheres.

Introduction

To successfully interact with the external world, animals must constantly assess the environment and choose proper actions directed toward it. The key area of the brain associated with this process is the striatum, where gating and filtering of information flow, along with action selection, take place. The striatum itself is strongly influenced by dopamine released from the robust dopaminergic innervation originating in the ventral tegmental area (VTA) and the substantia nigra pars compacta (SNc), brain regions crucial for controlling experience-based learning, motivation, and locomotion (Wise, 2004; Baik, 2013). To optimize the choice of motor actions, dopaminergic neurons perform calculations based on extensive information from multiple brain regions about both the internal state of the animal and the external world. The latter is largely provided by the superior colliculus (SC), a subcortical brain region processing sensory information originating primarily from the contralateral field of perception (May, 2006; Redgrave et al., 2010), while the former is represented by a diverse innervation from many other brain regions (Watabe-Uchida et al., 2012). Notably, the choice of motor actions can be observed in its simplest form, when the animal's motor response must be chosen based on relatively sparse and unprocessed sensory stimuli. This response is crucial for orienting the animal, along with its sensors and effectors, toward the stimulus source—the SC projection to the ventral midbrain seems to be of high importance in that regard.

The SC has a layered structure that reflects its functionality. Superficial layers receive topographically mapped retinal input from the contralateral hemifield and relay visual information to, among other targets, deeper layers of the SC, which process multimodal sensory information and guide directed eyes, head, limbs, and body movements (Felsen and Mainen, 2008; Gandhi and Katnani, 2011). They are also involved in calculating displacement vectors for navigating in 3D space (Wilson et al., 2018; Masullo et al., 2019).

As mentioned, the SC innervates midbrain dopaminergic neurons (Coizet et al., 2003, 2007; Comoli et al., 2003; McHaffie et al., 2006; May et al., 2009; Yetnikoff et al., 2015; Masullo et al., 2019; Solié et al., 2022), and numerous electrophysiological studies have been conducted to describe the physiology of this circuit (Coizet et al., 2003, 2006; Comoli et al., 2003; Dommett et al., 2005; Bertram et al., 2014; Takakuwa et al., 2017; Zhou et al., 2019; Solié et al., 2022). However, most of these studies have overlooked the lateralization of the SC→SNc and/or SC→VTA projection, usually focusing only on the ipsilateral part of the circuit. Our recent findings highlight the importance of lateralization, showing that the SC innervates and controls the contralateral rostromedial tegmental nucleus (RMTg; Pradel et al., 2021), which provides a potent inhibitory input to the dopaminergic system (Jhou et al., 2009a,b; Bourdy and Barrot, 2012). If the SC indeed controls the left and right dopaminergic system in an opposite manner this would result in asymmetric DA release in the left and right striatum, as dopaminergic neurons predominantly project ipsilaterally (Molochnikov and Cohen, 2014).

Extensive research has demonstrated the crucial role of asymmetrical striatal DA release in directing animal movement. Lesion studies have shown that movement is directed contralaterally to the striatum with higher DA transmission and ipsilaterally to the one with lower DA transmission (Arbuthnott and Crow, 1971; Iwamoto et al., 1976; Bourdy et al., 2014). Pharmacological studies on both lesioned and naïve animals further support these observations (Zimmerberg et al., 1974; Jerussi and Glick, 1976; Joyce et al., 1981; Glick et al., 1988; Da Cunha et al., 2008; Molochnikov and Cohen, 2014). Consistently, unilateral optogenetic activation of the striatal Go pathway induces contraversive rotations and a contralateral decision bias in rodents (Kravitz et al., 2010; Tai et al., 2012; Tecuapetla et al., 2014).

Given these results, the laterality of the projection descending from the SC to the ventral midbrain is significant. Sensory information from one side of the body activates the contralateral SC, potentially causing dopaminergic neurons in the same hemisphere to fire, thus releasing DA on the same side preferentially. This striatal DA imbalance could elicit an orienting movement toward the contralateral side—i.e., toward the stimulus. To investigate this mechanism, we utilized anatomical, electrophysiological, and optogenetic approaches to characterize the SC→SNc and SC→VTA circuit in detail.

Materials and Methods

Animals

Wild-type and TH IRES-Cre^+/− transgenic (SD-Th-cre^tm1sage; Brown et al., 2013) male Sprague Dawley rats were bred in the Institute of Zoology and Biomedical Research, Jagiellonian University (Krakow, Poland) breeding facility. Animals were housed in a temperature- and humidity-controlled room (20–23°C and 40–60% humidity) under a 12 h light/dark cycle, with ad libitum access to water and food. All procedures were conducted during the light phase of the light/dark cycle. All experimental procedures were performed according to the EU guide for the Care and Use of Laboratory Animals and were approved by the Ethics Committee for Animal Experiments at the Institute of Pharmacology, Polish Academy of Sciences (Krakow, Poland).

Brain injection surgeries

All surgeries were conducted on 7–9-week-old rats under deep anesthesia induced by an intraperitoneal injection of ketamine and xylazine (100 mg/kg and 10 mg/kg body mass, respectively; Biowet-Puławy). The depth of the anesthesia was verified by checking animal's reflexes (paw pinch, tail pinch, and corneal reflex). During surgery, animal's temperature was controlled and maintained at 37°C using an automatic heating pad (temperature controller TCP-22; WMT). Animals were placed in a stereotaxic frame (SF-4100; ASI Instruments) using noninvasive ear bars (EB-945, 45° tip). Sagittal incision on top of the head was made, the skin and soft tissue were retracted, and then the bregma and lambda points were used to align the head of the animal in the dorsoventral axis. Following small craniotomies, viral microinjections were performed. For that purpose a paraffin oil-filled manual injection system consisting of a Hamilton syringe (0.5 or 1 µl) connected to a glass micropipette (20–40 µm tip) via 3-cm-long Tygon tubing was used. Micropipettes were prepared from glass capillaries (Vitrex Medical A/S) with a vertical puller (PE-21; Narishige International Instruments). For transsynaptic anterograde tract tracing experiments, 80–200 nl of AAV1-hSyn-Cre-hGH [viral titer: 1.8 × 10¹³ viral genomes (vg)/ml; Addgene] was injected unilaterally into the SC of 10 rats (stereotaxic coordinates: −6.4 to −6.6 mm caudally, 1.8–2 mm laterally, and −4.4 to −4.6 mm ventrally from bregma point). For the in vivo electrophysiological experiments 300–400 nl of AAV2-hSyn-ChR2(H134R)-eYFP (viral titer: 3.1 × 10¹² vg/ml; UNC Vector Core) was injected bilaterally into the SC (stereotaxic coordinates: −6.4 to −6.8 mm caudally, ±1.8 to ±2 mm laterally, and −4.4 to −4.6 mm ventrally from bregma point). In the subset of these experiments, where TH-Cre^+/− rats were used, additional injections of AAV2-hSyn-DIO-ChrimsonR-tdTomato (viral titer: 6 × 10¹² vg/ml; UNC Vector Core) into the SNc and VTA (bilaterally, 400 nl per injection) were performed (stereotaxic coordinates for SNc: −5.4 mm caudally, ±1.7 mm laterally, and −7.8 mm ventrally from bregma point; and for VTA: −5.4 mm caudally, ±0.7 mm laterally, and −8 mm ventrally from bregma point). For the ex vivo electrophysiological experiments, 400 nl of AAV2-Syn-Chronos-GFP (viral titer: 2.1 × 10¹² vg/ml; UNC Vector Core) was injected unilaterally into the SC (−6.3 mm caudally, ±2 mm laterally, and −4.3 mm ventrally from bregma point) of 7-week-old rats. All the injections were performed at the rate of 100 nl/min, and after the injection pipettes were held in place for 5 min before retracting. Stereotaxic coordinates used for the injections were obtained using a rat brain atlas (Paxinos and Watson, 2007). At the end of surgery, the skin incision was sutured, and the wound was covered with antibacterial balm (Tribiotic; Kato Labs). The animals were also subcutaneously injected with the anti-inflammatory drug (Tolfedine, 4 mg/kg body mass; Biowet-Puławy) and analgesic (Torbugesic, 0.2 mg/kg body mass; Biowet-Puławy). Afterward, animals were placed in a clean homecage to recover, and the antibiotics were added to their drinking water for next 5 d (Sul-Tridin 24%, 1 ml/300 ml of water; Biowet-Puławy).

Anatomical experiments

Wild-type animals were euthanized 3 weeks after the injection of transsynaptic viral vector (AAV1-hSyn-Cre-hGH; details above, Brain injection surgeries subsection) using an intraperitoneal pentobarbital injection (80 mg, 0.5 ml of Morbital, Biowet-Puławy). Once the animals were deeply anesthetized, they were transcardially perfused with 300 ml of PBS, pH ∼7.4, followed by 300 ml of 4% formaldehyde in PBS (Avantor). Brains were extracted from the skulls and post-fixed in the same solution for another 24 h. Next, the brains were cut into 50-µm-thick slices using a vibratome (Leica VT1000S; Leica) and underwent the immunohistochemical staining procedure. First, blocking of the nonspecific binding sites along with membrane permeabilization was performed for 1 h at room temperature (10% Normal Donkey Serum, NDS, and 0.3% Triton X-100 diluted in PBS; Jackson ImmunoResearch Europe and Sigma-Aldrich, respectively). Next, slices containing injection sites (the SC) were incubated with a primary antibody against Cre recombinase (murine anti-Cre antibody 1:1,000 with 2% NDS, 0.3% Triton X-100 diluted in PBS; Abcam) for 2 d in 4°C. Slices containing the SNc and VTA (5–6 slices that covered these brain areas in the anteroposterior axis) were incubated with primary antibodies against Cre recombinase and tyrosine hydroxylase (murine anti-Cre antibody 1:1,000 and rabbit anti-TH antibody 1:500, with 2% NDS, 0.3% Triton X-100 diluted in PBS; Abcam and Sigma-Aldrich, respectively) in the same conditions. Afterward, slices were washed three times with PBS for 10 min and incubated with secondary antibodies for the next 24 h in 4°C (donkey anti-mouse antibody with Alexa Fluor 647 1:400 or donkey anti-mouse antibody with Alexa Fluor 647 1:400 and donkey anti-rabbit antibody with Alexa Fluor 488 1:400, with 2% NDS diluted in PBS; Jackson ImmunoResearch Europe). Slices were washed three times with PBS, mounted on glass slides using a DAPI-containing mounting medium (VectaShield, Sigma-Aldrich), covered with coverslips, and investigated with the use of a fluorescent microscope (Axio Imager.M2 equipped with a AxioCam MRm camera; Zeiss).

In vivo electrophysiological experiments

At least 2 weeks after the injections of viral vectors (details above, Brain injection surgeries subsection), animals were deeply anesthetized by intraperitoneal injection of urethane (1.5 g/kg body mass; Sigma-Aldrich) diluted in 0.9% sodium chloride. Once the depth of anesthesia was confirmed (absence of paw pinch, tail pinch, corneal reflexes), the animals were mounted to a stereotaxic frame (SF-1450AP; ASI Instruments) using sharp ear bars (EB-918, 18° tip). Sagittal incision on top of the head was made, the skin and soft tissue were retracted, and then the bregma and lambda points were used to align the head of the animal in the dorsoventral axis. Next, the craniotomies were made to allow the electrode and optical fiber implantations. All exposed brain surfaces were covered with paraffin oil (Sigma-Aldrich) to prevent tissue from drying. Throughout the experiment, core body temperature was held at 37°C by an automatic heating pad (temperature controller TCP-02; WMT), and electrocardiographic recording (sampled at 1 kHz, amplified 100×, and filtered at 300–500 Hz) was performed to monitor the state of the animal (Model 1800 2-Channel Microelectrode AC Amplifier; A-M Systems). In total, recordings from six wild-type Sprague Dawley and four TH-Cre^+/− rats used in these experiments underwent further analysis.

Single-cell recordings in the SNc and VTA were conducted using micropipettes filled with 2% Chicago Sky Blue dye diluted in 0.5 M NaCl with an impedance in range of 20–35 MΩ (measured in vivo). Pipettes were prepared from borosilicate glass capillaries (OD: 1.5 mm, ID: 0.86 mm, with filament; Sutter Instrument) using a horizontal puller (P-97; Sutter Instrument). Electrodes were placed within the SNc/VTA using the following stereotaxic coordinates: −5 to −6 mm caudally, ±0.7 to ±1.5 mm laterally, and −7.8 to −9.1 mm ventrally from the bregma point. To increase recording stability, a hydraulic micromanipulator was used to place the electrode in the desired position (MO-10; Narishige). The signal was amplified and filtered (1,000×, 300–5,000 Hz, respectively) using a BA-03X bridge amplifier (NPI Electronic) and then digitized (40 kHz) with a micro 1401 mkII interface operated by Spike2 software (version 8.11 for Windows; Cambridge Electronic Design). At the end of each experiment, a negative current (−10 μA) was passed through the electrode for 15–20 min to deposit Chicago Sky Blue dye at the recording site for further histological verification (Stimulus Isolator; WMT). Recorded neurons were classified as dopamine-like if they met previously established electrophysiological criteria: a triphasic broad action potential (>1.1 ms measured from the action potential initiation to the minimum of the trough) and a firing rate below 10 Hz (Grace and Bunney, 1980, 1983; Ungless and Grace, 2012). The final criterion for classifying a neuron meeting the above criteria as a DA-like neuron was the histological confirmation of its location in the SNc or VTA based on the Chicago Sky Blue dye deposition. In the subset of experiments where TH-Cre^+/− rats were used, optotagging was additionally performed to ensure that DA-like neurons are indeed dopaminergic. Such optotagging was conducted in the ChrimsonR-expressing dopaminergic neurons using red light (635 nm). For that purpose, light (5 ms pulse trains lasting 1 s at frequencies of 5, 10, and 20 Hz, repeated several times) was delivered into the tissue using an optical fiber (Ø105 µm, NA: 0.22, Thorlabs) connected to a laser source (MRL-III-635L laser with ADR-180A controller; Shanghai Laser & Optics Century). The optical fiber was implanted above the ventral midbrain using the following stereotaxic coordinates: 30° anterior angle, −0.8 mm caudally, ±0.8 mm laterally, −9 mm ventrally from the bregma.

Additionally, throughout the experiment, electrocorticographic recording (ECoG) was conducted (sampled at 1 kHz, amplified 1,000×, and filtered at 1–500 Hz) using a silver wire connected to a screw (0.1–0.2 MΩ measured at 1 kHz in saline) that was placed over the right hemisphere at the border of the primary motor and somatosensory cortices (Model 1800 2-Channel Microelectrode AC Amplifier; A-M Systems). The ECoG was performed to avoid the comparison between the effects of the ipsilateral and contralateral SC stimulation observed in the different states of the brain (i.e., activation and slow-wave activity), as the activity of DA-like neurons is altered by the brain state (Walczak and Błasiak, 2017).

During these recordings, the optogenetic stimulation of either the ipsilateral or contralateral ChR2-expressing SC was performed. Light was delivered into the brain using two optical fibers (Ø105 µm, NA: 0.22, Thorlabs) implanted just above both the SCs (stereotaxic coordinates: ±15° lateral angle, −6.6 to −7 mm caudally, ±2.5 mm laterally, 3.5 mm ventrally from the bregma). To mark the optical fibers’ placement within the tissue, they were covered with a fluorescent dye prior to implantation (DiI; Thermo Fisher Scientific). Optical fibers were connected to a blue light (473 nm) laser source (MBL-III-473 laser with PSU-III-LED controller; CNI Optoelectronics Technology). Before the implantation, the power of the light emitted from the tip of optical fibers was measured by a photodiode power sensor (S121C; Thorlabs) connected to a digital optical power and energy meter (PM100D; Thorlabs). The analog signal provided by the light meter was digitalized by micro 1401 mkII interface and measured in Spike2 software to check the stability of the light source. The light power delivered into the brain did not exceed 20 mW. Custom-made Spike2 GUI and scripts were used to control the parameters of light output. Single 100 ms light pulses repeated every 6 s were used in these experiments to stimulate either of the SCs.

At the end of each experiment, animals were intraperitoneally injected with pentobarbital, transcardially perfused, and brains were extracted, post-fixed, sliced, and inspected under the fluorescent microscope (as described above, Anatomical experiments subsection). Slices containing Chicago Sky Blue depositions, the tips of optical fibers, as well as the eYFP-expressing SC or tdTomato-expressing SNc/VTA were photographed. The images were matched to the corresponding coronal section of the rat brain stereotaxic atlas (Paxinos and Watson, 2007) using CorelDRAW software (Corel Corporation) to verify both the recording locations and optogenetic stimulation sites. Only recordings that were localized within the borders of the SNc or VTA, and only from these brains in which eYFP/tdTomato expression and optical fiber placements were confirmed, were included in the final analysis.

Ex vivo electrophysiological experiments

The experiments were carried out on acute horizontal slices of the ventral midbrain containing the SNc and VTA, at least 3 weeks (23–30 d) after the unilateral injection of AAV2-hSyn-Chronos-GFP into the SC (details above, Brain injection surgeries subsection). In total, 19 slices from five wild-type rats were used in the experiments (10 for ipsilateral and 9 for contralateral recordings).

Prior to tissue extraction, animals were deeply anesthetized in an induction chamber with 1 ml of isoflurane (Baxter). Once deeply anesthetized, animals were subjected to guillotine decapitation (AnimaVivari), and their brains were quickly taken out from the skull in a Petri dish filled with ice-cold oxygenated (95% oxygen, 5% CO₂) preparation artificial cerebrospinal fluid (ACSF), using ice-cold tools. The preparation ACSF was composed of the following (in mM): 92 NaCl, 2.5 KCl, 1.25 NaH₂PO₄, 30 NaHCO₃, 20 HEPES, 5 sodium ascorbate, 3 sodium pyruvate, 2 thiourea, 25 glucose, 10 MgSO₄, and 0.5 CaCl₂ (Sigma-Aldrich). Next, the brains were trimmed, mounted to an ice-cold platform with its dorsal part down and transferred to a vibroslicer chamber (Leica VT1000S; Leica) filled with ice-cold oxygenated preparation ACSF. Following, the brains were cut into 250-μm-thick horizontal slices. The ones containing the SNc and VTA were placed in an incubation chamber filled with recording ACSF heated to 32°C, and these containing the SC were used for histological verification of the injection site (using epifluorescent microscope). The recording ACSF was composed of the following (in mM): 125 NaCl, 3 KCl, 1.2 NaH₂PO₄, 25 NaHCO₃, 5 glucose, 2 CaCl₂, 2 MgCl₂, and 0.01 mg/L phenol red (Sigma-Aldrich). Slices were left to cool down to a room temperature and they were incubated for another 1 h before proceeding.

To acquire electrophysiological data, a two-well MEA2100-System (Multi Channel Systems) using two perfusion systems, the upper one to provide continuous perfusion with the recording ACSF and to apply drugs, and the lower one to apply gentle suction that keeps the slice in close proximity to recordings electrodes, was used. The recording was performed using perforated 8 × 8 multi-electrode arrays (MEA; 60pMEA200/30iR-Ti, Multi Channel Systems) consisting of 60 recording electrodes with a spacing of 200 μm in both directions. Slices were placed above the recording electrodes in either of two recording wells, one with ventral midbrain ipsilateral, and another one, contralateral to the injected SC. Following, slices were sucked down the MEA and left for 60 min to settle before recording initiation. Throughout the whole experiment, the slices were constantly perfused (2 ml/min) with fresh recording ACSF containing an elevated amount of potassium (5 mM KCl; to increase the spontaneous activity of the cells) warmed to 25°C. For online data visualization and collection Multi Channel Experimenter software (Multi Channel Systems) was used. Raw unfiltered signal, sampled at 20 kHz, was stored on a hard drive.

After 30 min of baseline recording, the optogenetic stimulation of ipsilateral or contralateral SC-originating axon terminals was performed. To deliver light into the tissue, optical fibers (Ø200 µm, NA: 0.5; Thorlabs) were placed above the slices in a distance allowing the beam of light to cover the recorded brain region. To avoid photovoltaic effect-mediated signal artifacts, a blue diode (PlexBright LED 465 nm controlled by a LD1 LED driver; Plexon) producing stable light output was used as a light source. Output light stability and power was measured as described above (In vivo electrophysiological experiments subsection). The same light power of 5 mW was used on all the slices. The stimulation protocol consisted of 1-s-long trains of 5 ms blue light pulses flashed at 40 Hz, repeated 80 times every 6 s. The parameters of the light output were controlled with a custom-made Spike2 GUI and script (Cambridge Electronic Design).

Following the optogenetic stimulation protocol, the slices underwent a bath perfusion application of quinpirole (5 µM, 5 ml, 2 ml/min; Sigma-Aldrich), a selective agonist of D₂ dopaminergic receptors. This procedure served as a pharmacological identification of SNc and VTA dopaminergic neurons since they are known to potently express this receptor, as opposed to nondopaminergic neurons in these brain regions (Centonze et al., 2002). Quinpirole was stored as 100× concentrated stocks and was diluted in fresh oxygenated recording ACSF immediately prior the administration. More than 4 min were needed for the drug to reach the MEA wells. Recording was continued for at least 25 min following the drug application.

At the end of each experiment, the slices were photographed for further histological verification and spatial distribution analysis. The images were matched to the corresponding coronal section of the rat brain stereotaxic atlas (Paxinos and Watson, 2007) using CorelDRAW software (Corel Corporation). Only these recordings that were localized within the borders of the SNc or VTA, and only from brains where proper GFP expression in the SC was observed, were further analyzed.

Data analysis

Anatomical data were analyzed using ImageJ software (FIJI, version 1.52s for Windows). Panoramic images of the ventral midbrain from brains successfully injected with anterograde transsynaptic viral vector into the SC (details above, Brain injection surgeries and Anatomical experiments subsections) were inspected using Cell Counter plugin. All monosynaptically innervated SNc and VTA neurons (Cre-positive ones; immunostaining details above, Anatomical experiments subsection) were marked manually on both ipsilateral and contralateral brain sides (in relation the SC injection site). Additionally, neurons that contained both Cre and TH were marked separately. The borders of the SNc and VTA were indicated by the TH immunostaining. The positions of all neurons was extracted and used for further spatial distribution visualization using custom-made MATLAB scripts (version R2018a for Windows; MathWorks) and for subsequent statistical analysis. For bubble density plot visualization (Figs. 1E, 4C, 6E), the surface containing positions of all marked neurons was divided into small square subregions. Then, the number of neurons within each square was counted; for each square a circle was drawn, which size was based on the number of cells counted. Lastly, each circle was repositioned to the center of mass of all neurons located within the corresponding square.

Electrophysiological data from in vivo single-unit recordings were manually inspected and refined in Spike2 software (Cambridge Electronic Design). Electrophysiological raw data from ex vivo MEA recordings were exported to HDF5 files using Multi Channel DataManager (Multi Channel Systems). Following, the files were processed with a custom-made MATLAB script in order to remap the channel order and to convert the file to DAT format. Then, DAT files underwent automatic spike sorting using KiloSort program (default parameters: ops.Th = [10 4], ops.AUCsplit = 0.9, ops.spkTh = −6, ops.lam = 10; Pachitariu et al., 2016) run in MATLAB environment. To enhance the speed of calculations a graphics processing unit was used (NVIDIA GeForce GTX 1050Ti GPU; CUDA 9.0 for Windows). Parallelly, using Multi Channel DataManager, raw data were also exported to CED-64 files (SMRX) suited for Spike2 software. Files were subsequently remapped and bandpass filtered (300–7,500 Hz, Butterworth, fourth order) with a custom-made Spike2 script. To such preprocessed SMRX files, the results of automated post-KiloSort spike sorting were transferred using another custom-made MATLAB script. Finally, these files were manually inspected using Spike2 software for further unit refinement (e.g., refining, splitting, merging) with the aid of autocorrelation, cross-correlation, principal component analysis, and visual comparison of the separated units and raw signal. Only the signal from recording electrodes found to be localized within the SNc or VTA was analyzed.

In the subset of in vivo experiments, where TH-Cre^+/− rats were used, spike fidelity was used as a measure of neuron being dopaminergic. It was calculated as a proportion of action potentials evoked by red light pulses (details above, in vivo electrophysiological experiments subsection). Action potential was deemed light-evoked when generated within 15 ms of the red light pulse initiation (detected by a custom-made Spike2 script). For each light pulse frequency (5, 10, and 20 Hz) spike fidelity from five 1-s-long trains was averaged. Neuron was deemed dopaminergic when its overall spike fidelity exceeded 80%. To extract spike shapes evoked by optotagging a custom-made Spike2 script was used and the extracted waveforms underwent PCA and correlation analyses using a custom-written MATLAB script.

In the ex vivo experiments a neuron was considered dopaminergic when, besides being localized within the SNc or VTA, it exhibited inhibitory response to a D₂ receptor agonist, quinpirole. Neuron was classified as inhibited when its activity (calculated in 1 min bins), following the drug application, was reduced by at least three standard deviations of the baseline firing for at least 180 consecutive seconds (3 bins). This classification was done using custom-made MATLAB script; however, in some ambiguous cases, manual reclassification was performed.

Finally, to detect the potential effects of optogenetic stimulations, custom-made Spike2 script was used to calculate average peristimulus spike density function (SDF; Gaussian kernel, width = 100 ms) for each unit and then to save them to TXT files. These files, with the help of customly crafted MATLAB scripts, were used to prepare the heatmaps, mean, and median activity plots, as well as to detect the effects caused by optogenetic stimulation. In case of in vivo experiments, an automated detection of either excitation or inhibition was conducted. The neuronal activity was considered to be altered (either excited or inhibited) by the optogenetic stimulation when SDF crossed the threshold of one standard deviation above (or below) mean value of SDF in the baseline, and additionally, the length of such change had to be longer than mean length (plus one standard deviation) of threshold-crossing episodes in the baseline. Threshold crossings appearing later than 60 ms from the onset of the optogenetic stimulation were not considered as effects. In case of ex vivo experiments, where SC-originating axon terminals were optogenetically stimulated within the SNc or VTA, the neuron was considered as excited (or inhibited) when its activity during the stimulation period (1 s) was higher (or lower) than the average activity in baseline ± one standard deviation. Some results are presented as normalized firing rate, which was calculated by dividing all the bins by the mean value of bins from the baseline, so the mean baseline is equal to one.

Experimental design and statistical analysis

Most statistical analyses were performed in GraphPad Prism software (version 6.0 for Windows; GraphPad Software). The distribution of the data was tested using Kolmogorov–Smirnov and Shapiro–Wilk tests. If the data were normally distributed Student's t test or ANOVA tests were performed (paired, if applicable). Otherwise, for comparison between two groups, Mann–Whitney test (unpaired) was used, and for comparison between more than two groups, Kruskal–Wallis test (unpaired) or Friedman test (paired) was used. For checking whether the data differs from the theoretical mean (or median), a one-sample t test or one-sample Wilcoxon signed rank test (depending on the distribution of the data) was performed. When two factors were considered, a two-way ANOVA was conducted. Multigroup comparison tests were followed by Sidak's or Holm–Sidak's post hoc test. When more than one dependent variable was tested, a MANOVA test was performed using SPSS Statistica software (version 13 for Windows; Tibco Software). To test differences in proportion, a Fisher's exact test or χ² test was conducted using RStudio software (version 1.2 for Windows; RStudio). Results are presented as mean ± SEM, unless otherwise stated. In all tests, compared values were deemed significant at p < 0.05. The complete results of the statistical analyses are reported in the Results section of the manuscript.

Code/software accessibility

The custom-made MATLAB and Spike2 codes used for analyses are available upon request from the corresponding authors.

Results

Anatomical lateralization of the innervation from the SC to the SNc and VTA

To describe the innervation descending from SC to the ventral midbrain, anterograde transsynaptic tract tracing experiments were performed. The SNc and VTA of animals which received unilateral injection of AAV1-Syn-Cre-hGH into the SC underwent the anti-Cre and anti-TH immunostaining and were further inspected and analyzed (Fig. 1A; details in Materials and Methods: Brain injection surgeries, Anatomical experiments, and Data analysis subsections). Since aforementioned viral vector is transported anterogradely through axon and passed through one synapse, the Cre expression in the SNc and VTA indicated monosynaptic innervation from the SC (Zingg et al., 2017; Huang et al., 2019). The summary of the results is shown in Figure 1B. Notably, more than half of monosynaptically innervated cells were dopaminergic, as indicated by the colocalization of Cre recombinase and TH immunoreactivity (52.8%; Fig. 1C). An example of the injection site in the SC, along with an overlay of all injection sites, is presented in Figure 1D (top and bottom panels, respectively).

Figure 1.

SNc and VTA are monosynaptically innervated predominantly by the SC on the ipsilateral side of the brain. A, Scheme of the experiment. SC was unilaterally injected with transsynaptic anterograde viral vector, and after 3 weeks the ventral midbrain in both hemispheres was inspected in search of monosynaptically innervated cells. B, Average cell count of Cre-positive cells within either SNc (purple) or VTA (green) on either ipsilateral or contralateral side of the brain in relation to the SC injection. C, Fraction of TH-positive cells across all monosynaptically innervated cells (Cre). D, Top panel, Exemplary brain image showing the SC injection site of the anterograde transsynaptic viral vector (AAV1-hSyn-Cre-hGH) containing gene for Cre recombinase, which was visualized by immunostaining (Alexa Fluor 647; yellow pseudocolor). Bottom panel, Reconstruction of all injection sites from all rats (n = 10); darker color indicates the overlap of injections across different rats. E, Top panel, Exemplary image showing anterogradely labeled neurons (Cre; yellow) in the VTA and SNc, as indicated by the TH immunostaining (green), along with the inset showing exemplary cells at higher magnification. Middle panel, Density plot showing all VTA and SNc cells monosynaptically innervated by the right SC. Bottom panel, Bubble density scatter plot with reconstructed positions of all anterogradely filled VTA and SNc neurons observed in all rats. Black circles depict neurons containing only Cre recombinase (non-DA) and orange circles depict neurons colocalizing Cre and TH (DA). The size of the circle indicates the number of cells localized within particular spot. F, Distribution of Cre-positive cells within the SNc (purple) and VTA (green) in anteroposterior axis on either contralateral (left panel) or ipsilateral (right panel) brain side in relation to the injection site. G, Distribution of Cre-positive cells within the SNc (purple) and VTA (green) in mediolateral axis. Dotted line indicates the midline. H, Distribution of all Cre-positive neurons (Cre; black), DA neurons (Cre + TH; orange), and fraction of DA neurons (TH [%]; pink) across anteroposterior axis in the ventral midbrain on either contralateral (left panel) or ipsilateral (right panel) brain side in relation to the injection site. I, Distribution of all Cre-positive neurons (Cre; black), DA neurons (Cre + TH; orange), and fraction of DA neurons (TH [%]; pink) across mediolateral axis. Dotted line indicates the midline. * for p < 0.05, ** for p < 0.01, **** for p < 0.0001, ns, nonsignificant.

The majority of monosynaptically innervated cells were located in the ipsilateral ventral midbrain, particularly within the SNc. This is illustrated by an example TH-immunostained SNc and VTA image containing Cre-positive cells (Fig. 1E, top panel), as well as a density heatmap of Cre-positive cells (middle panel) and a bubble density plot (bottom panel), which also provide information about Cre and TH colocalization. The distribution of monosynaptically labeled cells in the SNc and VTA in both anteroposterior and mediolateral axes is depicted in Figure 1F,G, respectively. A clear difference was observed in the number of labeled cells between ipsilateral and contralateral hemispheres, with the highest number of Cre-positive neurons found within the borders of the ipsilateral SNc (Fig. 1B; two-way ANOVA, repeated measures by both factors; total ipsilateral and contralateral cell counts: 68.1 ± 14.2 and 20.0 ± 3.6, respectively; laterality: F_(1,9)= 19.59; p = 0.0017; brain region: F_(1,9)= 16.87; p = 0.0026; laterality × brain region interaction: F_(1,9)= 27.58, p = 0.0005; followed by Holm–Sidak's post hoc test—ipsilateral SNc vs contralateral SNc: 49.5 ± 10.4 vs 10.6 ± 2.4, t = 9.73, p < 0.0001; ipsilateral VTA vs contralateral VTA: 18.6 ± 3.9 vs 9.3 ± 1.5, t = 2.31, p < 0.05; ipsilateral SNc vs ipsilateral VTA: t = 7.75, p < 0.0001; contralateral SNc vs contralateral VTA: t = 0.32, p = 0.76). Additionally, a mediolateral gradient in the number of monosynaptically innervated neurons by the lateral SC in the ventral midbrain was observed only in the ipsilateral hemisphere, with significantly more neurons innervated in the SNc, particularly in its lateral regions, as compared with the VTA (Fig. 2E,G).

Figure 2.

The impact of in vivo stimulation of the SC on the activity of SNc and VTA neurons. A, Scheme of the experiment. The SC was bilaterally injected with an AAV containing genes for ChR2 and eYFP (green), and in case of TH-Cre rats, additional injection of an AAV containing Cre-dependent genes for ChrimsonR and tdTomato (red) into the SNc and VTA was done. Afterward, the single-unit activity in the SNc and VTA was recorded while either ipsilateral or contralateral SC was optogenetically stimulated, and in case of TH-Cre rats, optotagging was additionally performed. B, Localization of all recorded neurons with reactions to either ipsilateral or contralateral SC stimulation marked separately (left and right panel, respectively). Neuronal population (DA SNc, DA VTA, or non-DA VTA) is coded with a border color of individual circle (purple, green, or black, respectively). Response type is color-coded with the filling of an individual circle (red, excitation; gray, no effect; blue, inhibition). C, Peristimulus heatmaps showing the reactions of all recorded SNc and VTA neurons to optogenetic stimulation of the ipsilateral (left panels) or contralateral (right panels) SC. Responses are sorted according to the amplitude of the response during the stimulation. The activity of individual neurons is presented in rows. Stimulation time is indicated by dotted lines (473 nm, 100 ms, <20 mW). D, Pie charts showing the proportions of DA SNc (top panels), DA VTA (middle panels), and non-DA VTA (bottom panels) neurons that exhibited a particular response type (excitation, no effect, inhibition) to optogenetic stimulation of either ipsilateral (left panels) or contralateral (right panels) SC. E, Mean firing rate (±SEM) of DA SNc (top panel), DA VTA (middle panel), and non-DA VTA (bottom panel) neurons recorded during baseline and optogenetic stimulation of ipsilateral or contralateral SC. F, Peristimulus median firing rate (normalized to baseline; first and third quartile marked with gray color) of DA SNc (top panels), DA VTA (middle panels), and non-DA VTA (bottom panels) neurons elicited by either ipsilateral (left panels) or contralateral (right panels) SC stimulation. G, Peristimulus median firing rate (normalized to baseline; first to third quartiles marked with semi-transparent red and blue colors) of DA SNc (top panels), DA VTA (middle panels) and non-DA VTA (bottom panels) neurons excited (red) and inhibited (blue) by either ipsilateral (left panels) or contralateral (right panels) SC stimulation. H, Left panel, Proportions of lateral and medial DA SNc neurons that exhibited a particular response type (excitation, no effect, inhibition) to optogenetic stimulation of either ipsilateral or contralateral SC. Right panel, Table showing percentages of neurons excited by ipsilateral or contralateral SC stimulation in the lateral and medial SNc DA neurons. I, Proportions of DA SNc (left panel), DA VTA (middle panel), and non-DA VTA (right panel) neurons exhibiting a given type of response to both ipsilateral (top line) and contralateral (bottom line) SC stimulation. The responses of individual neurons are shown in vertical columns. The neurons were sorted based on the type of response to ipsilateral SC stimulation. J, Proportions of neurons exhibiting lateralized excitatory responses to the ipsilateral (ipsi, excitation; contra, inhibition/no effect; top bars) and contralateral (contra, excitation; ipsi, inhibition/no effect; bottom bars) SC stimulation. * for p < 0.05, ** for p < 0.01, *** for p < 0.001, ns, nonsignificant.

No differences were observed in the anteroposterior distribution of cells in both the SNc and VTA on the contralateral side of the brain (Fig. 1F, left panel; two-way ANOVA, repeated measures by both factors; AP: F_(2,18)= 0.55, p = 0.58; brain region: F_(1,9)= 0.17, p = 0.69; AP × brain region interaction: F_(2,18)= 2.84, p = 0.0844). On the ipsilateral side, however, a gradient was observed, with the number of innervated cells increasing toward the anterior parts of the VTA. In contrast, cells in the ipsilateral SNc were evenly distributed along anteroposterior axis (Fig. 1F, right panel; two-way ANOVA, repeated measures by both factors; AP: F_(2,18)= 2.0, p = 0.16; brain region: F_(1,9)= 22.58, p = 0.001; AP × brain region interaction: F_(2,18)= 8.97, p = 0.002; followed by Holm–Sidak's post hoc test—VTA −5.2 mm vs VTA −5.6 mm, t = 3.11, p < 0.05; VTA −5.2 vs −6.0 mm, t = 4.29, p < 0.01; other comparisons: ns).

The distribution of all innervated cells (Cre) along with colocalized ones (Cre + TH) across the ventral midbrain in either anteroposterior or mediolateral axes is depicted in Figure 2H,I, respectively.

Together, these results show that the lateral SC innervates the ventral midbrain with clear prevalence toward ipsilateral side of the brain. Moreover, it seems that the ipsilateral SNc constitutes the main target of this innervation. This is supported by the increasing gradient of Cre-positive cells in the mediolateral axis spanning from the contralateral midbrain, through the ipsilateral VTA to the SNc. Finally, more than half of the cells targeted by the SC are dopaminergic.

The SC stimulation activates neurons in the SNc and VTA in vivo

To describe the physiology of the SC to the SNc and VTA circuit in the preserved whole brain preparation, the in vivo single-unit electrophysiological recordings in the SNc and VTA combined with optogenetic stimulation of either ipsilateral or contralateral SC were conducted (details in Materials and Methods: Brain injection surgeries, In vivo electrophysiological experiments, and Data analysis subsections). The recordings were performed on either wild-type rats (scheme of experiments in Fig. 2A, top panel) or TH-Cre^+/− rats, in which case optotagging was also performed (bottom panel). The activity of 107 neurons from either SNc or VTA was recorded in 14 rats. Among these, 81 neurons (64 DA-like and 17 non-DA-like) underwent both ipsilateral and contralateral SC stimulation. The spontaneous firing rate of all recorded DA-like neurons (4.0 ± 0.19 Hz; n = 84), as well as a subset of DA-like neurons that underwent stimulation of both SCs (3.81 ± 0.2 Hz; n = 64), was comparable with that described in the literature (Ungless and Grace, 2012; Marinelli and McCutcheon, 2014). In case of non-DA-like neurons, spontaneous firing rate displayed was 11.43 ± 1.79 Hz (n = 23) and 12.52 ± 2.21 Hz (n = 17), respectively. The following analysis was conducted on neurons which received both ipsilateral and contralateral SC stimulations to gain statistical power through paired statistical testing.

The optogenetic stimulation of the SC was delivered repeatedly every 6 s (at least 11 times, stimulation count ± SD: 77.6 ± 37.1), and in case of recorded cells that underwent bilateral SC stimulations, the same number of stimulations was applied to either side of the brain. The locations of all recorded neurons, color-coded by their response to either ipsilateral or contralateral SC stimulation, are shown on single coronal planes in Figure 2B. The reactions themselves are depicted on the heatmaps containing the peristimulus normalized activity of recorded neurons (Fig. 2C). Both stimulations elicited mixed reactions (i.e., excitations, inhibitions, or no response) in either DA or non-DA cells with no clear differences in the distribution of response types between the ipsilateral and contralateral SC stimulation (Fig. 2D; DA_SNc: n = 33, χ²= 4.54, p = 0.1; DA_VTA: n = 31, χ²= 1.06, p = 0.59; nonDA_VTA: n = 17, χ²= 1.06, p = 0.91; χ² tests). There was no significant difference in the distribution of reactions of DA-like neurons between the SNc and the VTA (irrespective of the side of stimulation) despite the trend toward more inhibitory responses in the VTA (χ²= 3.2, p = 0.2, χ² test). Despite not reaching statistical significance, in case of DA-like neurons, especially in the SNc, there was a tendency toward prevalence of excitations upon the ipsilateral (SNc: 21/33, 64%; VTA: 18/31, 58%), as compared with contralateral (SNc: 13/33, 39%; VTA: 14/31, 45%) stimulations (Fig. 2C,D).

This trend was reflected in changes in the firing rate upon the stimulation (Fig. 2E,F). At the level of the whole population, DA neurons in the VTA altered their activity during the stimulation of the ipsilateral, but not the contralateral, SC (Fig. 2F, middle panels; one-sample Wilcoxon signed rank tests, theoretical median: 100%; ipsilateral—median = 136.79% of baseline activity, first to third quartile: 73.25–204.9%, n = 31, p = 0.0177; contralateral—median = 116.86% of baseline activity, first to third quartile: 69.11–173.95%, n = 31, p = 0.0727). For DA neurons in the SNc, the change during ipsilateral SC stimulation was significantly more pronounced compared with the contralateral stimulation, although both reached significance (Fig. 2F, top panels; ipsilateral—median = 131.8% of baseline activity, first to third quartile: 88.35–183.39%, n = 33, p = 0.0009; contralateral—median = 112% of baseline activity, first to third quartile: 89.17–140.98%, n = 33, p = 0.0484). In contrast, non-DA cells in the VTA did not change their activity upon either ipsilateral or contralateral SC stimulation (Fig. 2F, bottom panels; ipsilateral—median = 99.92% of baseline activity, first to third quartile: 95.53–141.07%, n = 17, p = 0.55; contralateral—median = 113.54% of baseline activity, first to third quartile: 94–143.74%, n = 17, p = 0.0797). Overall firing rate of SNc DA neurons changed only when the ipsilateral SC was stimulated (Fig. 2E, top panel; baseline before ipsilateral stimulation: 3.57 ± 0.28 Hz, baseline before contralateral stimulation: 3.61 ± 0.28 Hz, during ipsilateral stimulation: 5.06 ± 0.4 Hz, during contralateral stimulation: 4.57 ± 0.45 Hz; repeated-measures one-way ANOVA, n = 33, F_(1.87,59.92)= 9.15, p = 0.0005; followed by Sidak's post hoc test: baseline before ipsilateral stimulation vs ipsilateral stimulation: t = 3.69, p < 0.01, other comparisons: ns). Even though only the ipsilateral SC stimulation excited SNc neurons, the effect was small, as no difference between the activity during ipsilateral and contralateral stimulation was detected. Similarly, the activity of VTA DA neurons was elevated only during the ipsilateral SC stimulation, but no differences were detected with regard to the laterality of stimulation (Fig. 2E, middle panel; baseline before ipsilateral stimulation: 4.02 ± 0.31 Hz, baseline before contralateral stimulation: 4.08 ± 0.29 Hz, during ipsilateral stimulation: 5.80 ± 0.71 Hz, during contralateral stimulation: 5.42 ± 0.67 Hz; repeated-measures one-way ANOVA, n = 31, F_(1.74,52.3)= 7.37, p = 0.0023; followed by Sidak's post hoc test: baseline before ipsilateral stimulation vs ipsilateral stimulation: t = 3.11, p < 0.05, other comparisons: ns). Overall firing rate of non-DA neurons of the VTA was not changed upon either ipsilateral or contralateral stimulation (Fig. 2E, bottom panel; baseline before ipsilateral stimulation: 12.18 ± 2.03 Hz, baseline before contralateral stimulation: 12.85 ± 2.47 Hz, during ipsilateral stimulation: 14.12 ± 2.88 Hz, during contralateral stimulation: 15.23 ± 3.26 Hz; Friedman test, n = 17, Friedman statistic = 2.25, p = 0.52). Moreover, the responses of VTA non-DA neurons were weaker than that of DA neurons both in case of excitation (DA—median = 182.68% of baseline activity, first to third quartile: 149.97–232.1%, non-DA—median = 139.37% of baseline activity, first to third quartile: 126.45–176.41%; n_DA= 66, n_non-DA= 13, U = 242, p = 0.0122, Mann–Whitney test) and inhibition (DA—median = 48.79% of baseline activity, first to third quartile: 32.81–64.41%, non-DA—median = 82.53% of baseline activity, first to third quartile: 73.45–90.5%; n_DA= 25, n_non-DA= 9, U = 32, p = 0.0002, Mann–Whitney test); the individual peristimulus activity traces for excited and inhibited neurons in all neuronal subgroups can be seen in Figure 2G. Given the tendency toward more excitatory responses in the SNc to ipsilateral SC stimulation (Fig. 2D, top panel) and the clear lateromedial gradient of SNc innervation by the lateral SC (Fig. 1E,G,I), we decided to investigate this further. Indeed, when the lateral SNc (neurons with a laterality ≥ 1.45 mm) was analyzed separately, we observed a higher prevalence of excitatory responses on the ipsilateral side compared with the contralateral side; no such effect was observed in the medial SNc (neurons with a laterality <1.45 mm; Fig. 2H; SNc lateral—ipsilateral vs contralateral: χ²= 7.14, p = 0.0281; SNc medial—ipsilateral vs contralateral: χ²= 0.54, p = 0.765; χ² tests). Furthermore, more excitatory responses were observed in the lateral SNc compared with the medial SNc upon ipsilateral but not contralateral SC stimulation (Fig. 2H; SNc ipsilateral—lateral vs medial: χ²= 6.21, p = 0.0449; SNc contralateral—lateral vs medial: χ²= 0.64, p = 0.7244). Importantly, this lateral part of the SNc is the part of the ventral midbrain where we observed the most dense projection from the lateral SC (Fig. 1G,I). We also examined the responses of individual neurons to both ipsilateral and contralateral stimulation (Fig. 2I). We observed a significant proportion of DA-like cells in the SNc which exhibited lateralized excitatory reactions to ipsilateral stimulation, i.e., cells which responded with excitation to ipsilateral SC stimulation while being nonresponsive or inhibited by the contralateral SC stimulation (Fig. 2J, left panel; p = 0.0163, Fisher's exact test); no such pattern was observed in VTA DA-like or non-DA-like neurons (Fig. 2J, middle and right panels; VTA_DA: p = 0.3354; VTA_non-DA: p = 1, Fisher's exact tests). Additionally, we ensured that the excited and inhibited neurons were not concentrated in a small subset of animals but were evenly distributed across all recorded subjects (average proportion of cells per rat ± SD—excited by the ipsilateral SC stimulation: 62.78 ± 24.29%; inhibited by ipsilateral SC stimulation: 19.86 ± 19.05%; excited by the contralateral SC stimulation: 46.24 ± 23.59%; inhibited by the contralateral SC stimulation: 24.79 ± 16.09%).

The results presented so far primarily focus on the types of neuronal responses (excitation, inhibition, no-response) and their lateralization (elicited by ipsilateral and/or contralateral SC stimulation) within the entire population of DA or non-DA neurons in the VTA or SNc. Subsequent analysis of response parameters, based on automated statistical effect detection (used to classify neurons as excited, inhibited, or nonresponsive—Fig. 2B,D,E,H,I,J; details in Materials and Methods: Data analysis subsection), did not yield significant findings in the laterality domain. No differences were observed between the ipsilateral and contralateral SC stimulation in terms of firing rate changes, latency to minimum or maximum amplitude of inhibitory and excitatory responses, or the duration of these responses (statistical details in Table 1).

View this table:

Table 1.

Effects of optogenetic stimulation of either ipsilateral or contralateral SC on the response parameters of SNc and VTA neurons

Overall, 23 out of 64 DA-like neurons were recorded from TH-Cre^+/− rats, thus they were subjected to optotagging to ensure their dopaminergic identity. Vast majority of these neurons reliably followed the light pulses (17/23, 73.9%; Fig. 3A,B) as indicated by overall light-evoked spike fidelity exceeding 80% (Fig. 3C, left panel). The distribution of spike fidelities for all light pulse frequencies used for optotagging is depicted in Figure 3C (middle and right panels). The latencies of evoked spikes were relatively low, and they differed between pulse frequencies used (5 Hz: median = 2.7 ms, first to third quartile: 1.9–3.2 mss, 10 Hz: median = 3 ms, first to third quartile: 2.4–3.5 ms, 20 Hz: median = 3.6 ms, first to third quartile: 2.7–4 ms; Friedman test, Friedman statistic = 34, p < 0.0001).

Figure 3.

The results of optotagging of DA neurons in the in vivo experiments. A, Pie chart showing the proportion of DA-like neurons recorded in wild type (dark gray) and TH-Cre (black) rats. Purple, as opposed to teal, indicates neurons that responded to optotagging. B, An example of a raw signal showing the response to light pulses of an optotagged neuron. C, Left panel, Binned count of averaged spike fidelity with bars indicating neurons considered responsive in purple (at least 80%) and unresponsive in teal. Middle panel, Median (first to third quartile indicated by whiskers) spike fidelity in response to red light pulse trains (5, 10, or 20 Hz) in optotagged neurons. Right panel, Binned neuron count of spike fidelity for each stimulation frequency (5, 10, 20 Hz) demonstrated as heatmap. D, The representation of spontaneous (gray) and light-evoked (purple) spike waveforms of optotagged DA neurons in the space defined by the first three principal components. E, Mean Euclidean distance in the first three principal components space of spontaneous spike waveforms to: corresponding light-evoked waveforms (purple box) and to all other spontaneous waveforms (gray box). Light gray lines represent individual waveforms. F, Spontaneous (gray) and light-evoked (purple) spike waveforms of individual, optotagged units. Numbers next to each unit show the Euclidean distance between baseline and light-evoked spikes in the first three principal components space as well as the coefficient of determination (R²) between baseline and evoked waveforms. G, The distribution of R² values shown in panel F. H, The proportions of response types to the stimulation of ipsilateral (left) and contralateral (right) SC across all subgroups of recorded DA-like neurons. The black and dark gray colors indicate the genotypes, TH-Cre and WT, respectively; the purple and teal colors distinguish between light-responsive (i.e., optotagged) an unresponsive neurons, respectively; the red, light gray, and blue colors denote the types of responses to the SC stimulation, namely, excitation, no effect, and inhibition, respectively. **** for p < 0.0001.

Although, it can be safely assumed, thanks to the high resistance of the microelectrodes used, that all recordings were single unit and the stimulation artifacts were relatively small and easily distinguishable from actual spikes, the analysis of evoked spike shapes was performed. Principal component analysis conducted on optotagged neurons revealed high similarity of light-evoked spike waveforms to the baseline, spontaneous spike waveforms (Fig. 3D). Indeed, both groups' (i.e., waveforms of light-evoked and spontaneous spikes) distribution did not differ significantly in the first three components space (which accounted for 87.5% of variance explained; Pillai's trace = 0.05, F_(3,30)= 0.58, p = 0.6305, MANOVA). Moreover, the distance in PC1–3 space between spontaneous and corresponding light-evoked spike waveforms was smaller than that of spontaneous spike waveforms to all other spontaneous spike waveforms (evoked: 1.19 ± 0.13, spontaneous: 2.22 ± 0.15, p < 0.0001, t = 7.82, df = 16, paired t test; Fig. 3E). Furthermore, the waveforms of spontaneous spikes exhibited a strong correlation with their light-evoked counterparts (median R²= 0.97, first to third quartile: 0.94–0.98), as illustrated by individual spike shapes shown in Figure 3F; the distribution of R² values is depicted in Figure 3G. Since not responding to optogenetic stimulation did not exclude the possibility that the neuron is still TH positive, all 23 neurons were taken into analysis along with 41 DA-like neurons from wild-type animals. Importantly, the proportions of response types to the SC stimulation did not differ between optotagged neurons and the remaining DA-like neurons both in case of ipsilateral and contralateral stimulations (ipsi: p = 0.7272, contra: p = 0.3483, Fisher's exact tests; Fig. 3H). Given that the neurons in either of these groups come predominantly from one genotype (TH-Cre or wild type), we checked if there was a difference in response profile between the genotypes and we also observed none (ipsi: p = 0.4425, contra: 0.9462, Fisher's exact tests). Moreover, no difference in baseline firing rate between the genotypes was observed (TH-Cre: 3.31 ± 0.39 Hz, WT: 4.1 ± 0.23 Hz, p = 0.066, t = 1.872, df = 62, unpaired t test).

Overall, these data suggest that the ipsilateral SC activation may be more effective at eliciting excitations in midbrain dopaminergic neurons than the contralateral SC stimulation, particularly in the lateral SNc. Importantly, this finding aligns with our anatomical observations. Notably, these experiments were conducted in in vivo conditions, where the entire brain circuit is preserved, thus preventing us from isolating the direct effects of SC to ventral midbrain circuit manipulation.

Stimulation of SC terminals within ventral midbrain ex vivo excites the ipsilaterally located neurons

To describe the physiology of the direct SC to SNc and VTA connection, the ex vivo MEA electrophysiological recordings in the SNc and VTA slices combined with optogenetic stimulation of terminals descending from either the ipsilateral or contralateral SC were conducted (scheme of the experiment in Fig. 4A; details in the Materials and Methods: Brain injection surgeries, Ex vivo electrophysiological experiments, and Data analysis subsections).

Figure 4.

Pharmacological identification of DA neurons in the ex vivo experiments. A, Scheme of the experiment. SC was unilaterally injected with an AAV carrying genes for Chronos and GFP and after at least 3 weeks ex vivo MEA recordings combined with optogenetic stimulation of axon terminals descending from the SC were performed. Simultaneously, ipsilateral and contralateral ventral midbrain slices were recorded on separate MEAs; thus either ipsilateral or contralateral SC-originating terminals were stimulated. At the end of each experiment, quinpirole bath application was performed to identify putative DA and non-DA neurons. B, Heatmap of individual neurons’ firing rates (normalized to baseline; 1 min binned) before and after the application of quinpirole. Black bar represents the time of drug application and dotted line represents the time when the drug starts reaching the slice. Proportion of responsive (inhibited; putative DA neurons) and unresponsive (putative non-DA neurons) neurons is visible on the left side. C, The spatial distribution of neurons inhibited (blue; putative DA) and non-inhibited (gray; putative non-DA) by quinpirole application. For convenience, all neurons were depicted in the same hemisphere. In the bubble density scatter plot, the size of each circle corresponds to the number of cells in particular spot. Panel on the left depicts the distribution of the cells in the anteroposterior axis and panel on top represents the distribution of cells in the mediolateral axis. D, Proportion of putative DA and non-DA neurons recorded within the VTA (left panel) and SNc (right panel). E, The distribution of minimum firing rate change in the neurons inhibited by quinpirole bath application. F, The mean baseline firing rate (±SEM) of putative DA and non-DA neurons. G, H, The median firing rates of putative DA neurons and non-DA neurons, respectively (normalized to baseline; first to third quartile range indicated by gray area), before and after the application of quinpirole (black bar). The drug starts reaching the slice at time = 0 (dotted line). **** for p < 0.0001.

Since there are no electrophysiological criteria allowing to identify DA neurons during ex vivo extracellular recordings, we classified the neurons as DA-like based on their sensitivity to D₂ receptor activation. Out of 446 recorded neurons, 189 (42.4%) were inhibited by the bath application of a potent D₂ receptor agonist, quinpirole (details in the Materials and Methods: Data analysis subsection), and thus they were treated as DA-like in the following analysis. The activity of both DA-like and non-DA like neurons upon the application of quinpirole is depicted in the heatmaps in Figure 4B and their distribution map is shown in Figure 4C. The spatial distribution of cells that were inhibited by quinpirole was not uniform [Pillai's trace = 0.015, F_(3,42)= 3.42, p = 0.03352, MANOVA (AP and ML axes)]. This difference was pronounced only in the ML axis (DA/non-DA × 0.2 mm ML bins: p = 0.00050, χ²= 29.9, chi-squared test), with non-DA neurons showing up more frequently medially, but not in the AP axis (DA/non-DA × 0.2 mm AP bins: p = 0.05797, χ²= 15.8, chi-squared test). Nevertheless, no difference in proportions of DA and non-DA neurons between VTA and SNc was observed (odds = 1.42, p = 0.1383, Fisher's exact test; Fig. 4D). The vast majority of quinpirole-inhibited cells were completely silenced by the drug application (Fig. 4E). The spontaneous activity of DA cells was clearly lower than that of non-DA cells (DA: median = 1.41 Hz, first to third quartile: 0.8–3.22 Hz; non-DA: median = 3.71, first to third quartile: 1.24–6.85 Hz; n_DA= 189, n_non-DA= 257, U = 17,174, p < 0.0001, Mann–Whitney test; Fig. 4F). The normalized median (±first and third quartiles) firing rate for both populations of cells is depicted in Figure 4G,H.

Out of 446 neurons, 434 neurons were analyzed to detect the potential effect of the optogenetic stimulation of SC axonal terminals. The activity of all recorded neurons divided into groups according to the laterality of stimulation, brain region, and neurons being dopaminergic is depicted in Figure 5A. The stimulation of ipsilateral SC-originating axon terminals evoked excitations in DA neurons of both the SNc and VTA (SNc: 7/26, 26.9%; VTA: 16/85, 18.8%; Fig. 5B). In contrast, stimulation of contralateral SC terminals failed to excite DA neurons of the SNc and VTA (SNc: 1/24, 4.2%; VTA: 1/54, 1.9%; Fig. 5B). The distribution of response types differed between the stimulation of ipsilateral and contralateral SC-originating terminals (SNc: p = 0.05045; VTA: p = 0.002617; Fisher's exact tests; Fig. 5B). Similar difference was observed in case of non-DA neurons within the SNc (ipsilateral stimulation: 4/22, 18.2%; contralateral stimulation: 0/27, 0%; p = 0.03452; Fisher's exact test; Fig. 5B). On the other hand, no disproportion of response types between ipsilateral and contralateral SC terminals’ stimulation was observed in case of non-DA VTA neurons (ipsilateral stimulation: 22/131, 16.8%; contralateral stimulation: 7/65, 10.8%; p = 0.294; Fisher's exact test; Fig. 5B). Additionally, only in case of ipsilateral SC terminals' stimulation in the VTA, five inhibitions were observed which were pooled with the unresponsive cells for the purpose of analysis.

Figure 5.

The impact of ex vivo stimulation of SC-originating axon terminals on the activity of the SNc and VTA neurons. A, Heatmaps showing the peristimulus activity of all recorded DA and non-DA neurons of the SNc and VTA (19 slices from 5 animals) during optogenetic stimulation of axon terminals originating from the ipsilateral (left panels) or contralateral (right panels) SC. The firing rate of each neuron was normalized to the mean value observed during baseline (1 s before the stimulus). The activity of individual neurons is depicted in rows, arranged in ascending order based on the average value of the normalized firing frequency observed during 1 s of optogenetic stimulation. Stimulation time is indicated by dotted lines (465 nm, 5 ms at 40 Hz over 1 s, 5 mW). B, Pie charts depicting the proportions of neurons in the SNc and VTA (DA and non-DA) showing a specific type of response (excitation, no effect, inhibition) to optogenetic stimulation of SC axon terminals descending from the ipsilateral (left panels) or contralateral (right panels) side of the brain. C, Mean change in firing rate (±SEM) of recorded SNc and VTA neurons (DA and non-DA) upon the stimulation of either ipsilateral or contralateral SC-originating axon terminals. D, Peristimulus mean change in firing rate (±SEM) of all recorded SNc and VTA neurons (DA and non-DA) elicited by stimulation of axon terminals originating from either ipsilateral (left panels) or contralateral (right panels) SC. E, Mean change in firing rate (±SEM) of SNc and VTA neurons (either DA or non-DA) that were excited upon the stimulation of axon terminals originating from the ipsilateral SC. F, Peristimulus mean change in firing rate (±SEM) of SNc and VTA neurons (either DA and non-DA) that were excited by the stimulation of the axon terminals descending from the ipsilateral SC. * for p < 0.05, ** for p < 0.01, **** for p < 0.0001, # for p = 0.05045, ns, nonsignificant.

The disproportion in excitations evoked by the stimulation of ipsilateral and contralateral SC terminals is also reflected by the change in activity of neurons (Fig. 5C,D). At the population level both DA and non-DA neurons of the SNc and VTA changed their firing rate only upon ipsilateral stimulation (Fig. 5D; one-sample Wilcoxon signed rank tests, theoretical median: 0 Hz; SNc—DA: n = 26, p = 0.0032, non-DA: n = 22, p = 0.0019; VTA—DA: n = 85, p < 0.0001; non-DA: n = 131, p = 0.0407). No changes were observed after the stimulation of contralateral SC-originating terminals in either of the groups (Fig. 5D; one-sample Wilcoxon signed rank tests, theoretical median: 0 Hz; SNc—DA: n = 24, p = 0.94, non-DA: n = 27, p = 0.58; VTA—DA: n = 54, p = 0.09; non-DA: n = 65, p = 0.13). Consequently, the firing rate change was higher in these DA neurons which were subjected to the ipsilateral SC terminal stimulation (Fig. 5C; SNc ΔFR—ipsilateral: 0.32 ± 0.12 Hz, contralateral: 0.04 ± 0.05 Hz, n_ipsi= 26, n_contra= 24, U = 200, p = 0.0293; VTA ΔFR—ipsilateral: 0.36 ± 0.15 Hz, contralateral: 0.04 ± 0.02 Hz, n_ipsi= 85, n_contra= 54, U = 1,727, p = 0.0138; Mann–Whitney tests). Similar differences were observed in the non-DA cells within the SNc (ΔFR—ipsilateral: 0.47 ± 0.26 Hz, contralateral: 0.01 ± 0.03 Hz, n_ipsi= 22, n_contra= 27, U = 162, p = 0.0061), in contrast to the VTA where no differences were observed (ΔFR—ipsilateral: 0.15 ± 0.05 Hz, contralateral: 0.13 ± 0.07 Hz, n_ipsi= 131, n_contra= 65, U = 4,214, p = 0.91). Since excitation of SNc and VTA neurons following the contralateral stimulation was nearly absent, the comparison of the response parameters was not possible. The amplitude of the excitation following the ipsilateral stimulation did not differ between groups (Fig. 5E; SNc ΔFR—DA: 1.05 ± 0.29 Hz, non-DA: 2.25 ± 1.1 Hz; VTA ΔFR—DA: 1.76 ± 0.73 Hz, non-DA: 1.07 ± 0.16 Hz; Kruskal–Wallis test, Kruskal–Wallis statistic = 0.58, p = 0.9). The firing rate traces of neurons excited by ipsilateral stimulation are shown in Figure 5F. We ensured that the excited neurons were not all recorded from a single animal and were evenly distributed across the five recorded rats (average proportion of excited cells per animal ± SD: 11.38 ± 7%; rat 1: 20/100 [20%], rat 2: 20/124 [16.13%], rat 3: 11/83 [13.25%], rat 4: 0/34 [0%], rat 5: 7/93 [7.5%]). The same applies to the five inhibited cells (average proportion of inhibited cells per animal ± SD: 1.7 ± 2.18%; rat 1: 1/100 [1%], rat 2: 2/124 [1.61%], rat 3: 0/83 [0%], rat 4: 2/34 [5.88%], rat 5: 0/93 [0%]).

Figure 6 shows the distribution of all recorded cells along the anteroposterior and mediolateral axes with regard to the response type. Figure 6, A and B, illustrates the recording method and the side of the brain where the SC was transfected (ipsilateral or contralateral to the recording side). For clarity, neurons stimulated ipsilaterally or contralaterally were depicted on the left or right side, respectively, along the mediolateral axis. Since the number of responsive cells following the contralateral stimulation was insufficient for statistical analysis, only distribution of neurons ipsilateral to the transduced SC was analyzed. The distributions of excited DA and non-DA neurons differed (Pillai's trace = 0.13, F_(2,46)= 3.3, p = 0.045981, MANOVA for AP and ML axes). To determine along which axis the distributions diverged, we conducted additional tests. It was found that mediolateral distributions of excited DA and non-DA cells were significantly different (Fig. 6C; DA/non-DA × 0.2 mm ML bins: p = 0.03298, Fisher's exact test). Indeed, more excited DA cells were located laterally (odds = 2.83), while more excited non-DA cells were found medially (odds = 1.89; DA/non-DA × 1 mm ML bins: p = 0.009617, Fisher's exact test). Accordingly, in the medial part of the ventral midbrain, excited DA cells were less common than non-DA cells (odds = 0.35), while excited non-DA cells were less common laterally (odds = 0.53). On the other hand, excited DA and non-DA neurons were similarly distributed along the anteroposterior axis (Fig. 6D; DA/non-DA × 0.2 mm AP bins: p = 0.56, Fisher's exact test). The exact locations of all recorded neurons, based on their response to either ipsilateral or contralateral stimulation, are shown in single horizontal planes in Figure 6E.

Figure 6.

The distribution of neurons recorded in the ex vivo experiments. For convenience, all neurons stimulated ipsilaterally or contralaterally were moved to either left or right panels, respectively, in relation to dotted line representing the midline. A, B, Schemes of the experiment. SC was unilaterally injected with an AAV carrying genes for Chronos and GFP and after at least 3 weeks ex vivo MEA recordings combined with optogenetic stimulation of axon terminals descending from the SC were performed. Simultaneously, ipsilateral (A) and contralateral (B) ventral midbrain slices were recorded on separate MEAs, thus either ipsilateral (A) or contralateral (B) SC-originating terminals were stimulated. C, D, Mediolateral (C) and anteroposterior (D) distribution of DA neurons (top or right panel, respectively) and non-DA neurons (bottom or left panel, respectively) that underwent stimulation of ipsilateral SC-originating axon terminals with response type color-coded (red, excitation; gray, no effect; blue, inhibition). E, Localization of recorded neurons that were subjected to the stimulation of ipsilateral SC-originating axon terminals. Neuronal population (DA SNc, DA VTA, non-DA SNc, or non-DA VTA) is coded with a border color of an individual circle (purple, green, black, or orange, respectively). Response type is color-coded with the filling of an individual circle (red, excitation; gray, no effect; blue, inhibition). The size of each circle corresponds to the number of cells in a particular spot. Panels analogous to C, D, and E containing data for the contralateral SC-originating axon terminals stimulation are located right to the dotted line indicating midline.

Overall, these experiments indicate that the stimulation of the direct SC to the ventral midbrain connection can elicit excitations preferentially on the ipsilateral side of the brain. This difference is more pronounced in the population of DA neurons, as non-DA neurons within the VTA also reacted to the stimulation of the contralateral SC. Moreover, DA neurons excited by the stimulation of the ipsilateral SC tend to be localized more laterally, as opposed to non-DA neurons which lie in more medial midbrain parts.

Discussion

The presented data demonstrate, both anatomically and electrophysiologically, that innervation from the lateral SC predominantly targets the ipsilateral SNc and VTA, surpassing contralateral connections. Tract-tracing experiments reveal a clear interhemispheric lateralization of monosynaptic innervation originating from the lateral SC to the ventral midbrain. The vast majority of monosynaptically labeled cells were localized in the ipsilateral SNc; however, the lateralization was also observed in the VTA. These findings align with previous reports confirming that the SC innervates the ventral midbrain (Coizet et al., 2003, 2007; Comoli et al., 2003; McHaffie et al., 2006; May et al., 2009; Watabe-Uchida et al., 2012; Yetnikoff et al., 2015; Masullo et al., 2019; Zhou et al., 2019; Solié et al., 2022). Some of these studies even highlight the prevalence of the ipsilateral innervation; however, the detailed lateralization analysis has largely been neglected, e.g., only the ipsilateral innervation was reported. Moreover, research to date gives very little information about target cells, aside from noting that at least some of the innervated cells are TH-positive or the studies focus solely on one type of cells preventing from proper comparisons. Additionally, many of these studies focused on either the SNc or VTA or assessed differences qualitatively, making the comparison of the innervation sent from the SC to either of the regions difficult. First, we provide a comprehensive quantitative analysis of the monosynaptic innervation from the lateral SC to the ventral midbrain, detailing both the spatial distribution of innervated cells within the SNc and VTA and the laterality of these projections. Additionally, we provide quantitative data on the number of innervated cells with specific biochemical markers, indicating that slightly more than half of these cells express TH. Interestingly, many of the innervated cells are TH negative, suggesting that they are likely GABAergic, based on their distribution within the ventral midbrain (Nair-Roberts et al., 2008; Ungless and Grace, 2012). However, whether these neurons are projecting neurons or local interneurons remains an open question.

Our anatomical observations, as summarized above, align well with the electrophysiological recordings of the VTA and SNc conducted in the ex vivo preparations, where we optogenetically activated terminals originating unilaterally from the lateral SC. These results are partially corroborated by our in vivo recordings, where we applied optogenetic stimulation to either the ipsilateral or contralateral SC. Among the pharmacologically identified DA neurons in the ex vivo experiments, we observed only excitatory responses, which appeared almost exclusively on the ipsilateral side to the SC which was the source of stimulated terminals (SNc: 27 vs 4% and VTA: 19 vs 2%, respectively, on the ipsilateral vs contralateral side). The percentage of DA neurons excited in the ipsilateral VTA (∼19%) was similar to what Solié and coworkers recently showed (25% of DA neurons in the ipsilateral VTA responded with EPSCs to optogenetic stimulation of terminals originating from SC; Solié et al., 2022). They also observed that only ∼4% of DA neurons in the ipsilateral VTA responded with IPSCs. The slightly higher proportion of excited DA neurons observed in aforementioned study (25 vs 19%) may result from differences in techniques used. Solié and colleagues used patch-clamp recordings to observe membrane currents, the consequences of which would be undetectable with the extracellular recordings used in our work. We also observed excitatory responses in non-DA neurons in ex vivo preparations, confirming previous anatomical and electrophysiological studies (Zhou et al., 2019; Solié et al., 2022). Notably, in the SNc, the excited non-DA neurons (18%) were located exclusively in the hemisphere ipsilateral to the SC from which the activated fibers originated. In the VTA, however, we observed excited non-DA neurons on both the ipsilateral (17%) and contralateral sides (11%). Based on the observations described here and our previous studies, it appears that the inhibitory control of the SC over ipsilateral midbrain DA neurons may be mediated through the activation of local GABAergic interneurons, whereas control over contralateral DA neurons may occur through the activation of GABAergic neurons in the contralateral RMTg (Pradel et al., 2021) and, in case of the VTA, at least to some extent, via local interneurons. Unsurprisingly, in the in vivo preparations, we observed greater diversity of responses in VTA and SNc neurons to the activation of the lateral SC. This is likely due to polysynaptic mechanisms, considering the numerous subcortical targets of SC innervation. Nonetheless, a tendency for excitatory responses to predominate on the ipsilateral side was evident, especially in the SNc. In the SNc, more cells exhibited ipsilaterally lateralized excitation, i.e., they responded to ipsilateral SC stimulation with excitation but were nonresponsive or inhibited by contralateral stimulation. Moreover, the lateral part of the SNc was particularly reactive to ipsilateral SC manipulation, with 80% of the cells responding with excitation. Importantly, this region of the ventral midbrain received the strongest innervation from the lateral SC in our anatomical study.

Previous studies have shown that the SC can influence the activity of midbrain dopaminergic neurons; however, most of these studies relied on pharmacological interventions, lesions, or receptive field stimulation (which is known to activate the SC), rather than directly manipulating the circuit. For example, a unilateral SC lesion, as opposed to the primary visual cortex lesion, reduced visually evoked field potentials in the SNc (Comoli et al., 2003). Consistently, once the SC was pharmacologically disinhibited, the elevation of spontaneous (Coizet et al., 2003, 2006) as well as visually evoked activity of dopaminergic neurons ipsilateral to the treated SC (Comoli et al., 2003; Dommett et al., 2005; Bertram et al., 2014) and the resulting striatal dopamine release (Dommett et al., 2005) were observed. Only recently have some studies combined electrophysiological recordings with optogenetic manipulation of this circuit (Zhou et al., 2019; Solié et al., 2022). In primates, it has been demonstrated that a lesion of the primary visual cortex does not prevent the acquisition and expression of anticipatory behaviors in response to reward-associated visual cues, nor the concomitant reactions of contralateral dopaminergic neurons (Takakuwa et al., 2017). However, when additional chemical inhibition of the SC contralateral to the stimulus was performed, both the behavior and neuronal responses were abolished.

Unfortunately, by focusing only on the ipsilateral part of the circuit, most of the studies omitted a thorough analysis of laterality. Our results confirm a silently held assumption of previous studies that the SC→VTA/SNc circuit is lateralized toward the ipsilateral side. Moreover, our findings are not only consistent with existing literature but also help explain some recently observed phenomena. It has been shown that in head-fixed animals maneuvering in virtual reality, the majority of VTA dopaminergic neurons respond to transient visual stimuli, to which the SC is highly sensitive, appearing in the contralateral visual field with excitation, while stimuli on the ipsilateral side elicited inhibition or no response. Interestingly, such a disproportion was not observed by the experimenters when visual stimuli were permanent. In such case, approximately the same number of DA neurons in the VTA responded with excitation to stimuli in the contralateral as in the ipsilateral visual field. Furthermore, both in the case of transient and permanent visual stimuli, it was rare for a given DA neuron to respond in a similar fashion to both ipsilateral and contralateral stimulus, e.g., if a neuron responded with excitation to the ipsilateral stimulus, its response to the contralateral stimulus was either inhibition or lack thereof (Engelhard et al., 2019). Accordingly, the axons of dopaminergic neurons within the dorsal striatum elevate their activity only in response to the contralateral cues as well as during the rewarded contralateral actions (Moss et al., 2021). Likewise, only contralateral cues elicited responses in the dorsal striatum; however, at least part of this response depended on direct corticostriatal input (Peters et al., 2021).

The lateralization of these connections seems to be important, especially in the light of our recent findings that the SC can inhibit contralateral dopaminergic neurons via the RMTg (Pradel et al., 2021). The lateral SC, by activating ipsilateral dopaminergic neurons and inhibiting the contralateral ones (via RMTg), would be responsible for increasing DA level in the ipsilateral striatum while decreaseing it in the contralateral striatum. This is supported by the fact that the dopaminergic system is highly lateralized as the targets for its output projections are located predominantly in the same hemisphere (Molochnikov and Cohen, 2014). Extensive evidence demonstrates that interhemispheric differences in the amount of DA released in the striatum affect the direction of animal movement. Unilateral lesions of dopaminergic neurons were shown to drive spontaneous ipsiversive body rotations (Arbuthnott and Crow, 1971; Iwamoto et al., 1976; Molochnikov and Cohen, 2014), which eventually subside due to compensatory overexpression of dopaminergic receptors in the striatum on the lesioned side. Systemic administration of amphetamine in such animals induces ipsiversive rotations as drug-induced dopamine elevation is restricted to the intact hemisphere. Administration of apomorphine, however, induces contraversive rotations as it binds to overexpressed dopamine receptors in the denervated striatum (Da Cunha et al., 2008). Interestingly, systemic amphetamine injection in naïve animals enhanced their pre-injection side preference (Jerussi and Glick, 1976), revealing the basal asymmetries between left and right nigrostriatal systems (Zimmerberg et al., 1974; Glick et al., 1988). Consistently, unilateral lesion of the RMTg, and thus unilateral disinhibition of the dopaminergic system, causes contraversive rotations (Bourdy et al., 2014; Barrot et al., 2016; Faivre et al., 2020). Accordingly, injections of DA, amphetamine, or apomorphine into the striatum of naïve animals introduce contraversive bias into their behavior (Joyce et al., 1981; Molochnikov and Cohen, 2014). It was also demonstrated that unilateral optogenetic activation of striatal Go pathway induces contralateral movement and decision bias in rodents (Kravitz et al., 2010; Tai et al., 2012; Tecuapetla et al., 2014). Overall, the general rule is that animals’ behavior is directed toward the side with weaker striatal DA transmission (Da Cunha et al., 2008). These data support the notion that the SC-mediated unilateral activation of dopaminergic neurons in response to contralateral sensory stimulation, followed by asymmetrical DA release in the striatum, biases movement toward the side with weaker DA transmission, i.e., toward the stimulus.

In literature, no studies provide an exhaustive description of the topography of descending projections from the SC to the ventral midbrain. However, by analyzing the results of individual studies, one can find evidence supporting its existence. Although our study focused on the lateralization of the SC→SNc/VTA pathway, we observed that the projection to the ipsilateral SNc is stronger than to the VTA. Moreover, it appears that innervation within the SNc may be topographically organized. In line with previous retrograde tracing studies (Comoli et al., 2003), we found that the SC innervates lateral SNc more robustly, which has been linked to coding salience (Bromberg-Martin et al., 2010). This result was confirmed by our in vivo electrophysiological recordings, which showed that excitatory reactions were more prevalent in the lateral part of the ipsilateral SNc compared with its medial part or the contralateral SNc. In contrast, we did not observe such mediolateral topography in the VTA. However, given that we found weaker innervation in the posterior VTA and, correspondingly, in its ventral nuclei (paranigral and parainterfascicular), the dorsolateral VTA (parabrachial area, PBP) appeared more strongly innervated. According to Ikemoto's model (Ikemoto, 2007), further reinforced by recent research (de Jong et al., 2022), this area of the VTA gives rise to dopaminergic innervation of the ventrolateral striatum, which is linked to controlling behavior based on the perceived value of stimuli (de Jong et al., 2019). Thus, it appears that the lateral SC innervates areas of the ventral midbrain, i.e., SNc and PBP, where two complementary dopaminergic systems originate, playing crucial roles in salience detection and experience-based learning (Ikemoto, 2007; Bromberg-Martin et al., 2010; Solié et al., 2022). This suggests that the lateral SC→SNc/VTA pathway may trigger simple, nonvolitional orienting contralateral movements, while also influencing the mechanisms underlying the selection and execution of more complex orienting behaviors. The existence of similarly specialized medial pathway, connecting the SC with the ventromedial VTA, is less documented. Interestingly, the medial SC receives sensory information from the upper visual field, supporting its involvement in defensive behaviors. Indeed, stimulation of the medial SC elicits ipsilateral avoidance movements (Sahibzada et al., 1986; Comoli et al., 2012; Isa et al., 2020). Moreover, SC neurons activated by upper looming stimuli promote escape behavior, primarily via VTA GABAergic neurons (Zhou et al., 2019). In contrast, the lateral SC promotes contralateral approach movements and receives sensory information from the lower visual field (Dean et al., 1986; Sahibzada et al., 1986; Comoli et al., 2012), supporting its involvement in appetitive behaviors, such as foraging—in which DA neurons are heavily involved.

In conclusion, the findings presented in this study deepen our understanding of the neuronal pathway descending from the lateral SC to the dopaminergic structures of the ventral midbrain. Specifically, they reveal both its interhemispheric lateralization and intrahemispheric diversity in the strength and nature of innervation in different parts of the VTA and SNc. Combined with previous research, our results suggest that sensory information from one side of the body may predominantly reach the contralateral dopaminergic system through the lateral SC in the same hemisphere. The resulting DA release in the striatum, ipsilateral to the activated dopaminergic system (and SC), could thus promote contralateral orientation and movement toward the stimulus. This hypothesis is further supported by our earlier research, which shows that the SC can also inhibit the contralateral dopaminergic system via the RMTg (Pradel et al., 2021), thereby increasing the asymmetry in DA release between the left and right striatum. As both mechanisms are likely additive, we propose that this brain circuitry facilitates directional movement toward the source of incoming sensory information.

Footnotes

This work was supported by the Polish National Science Center grants: 2017/27/N/NZ4/00785 and 2020/36/T/NZ4/00341 awarded to K.P., 2018/28/C/NZ4/00099 awarded to Ł.C., 2019/33/B/NZ4/03127 awarded to T.B., and the statutory funds of the Institute of Zoology and Biomedical Research, Jagiellonian University. The publication has been supported by a grant from the Priority Research Area FutureSoc under the Strategic Programme Excellence Initiative at the Jagiellonian University.
The authors declare no competing financial interests.
Correspondence should be addressed to Kamil Pradel at kamil.pradel{at}gmail.com or Tomasz Błasiak at tomasz.blasiak{at}uj.edu.pl.

SfN exclusive license.

References

↵
1. Arbuthnott GW,
2. Crow TJ
(1971) Relation of contraversive turning to unilateral release of dopamine from the nigrostriatal pathway in rats. Exp Neurol 30:484–491. https://doi.org/10.1016/0014-4886(71)90149-X
OpenUrl CrossRef PubMed
↵
1. Baik JH
(2013) Dopamine signaling in reward-related behaviors. Front Neural Circuits 7:152. https://doi.org/10.3389/fncir.2013.00152 pmid:24130517
OpenUrl CrossRef PubMed
↵
1. Barrot M,
2. Georges F,
3. Veinante P
(2016) Chapter 25 – The tail of the ventral tegmental area/rostromedial tegmental nucleus: a modulator of midbrain dopamine systems. In: Handbook of behavioral neuroscience (Steiner H, Tseng KY, eds), pp 495–511. Amsterdam: Elsevier B.V.
↵
1. Bertram C,
2. Dahan L,
3. Boorman LW,
4. Harris S,
5. Vautrelle N,
6. Leriche M,
7. Redgrave P,
8. Overton PG
(2014) Cortical regulation of dopaminergic neurons: role of the midbrain superior colliculus. J Neurophysiol 111:755–767. https://doi.org/10.1152/jn.00329.2013 pmid:24225541
OpenUrl CrossRef PubMed
↵
1. Bourdy R,
2. Barrot M
(2012) A new control center for dopaminergic systems: pulling the VTA by the tail. Trends Neurosci 35:681–690. https://doi.org/10.1016/j.tins.2012.06.007
OpenUrl CrossRef PubMed
↵
1. Bourdy R,
2. Sánchez-Catalán MJ,
3. Kaufling J,
4. Balcita-Pedicino JJ,
5. Freund-Mercier MJ,
6. Veinante P,
7. Sesack SR,
8. Georges F,
9. Barrot M
(2014) Control of the nigrostriatal dopamine neuron activity and motor function by the tail of the ventral tegmental area. Neuropsychopharmacology 39:2788–2798. https://doi.org/10.1038/npp.2014.129 pmid:24896615
OpenUrl CrossRef PubMed
↵
1. Bromberg-Martin ES,
2. Matsumoto M,
3. Hikosaka O
(2010) Dopamine in motivational control: rewarding, aversive, and alerting. Neuron 68:815–834. https://doi.org/10.1016/j.neuron.2010.11.022 pmid:21144997
OpenUrl CrossRef PubMed
↵
1. Brown AJ, et al.
(2013) Whole-rat conditional gene knockout via genome editing. Nat Methods 10:638–640. https://doi.org/10.1038/nmeth.2516
OpenUrl CrossRef PubMed
↵
1. Centonze D,
2. Usiello A,
3. Gubellini P,
4. Pisani A,
5. Borrelli E,
6. Bernardi G,
7. Calabresi P
(2002) Dopamine D2 receptor-mediated inhibition of dopaminergic neurons in mice lacking D2L receptors. Neuropsychopharmacology 27:723–726. https://doi.org/10.1016/S0893-133X(02)00367-6
OpenUrl CrossRef PubMed
↵
1. Coizet V,
2. Comoli E,
3. Westby GWM,
4. Redgrave P
(2003) Phasic activation of substantia nigra and the ventral tegmental area by chemical stimulation of the superior colliculus: an electrophysiological investigation in the rat. Eur J Neurosci 17:28–40. https://doi.org/10.1046/j.1460-9568.2003.02415.x
OpenUrl CrossRef PubMed
↵
1. Coizet V,
2. Dommett EJ,
3. Redgrave P,
4. Overton PG
(2006) Nociceptive responses of midbrain dopaminergic neurones are modulated by the superior colliculus in the rat. Neuroscience 139:1479–1493. https://doi.org/10.1016/j.neuroscience.2006.01.030
OpenUrl CrossRef PubMed
↵
1. Coizet V,
2. Overton PG,
3. Redgrave P
(2007) Collateralization of the tectonigral projection with other major output pathways of superior colliculus in the rat. J Comp Neurol 500:1034–1049. https://doi.org/10.1002/cne.21202 pmid:17183537
OpenUrl CrossRef PubMed
↵
1. Comoli E,
2. Coizet V,
3. Boyes J,
4. Bolam JP,
5. Canteras NS,
6. Quirk RH,
7. Overton PG,
8. Redgrave P
(2003) A direct projection from superior colliculus to substantia nigra for detecting salient visual events. Nat Neurosci 6:974–980. https://doi.org/10.1038/nn1113
OpenUrl CrossRef PubMed
↵
1. Comoli E,
2. Favaro PDN,
3. Vautrelle N,
4. Leriche M,
5. Overton PG,
6. Redgrave P
(2012) Segregated anatomical input to sub-regions of the rodent superior colliculus associated with approach and defense. Front Neuroanat 6:9. https://doi.org/10.3389/fnana.2012.00009 pmid:22514521
OpenUrl CrossRef PubMed
↵
1. Da Cunha C,
2. Wietzikoski EC,
3. Ferro MM,
4. Martinez GR,
5. Vital MABF,
6. Hipólide D,
7. Tufik S,
8. Canteras NS
(2008) Hemiparkinsonian rats rotate toward the side with the weaker dopaminergic neurotransmission. Behav Brain Res 189:364–372. https://doi.org/10.1016/j.bbr.2008.01.012
OpenUrl CrossRef PubMed
↵
1. Dean P,
2. Redgrave P,
3. Sahibzada N,
4. Tsuji K
(1986) Head and body movements produced by electrical stimulation of superior colliculus in rats: effects of interruption of crossed tectoreticulospinal pathway. Neuroscience 19:367–380. https://doi.org/10.1016/0306-4522(86)90267-8
OpenUrl CrossRef PubMed
↵
1. de Jong JW,
2. Afjei SA,
3. Dorocic IP,
4. Peck JR,
5. Liu C,
6. Kim CK,
7. Tian L,
8. Deisseroth K,
9. Lammel S
(2019) A neural circuit mechanism for encoding aversive stimuli in the mesolimbic dopamine system. Neuron 101:133–151.e7. https://doi.org/10.1016/j.neuron.2018.11.005 pmid:30503173
OpenUrl CrossRef PubMed
↵
1. de Jong JW,
2. Fraser KM,
3. Lammel S
(2022) Mesoaccumbal dopamine heterogeneity: what do dopamine firing and release have to do with it? Annu Rev Neurosci 45:109–129. https://doi.org/10.1146/annurev-neuro-110920-011929 pmid:35226827
OpenUrl CrossRef PubMed
↵
1. Dommett E,
2. Coizet V,
3. Blaha CD,
4. Martindale J,
5. Lefebvre V,
6. Walton N,
7. Mayhew JEW,
8. Overton PG,
9. Redgrave P
(2005) How visual stimuli activate dopaminergic neurons at short latency. Science 307:1476–1479. https://doi.org/10.1126/science.1107026
OpenUrl Abstract/FREE Full Text
↵
1. Engelhard B, et al.
(2019) Specialized coding of sensory, motor and cognitive variables in VTA dopamine neurons. Nature 570:509–513. https://doi.org/10.1038/s41586-019-1261-9 pmid:31142844
OpenUrl CrossRef PubMed
↵
1. Faivre F,
2. Sánchez-Catalán MJ,
3. Dovero S,
4. Bido S,
5. Joshi A,
6. Bezard E,
7. Barrot M
(2020) Ablation of the tail of the ventral tegmental area compensates symptoms in an experimental model of Parkinson’s disease. Neurobiol Dis 139:104818. https://doi.org/10.1016/j.nbd.2020.104818
OpenUrl CrossRef PubMed
↵
1. Felsen G,
2. Mainen ZF
(2008) Neural substrates of sensory-guided locomotor decisions in the rat superior colliculus. Neuron 60:137–148. https://doi.org/10.1016/j.neuron.2008.09.019 pmid:18940594
OpenUrl CrossRef PubMed
↵
1. Gandhi NJ,
2. Katnani HA
(2011) Motor functions of the superior colliculus. Annu Rev Neurosci 34:205–231. https://doi.org/10.1146/annurev-neuro-061010-113728 pmid:21456962
OpenUrl CrossRef PubMed
↵
1. Glick SD,
2. Carlson JN,
3. Baird JL,
4. Maisonneuve IM,
5. Bullock AE
(1988) Basal and amphetamine-induced asymmetries in striatal dopamine release and metabolism: bilateral in vivo microdialysis in normal rats. Brain Res 473:161–164. https://doi.org/10.1016/0006-8993(88)90329-0
OpenUrl CrossRef PubMed
↵
1. Grace AA,
2. Bunney BS
(1980) Nigral dopamine neurons: intracellular recording and identification with L-dopa injection and histofluorescence. Science 210:654–656. https://doi.org/10.1126/science.7433992
OpenUrl Abstract/FREE Full Text
↵
1. Grace AA,
2. Bunney BS
(1983) Intracellular and extracellular electrophysiology of nigral dopaminergic neurons—1. Identification and characterization. Neuroscience 10:301–315. https://doi.org/10.1016/0306-4522(83)90135-5
OpenUrl CrossRef PubMed
↵
1. Huang L, et al.
(2019) A visual circuit related to habenula underlies the antidepressive effects of light therapy. Neuron 102:128–142.e8. https://doi.org/10.1016/j.neuron.2019.01.037
OpenUrl PubMed
↵
1. Ikemoto S
(2007) Dopamine reward circuitry: two projection systems from the ventral midbrain to the nucleus accumbens-olfactory tubercle complex. Brain Res Re 56:27–78. https://doi.org/10.1016/j.brainresrev.2007.05.004 pmid:17574681
OpenUrl CrossRef PubMed
↵
1. Isa K,
2. Sooksawate T,
3. Kobayashi K,
4. Kobayashi K,
5. Redgrave P,
6. Isa T
(2020) Dissecting the tectal output channels for orienting and defense responses. eNeuro 7:ENEURO.0271-20.2020. https://doi.org/10.1523/ENEURO.0271-20.2020 pmid:32928881
OpenUrl Abstract/FREE Full Text
↵
1. Iwamoto ET,
2. Loh HH,
3. Way EL
(1976) Circling behavior in rats with 6-hydroxydopamine or electrolytic nigral lesions. Eur J Pharmacol 37:339–356. https://doi.org/10.1016/0014-2999(76)90042-X
OpenUrl CrossRef PubMed
↵
1. Jerussi TP,
2. Glick SD
(1976) Drug-induced rotation in rats without lesions: behavioral and neurochemical indices of a normal asymmetry in nigro-striatal function. Psychopharmacology 47:249–260. https://doi.org/10.1007/BF00427609
OpenUrl CrossRef PubMed
↵
1. Jhou TC,
2. Fields HL,
3. Baxter MG,
4. Saper CB,
5. Holland PC
(2009a) The rostromedial tegmental nucleus (RMTg), a GABAergic afferent to midbrain dopamine neurons, encodes aversive stimuli and inhibits motor responses. Neuron 61:786–800. https://doi.org/10.1016/j.neuron.2009.02.001 pmid:19285474
OpenUrl CrossRef PubMed
↵
1. Jhou TC,
2. Geisler S,
3. Marinelli M,
4. Degarmo BA,
5. Zahm DS
(2009b) The mesopontine rostromedial tegmental nucleus: a structure targeted by the lateral habenula that projects to the ventral tegmental area of Tsai and substantia nigra compacta. J Comp Neurol 513:566–596. https://doi.org/10.1002/cne.21891 pmid:19235216
OpenUrl CrossRef PubMed
↵
1. Joyce JN,
2. Davis RE,
3. Van Hartesveldt C
(1981) Behavioral effects of unilateral dopamine injection into dorsal or ventral striatum. Eur J Pharmacol 72:1–10. https://doi.org/10.1016/0014-2999(81)90290-9
OpenUrl CrossRef PubMed
↵
1. Kravitz AV,
2. Freeze BS,
3. Parker PRL,
4. Kay K,
5. Myo T,
6. Deisseroth K,
7. Kreitzer AC
(2010) Control of basal ganglia circuitry. Nature 466:622–626. https://doi.org/10.1038/nature09159 pmid:20613723
OpenUrl CrossRef PubMed
↵
1. Marinelli M,
2. McCutcheon JE
(2014) Heterogeneity of dopamine neuron activity across traits and states. Neuroscience 282:176–197. https://doi.org/10.1016/j.neuroscience.2014.07.034 pmid:25084048
OpenUrl CrossRef PubMed
↵
1. Masullo L,
2. Mariotti L,
3. Alexandre N,
4. Freire-Pritchett P,
5. Boulanger J,
6. Tripodi M
(2019) Genetically defined functional modules for spatial orienting in the mouse superior colliculus. Curr Biol 29:2892–2904.e8. https://doi.org/10.1016/j.cub.2019.07.083 pmid:31474533
OpenUrl CrossRef PubMed
↵
1. May PJ
(2006) The mammalian superior colliculus: laminar structure and connections. Prog Brain Res 151:321–378. https://doi.org/10.1016/S0079-6123(05)51011-2
OpenUrl CrossRef PubMed
↵
1. May PJ,
2. McHaffie JG,
3. Stanford TR,
4. Jiang H,
5. Costello MG,
6. Coizet V,
7. Hayes LM,
8. Haber SN,
9. Redgrave P
(2009) Tectonigral projections in the primate: a pathway for pre-attentive sensory input to midbrain dopaminergic neurons. Eur J Neurosci 29:575–587. https://doi.org/10.1111/j.1460-9568.2008.06596.x pmid:19175405
OpenUrl CrossRef PubMed
↵
1. McHaffie J,
2. Jiang H,
3. May P,
4. Coizet V,
5. Overton P,
6. Stein B,
7. Redgrave P
(2006) A direct projection from superior colliculus to substantia nigra pars compacta in the cat. Neuroscience 138:221–234. https://doi.org/10.1016/j.neuroscience.2005.11.015
OpenUrl CrossRef PubMed
↵
1. Molochnikov I,
2. Cohen D
(2014) Hemispheric differences in the mesostriatal dopaminergic system. Front Syst Neurosci 8:110. https://doi.org/10.3389/fnsys.2014.00110 pmid:24966817
OpenUrl CrossRef PubMed
↵
1. Moss MM,
2. Zatka-Haas P,
3. Harris KD,
4. Carandini M,
5. Lak A
(2021) Dopamine axons in dorsal striatum encode contralateral visual stimuli and choices. J Neurosci 41:7197–7205. https://doi.org/10.1523/JNEUROSCI.0490-21.2021 pmid:34253628
OpenUrl Abstract/FREE Full Text
↵
1. Nair-Roberts RG,
2. Chatelain-Badie SD,
3. Benson E,
4. White-Cooper H,
5. Bolam JP,
6. Ungless MA
(2008) Stereological estimates of dopaminergic, GABAergic and glutamatergic neurons in the ventral tegmental area, substantia nigra and retrorubral field in the rat. Neuroscience 152:1024–1031. https://doi.org/10.1016/j.neuroscience.2008.01.046 pmid:18355970
OpenUrl CrossRef PubMed
↵
1. Pachitariu M,
2. Steinmetz NA,
3. Kadir S,
4. Carandini M,
5. Harris KD
(2016) Kilosort: realtime spike-sorting for extracellular electrophysiology with hundreds of channels. bioRxiv 061481:1–14. https://doi.org/10.1101/061481
OpenUrl
↵
1. Paxinos G,
2. Watson C
(2007) The rat brain in stereotaxic coordinates, Ed 6. Elsevier.
↵
1. Peters AJ,
2. Fabre JMJ,
3. Steinmetz NA,
4. Harris KD,
5. Carandini M
(2021) Striatal activity topographically reflects cortical activity. Nature 591:420–425. https://doi.org/10.1038/s41586-020-03166-8 pmid:33473213
OpenUrl CrossRef PubMed
↵
1. Pradel K,
2. Drwięga G,
3. Błasiak T
(2021) Superior colliculus controls the activity of the rostromedial tegmental nuclei in an asymmetrical manner. J Neurosci 41:4006–4022. https://doi.org/10.1523/JNEUROSCI.1556-20.2021 pmid:33741724
OpenUrl Abstract/FREE Full Text
↵
1. Redgrave P,
2. Coizet V,
3. Comoli E,
4. McHaffie JG,
5. Leriche M,
6. Vautrelle N,
7. Hayes LM,
8. Overton P
(2010) Interactions between the midbrain superior colliculus and the basal ganglia. Front Neuroanat 4:132. https://doi.org/10.3389/fnana.2010.00132 pmid:20941324
OpenUrl PubMed
↵
1. Sahibzada N,
2. Dean P,
3. Redgrave P
(1986) Movements resembling orientation or avoidance elicited by electrical stimulation of the superior colliculus in rats. J Neurosci 6:723–733. https://doi.org/10.1523/JNEUROSCI.06-03-00723.1986 pmid:3958791
OpenUrl Abstract/FREE Full Text
↵
1. Solié C,
2. Contestabile A,
3. Espinosa P,
4. Musardo S,
5. Bariselli S,
6. Huber C,
7. Carleton A,
8. Bellone C
(2022) Superior colliculus to VTA pathway controls orienting response and influences social interaction. Nat Commun 13:817. https://doi.org/10.1038/s41467-022-28512-4 pmid:35145124
OpenUrl CrossRef PubMed
↵
1. Tai LH,
2. Lee AM,
3. Benavidez N,
4. Bonci A,
5. Wilbrecht L
(2012) Transient stimulation of distinct subpopulations of striatal neurons mimics changes in action value. Nat Neurosci 15:1281–1289. https://doi.org/10.1038/nn.3188 pmid:22902719
OpenUrl CrossRef PubMed
↵
1. Takakuwa N,
2. Kato R,
3. Redgrave P,
4. Isa T
(2017) Emergence of visually-evoked reward expectation signals in dopamine neurons via the superior colliculus in V1 lesioned monkeys. Elife 6:e24459. https://doi.org/10.7554/eLife.24459 pmid:28628005
OpenUrl CrossRef PubMed
↵
1. Tecuapetla F,
2. Matias S,
3. Dugue GP,
4. Mainen ZF,
5. Costa RM
(2014) Balanced activity in basal ganglia projection pathways is critical for contraversive movements. Nat Commun 5:4315. https://doi.org/10.1038/ncomms5315 pmid:25002180
OpenUrl CrossRef PubMed
↵
1. Ungless MA,
2. Grace AA
(2012) Are you or aren’t you? Challenges associated with physiologically identifying dopamine neurons. Trends Neurosci 35:422–430. https://doi.org/10.1016/j.tins.2012.02.003 pmid:22459161
OpenUrl CrossRef PubMed
↵
1. Walczak M,
2. Błasiak T
(2017) Midbrain dopaminergic neuron activity across alternating brain states of urethane anaesthetized rat. Eur J Neurosci 45:1068–1077. https://doi.org/10.1111/ejn.13533
OpenUrl CrossRef PubMed
↵
1. Watabe-Uchida M,
2. Zhu L,
3. Ogawa SK,
4. Vamanrao A,
5. Uchida N
(2012) Whole-brain mapping of direct inputs to midbrain dopamine neurons. Neuron 74:858–873. https://doi.org/10.1016/j.neuron.2012.03.017
OpenUrl CrossRef PubMed
↵
1. Wilson JJ,
2. Alexandre N,
3. Trentin C,
4. Tripodi M
(2018) Three-dimensional representation of motor space in the mouse superior colliculus. Curr Biol 28:1744–1755.e12. https://doi.org/10.1016/j.cub.2018.04.021 pmid:29779875
OpenUrl CrossRef PubMed
↵
1. Wise RA
(2004) Dopamine, learning and motivation. Nat Rev Neurosci 5:483–494. https://doi.org/10.1038/nrn1406
OpenUrl CrossRef PubMed
↵
1. Yetnikoff L,
2. Cheng AY,
3. Lavezzi HN,
4. Parsley KP,
5. Zahm DS
(2015) Sources of input to the rostromedial tegmental nucleus, ventral tegmental area, and lateral habenula compared: a study in rat. J Comp Neurol 523:2426–2456. https://doi.org/10.1002/cne.23797 pmid:25940654
OpenUrl CrossRef PubMed
↵
1. Zhou Z, et al.
(2019) A VTA GABAergic neural circuit mediates visually evoked innate defensive responses. Neuron 103:473–488.e6. https://doi.org/10.1016/j.neuron.2019.05.027
OpenUrl PubMed
↵
1. Zimmerberg B,
2. Glick SD,
3. Jerussi TP
(1974) Neurochemical correlate of a spatial preference in rats. Science 185:623–625. https://doi.org/10.1126/science.185.4151.623
OpenUrl Abstract/FREE Full Text
↵
1. Zingg B,
2. Chou XL,
3. Zhang ZG,
4. Mesik L,
5. Liang F,
6. Tao HW,
7. Zhang LI
(2017) AAV-mediated anterograde transsynaptic tagging: mapping corticocollicular input-defined neural pathways for defense behaviors. Neuron 93:33–47. https://doi.org/10.1016/j.neuron.2016.11.045 pmid:27989459
OpenUrl CrossRef PubMed

In this issue

View Full Page PDF

Citation Tools

Respond to this article

Request Permissions

Keywords

Cited By...

Research Articles

Show more Research Articles

Systems/Circuits

Show more Systems/Circuits

[1] ↵
Arbuthnott GW,
Crow TJ
(1971) Relation of contraversive turning to unilateral release of dopamine from the nigrostriatal pathway in rats. Exp Neurol 30:484–491. https://doi.org/10.1016/0014-4886(71)90149-X
OpenUrl CrossRef PubMed

[2] Arbuthnott GW,

[3] Crow TJ

[4] ↵
Baik JH
(2013) Dopamine signaling in reward-related behaviors. Front Neural Circuits 7:152. https://doi.org/10.3389/fncir.2013.00152 pmid:24130517
OpenUrl CrossRef PubMed

[5] Baik JH

[6] ↵
Barrot M,
Georges F,
Veinante P
(2016) Chapter 25 – The tail of the ventral tegmental area/rostromedial tegmental nucleus: a modulator of midbrain dopamine systems. In: Handbook of behavioral neuroscience (Steiner H, Tseng KY, eds), pp 495–511. Amsterdam: Elsevier B.V.

[7] Barrot M,

[8] Georges F,

[9] Veinante P

[10] ↵
Bertram C,
Dahan L,
Boorman LW,
Harris S,
Vautrelle N,
Leriche M,
Redgrave P,
Overton PG
(2014) Cortical regulation of dopaminergic neurons: role of the midbrain superior colliculus. J Neurophysiol 111:755–767. https://doi.org/10.1152/jn.00329.2013 pmid:24225541
OpenUrl CrossRef PubMed

[11] Bertram C,

[12] Dahan L,

[13] Boorman LW,

[14] Harris S,

[15] Vautrelle N,

[16] Leriche M,

[17] Redgrave P,

[18] Overton PG

[19] ↵
Bourdy R,
Barrot M
(2012) A new control center for dopaminergic systems: pulling the VTA by the tail. Trends Neurosci 35:681–690. https://doi.org/10.1016/j.tins.2012.06.007
OpenUrl CrossRef PubMed

[20] Bourdy R,

[21] Barrot M

[22] ↵
Bourdy R,
Sánchez-Catalán MJ,
Kaufling J,
Balcita-Pedicino JJ,
Freund-Mercier MJ,
Veinante P,
Sesack SR,
Georges F,
Barrot M
(2014) Control of the nigrostriatal dopamine neuron activity and motor function by the tail of the ventral tegmental area. Neuropsychopharmacology 39:2788–2798. https://doi.org/10.1038/npp.2014.129 pmid:24896615
OpenUrl CrossRef PubMed

[23] Bourdy R,

[24] Sánchez-Catalán MJ,

[25] Kaufling J,

[26] Balcita-Pedicino JJ,

[27] Freund-Mercier MJ,

[28] Veinante P,

[29] Sesack SR,

[30] Georges F,

[31] Barrot M

[32] ↵
Bromberg-Martin ES,
Matsumoto M,
Hikosaka O
(2010) Dopamine in motivational control: rewarding, aversive, and alerting. Neuron 68:815–834. https://doi.org/10.1016/j.neuron.2010.11.022 pmid:21144997
OpenUrl CrossRef PubMed

[33] Bromberg-Martin ES,

[34] Matsumoto M,

[35] Hikosaka O

[36] ↵
Brown AJ, et al.
(2013) Whole-rat conditional gene knockout via genome editing. Nat Methods 10:638–640. https://doi.org/10.1038/nmeth.2516
OpenUrl CrossRef PubMed

[37] Brown AJ, et al.

[38] ↵
Centonze D,
Usiello A,
Gubellini P,
Pisani A,
Borrelli E,
Bernardi G,
Calabresi P
(2002) Dopamine D2 receptor-mediated inhibition of dopaminergic neurons in mice lacking D2L receptors. Neuropsychopharmacology 27:723–726. https://doi.org/10.1016/S0893-133X(02)00367-6
OpenUrl CrossRef PubMed

[39] Centonze D,

[40] Usiello A,

[41] Gubellini P,

[42] Pisani A,

[43] Borrelli E,

[44] Bernardi G,

[45] Calabresi P

[46] ↵
Coizet V,
Comoli E,
Westby GWM,
Redgrave P
(2003) Phasic activation of substantia nigra and the ventral tegmental area by chemical stimulation of the superior colliculus: an electrophysiological investigation in the rat. Eur J Neurosci 17:28–40. https://doi.org/10.1046/j.1460-9568.2003.02415.x
OpenUrl CrossRef PubMed

[47] Coizet V,

[48] Comoli E,

[49] Westby GWM,

[50] Redgrave P

[51] ↵
Coizet V,
Dommett EJ,
Redgrave P,
Overton PG
(2006) Nociceptive responses of midbrain dopaminergic neurones are modulated by the superior colliculus in the rat. Neuroscience 139:1479–1493. https://doi.org/10.1016/j.neuroscience.2006.01.030
OpenUrl CrossRef PubMed

[52] Coizet V,

[53] Dommett EJ,

[54] Redgrave P,

[55] Overton PG

[56] ↵
Coizet V,
Overton PG,
Redgrave P
(2007) Collateralization of the tectonigral projection with other major output pathways of superior colliculus in the rat. J Comp Neurol 500:1034–1049. https://doi.org/10.1002/cne.21202 pmid:17183537
OpenUrl CrossRef PubMed

[57] Coizet V,

[58] Overton PG,

[59] Redgrave P

[60] ↵
Comoli E,
Coizet V,
Boyes J,
Bolam JP,
Canteras NS,
Quirk RH,
Overton PG,
Redgrave P
(2003) A direct projection from superior colliculus to substantia nigra for detecting salient visual events. Nat Neurosci 6:974–980. https://doi.org/10.1038/nn1113
OpenUrl CrossRef PubMed

[61] Comoli E,

[62] Coizet V,

[63] Boyes J,

[64] Bolam JP,

[65] Canteras NS,

[66] Quirk RH,

[67] Overton PG,

[68] Redgrave P

[69] ↵
Comoli E,
Favaro PDN,
Vautrelle N,
Leriche M,
Overton PG,
Redgrave P
(2012) Segregated anatomical input to sub-regions of the rodent superior colliculus associated with approach and defense. Front Neuroanat 6:9. https://doi.org/10.3389/fnana.2012.00009 pmid:22514521
OpenUrl CrossRef PubMed

[70] Comoli E,

[71] Favaro PDN,

[72] Vautrelle N,

[73] Leriche M,

[74] Overton PG,

[75] Redgrave P

[76] ↵
Da Cunha C,
Wietzikoski EC,
Ferro MM,
Martinez GR,
Vital MABF,
Hipólide D,
Tufik S,
Canteras NS
(2008) Hemiparkinsonian rats rotate toward the side with the weaker dopaminergic neurotransmission. Behav Brain Res 189:364–372. https://doi.org/10.1016/j.bbr.2008.01.012
OpenUrl CrossRef PubMed

[77] Da Cunha C,

[78] Wietzikoski EC,

[79] Ferro MM,

[80] Martinez GR,

[81] Vital MABF,

[82] Hipólide D,

[83] Tufik S,

[84] Canteras NS

[85] ↵
Dean P,
Redgrave P,
Sahibzada N,
Tsuji K
(1986) Head and body movements produced by electrical stimulation of superior colliculus in rats: effects of interruption of crossed tectoreticulospinal pathway. Neuroscience 19:367–380. https://doi.org/10.1016/0306-4522(86)90267-8
OpenUrl CrossRef PubMed

[86] Dean P,

[87] Redgrave P,

[88] Sahibzada N,

[89] Tsuji K

[90] ↵
de Jong JW,
Afjei SA,
Dorocic IP,
Peck JR,
Liu C,
Kim CK,
Tian L,
Deisseroth K,
Lammel S
(2019) A neural circuit mechanism for encoding aversive stimuli in the mesolimbic dopamine system. Neuron 101:133–151.e7. https://doi.org/10.1016/j.neuron.2018.11.005 pmid:30503173
OpenUrl CrossRef PubMed

[91] de Jong JW,

[92] Afjei SA,

[93] Dorocic IP,

[94] Peck JR,

[95] Liu C,

[96] Kim CK,

[97] Tian L,

[98] Deisseroth K,

[99] Lammel S

[100] ↵
de Jong JW,
Fraser KM,
Lammel S
(2022) Mesoaccumbal dopamine heterogeneity: what do dopamine firing and release have to do with it? Annu Rev Neurosci 45:109–129. https://doi.org/10.1146/annurev-neuro-110920-011929 pmid:35226827
OpenUrl CrossRef PubMed

[101] de Jong JW,

[102] Fraser KM,

[103] Lammel S

[104] ↵
Dommett E,
Coizet V,
Blaha CD,
Martindale J,
Lefebvre V,
Walton N,
Mayhew JEW,
Overton PG,
Redgrave P
(2005) How visual stimuli activate dopaminergic neurons at short latency. Science 307:1476–1479. https://doi.org/10.1126/science.1107026
OpenUrl Abstract/FREE Full Text

[105] Dommett E,

[106] Coizet V,

[107] Blaha CD,

[108] Martindale J,

[109] Lefebvre V,

[110] Walton N,

[111] Mayhew JEW,

[112] Overton PG,

[113] Redgrave P

[114] ↵
Engelhard B, et al.
(2019) Specialized coding of sensory, motor and cognitive variables in VTA dopamine neurons. Nature 570:509–513. https://doi.org/10.1038/s41586-019-1261-9 pmid:31142844
OpenUrl CrossRef PubMed

[115] Engelhard B, et al.

[116] ↵
Faivre F,
Sánchez-Catalán MJ,
Dovero S,
Bido S,
Joshi A,
Bezard E,
Barrot M
(2020) Ablation of the tail of the ventral tegmental area compensates symptoms in an experimental model of Parkinson’s disease. Neurobiol Dis 139:104818. https://doi.org/10.1016/j.nbd.2020.104818
OpenUrl CrossRef PubMed

[117] Faivre F,

[118] Sánchez-Catalán MJ,

[119] Dovero S,

[120] Bido S,

[121] Joshi A,

[122] Bezard E,

[123] Barrot M

[124] ↵
Felsen G,
Mainen ZF
(2008) Neural substrates of sensory-guided locomotor decisions in the rat superior colliculus. Neuron 60:137–148. https://doi.org/10.1016/j.neuron.2008.09.019 pmid:18940594
OpenUrl CrossRef PubMed

[125] Felsen G,

[126] Mainen ZF

[127] ↵
Gandhi NJ,
Katnani HA
(2011) Motor functions of the superior colliculus. Annu Rev Neurosci 34:205–231. https://doi.org/10.1146/annurev-neuro-061010-113728 pmid:21456962
OpenUrl CrossRef PubMed

[128] Gandhi NJ,

[129] Katnani HA

[130] ↵
Glick SD,
Carlson JN,
Baird JL,
Maisonneuve IM,
Bullock AE
(1988) Basal and amphetamine-induced asymmetries in striatal dopamine release and metabolism: bilateral in vivo microdialysis in normal rats. Brain Res 473:161–164. https://doi.org/10.1016/0006-8993(88)90329-0
OpenUrl CrossRef PubMed

[131] Glick SD,

[132] Carlson JN,

[133] Baird JL,

[134] Maisonneuve IM,

[135] Bullock AE

[136] ↵
Grace AA,
Bunney BS
(1980) Nigral dopamine neurons: intracellular recording and identification with L-dopa injection and histofluorescence. Science 210:654–656. https://doi.org/10.1126/science.7433992
OpenUrl Abstract/FREE Full Text

[137] Grace AA,

[138] Bunney BS

[139] ↵
Grace AA,
Bunney BS
(1983) Intracellular and extracellular electrophysiology of nigral dopaminergic neurons—1. Identification and characterization. Neuroscience 10:301–315. https://doi.org/10.1016/0306-4522(83)90135-5
OpenUrl CrossRef PubMed

[140] Grace AA,

[141] Bunney BS

[142] ↵
Huang L, et al.
(2019) A visual circuit related to habenula underlies the antidepressive effects of light therapy. Neuron 102:128–142.e8. https://doi.org/10.1016/j.neuron.2019.01.037
OpenUrl PubMed

[143] Huang L, et al.

[144] ↵
Ikemoto S
(2007) Dopamine reward circuitry: two projection systems from the ventral midbrain to the nucleus accumbens-olfactory tubercle complex. Brain Res Re 56:27–78. https://doi.org/10.1016/j.brainresrev.2007.05.004 pmid:17574681
OpenUrl CrossRef PubMed

[145] Ikemoto S

[146] ↵
Isa K,
Sooksawate T,
Kobayashi K,
Kobayashi K,
Redgrave P,
Isa T
(2020) Dissecting the tectal output channels for orienting and defense responses. eNeuro 7:ENEURO.0271-20.2020. https://doi.org/10.1523/ENEURO.0271-20.2020 pmid:32928881
OpenUrl Abstract/FREE Full Text

[147] Isa K,

[148] Sooksawate T,

[149] Kobayashi K,

[150] Kobayashi K,

[151] Redgrave P,

[152] Isa T

[153] ↵
Iwamoto ET,
Loh HH,
Way EL
(1976) Circling behavior in rats with 6-hydroxydopamine or electrolytic nigral lesions. Eur J Pharmacol 37:339–356. https://doi.org/10.1016/0014-2999(76)90042-X
OpenUrl CrossRef PubMed

[154] Iwamoto ET,

[155] Loh HH,

[156] Way EL

[157] ↵
Jerussi TP,
Glick SD
(1976) Drug-induced rotation in rats without lesions: behavioral and neurochemical indices of a normal asymmetry in nigro-striatal function. Psychopharmacology 47:249–260. https://doi.org/10.1007/BF00427609
OpenUrl CrossRef PubMed

[158] Jerussi TP,

[159] Glick SD

[160] ↵
Jhou TC,
Fields HL,
Baxter MG,
Saper CB,
Holland PC
(2009a) The rostromedial tegmental nucleus (RMTg), a GABAergic afferent to midbrain dopamine neurons, encodes aversive stimuli and inhibits motor responses. Neuron 61:786–800. https://doi.org/10.1016/j.neuron.2009.02.001 pmid:19285474
OpenUrl CrossRef PubMed

[161] Jhou TC,

[162] Fields HL,

[163] Baxter MG,

[164] Saper CB,

[165] Holland PC

[166] ↵
Jhou TC,
Geisler S,
Marinelli M,
Degarmo BA,
Zahm DS
(2009b) The mesopontine rostromedial tegmental nucleus: a structure targeted by the lateral habenula that projects to the ventral tegmental area of Tsai and substantia nigra compacta. J Comp Neurol 513:566–596. https://doi.org/10.1002/cne.21891 pmid:19235216
OpenUrl CrossRef PubMed

[167] Jhou TC,

[168] Geisler S,

[169] Marinelli M,

[170] Degarmo BA,

[171] Zahm DS

[172] ↵
Joyce JN,
Davis RE,
Van Hartesveldt C
(1981) Behavioral effects of unilateral dopamine injection into dorsal or ventral striatum. Eur J Pharmacol 72:1–10. https://doi.org/10.1016/0014-2999(81)90290-9
OpenUrl CrossRef PubMed

[173] Joyce JN,

[174] Davis RE,

[175] Van Hartesveldt C

[176] ↵
Kravitz AV,
Freeze BS,
Parker PRL,
Kay K,
Myo T,
Deisseroth K,
Kreitzer AC
(2010) Control of basal ganglia circuitry. Nature 466:622–626. https://doi.org/10.1038/nature09159 pmid:20613723
OpenUrl CrossRef PubMed

[177] Kravitz AV,

[178] Freeze BS,

[179] Parker PRL,

[180] Kay K,

[181] Myo T,

[182] Deisseroth K,

[183] Kreitzer AC

[184] ↵
Marinelli M,
McCutcheon JE
(2014) Heterogeneity of dopamine neuron activity across traits and states. Neuroscience 282:176–197. https://doi.org/10.1016/j.neuroscience.2014.07.034 pmid:25084048
OpenUrl CrossRef PubMed

[185] Marinelli M,

[186] McCutcheon JE

[187] ↵
Masullo L,
Mariotti L,
Alexandre N,
Freire-Pritchett P,
Boulanger J,
Tripodi M
(2019) Genetically defined functional modules for spatial orienting in the mouse superior colliculus. Curr Biol 29:2892–2904.e8. https://doi.org/10.1016/j.cub.2019.07.083 pmid:31474533
OpenUrl CrossRef PubMed

[188] Masullo L,

[189] Mariotti L,

[190] Alexandre N,

[191] Freire-Pritchett P,

[192] Boulanger J,

[193] Tripodi M

[194] ↵
May PJ
(2006) The mammalian superior colliculus: laminar structure and connections. Prog Brain Res 151:321–378. https://doi.org/10.1016/S0079-6123(05)51011-2
OpenUrl CrossRef PubMed

[195] May PJ

[196] ↵
May PJ,
McHaffie JG,
Stanford TR,
Jiang H,
Costello MG,
Coizet V,
Hayes LM,
Haber SN,
Redgrave P
(2009) Tectonigral projections in the primate: a pathway for pre-attentive sensory input to midbrain dopaminergic neurons. Eur J Neurosci 29:575–587. https://doi.org/10.1111/j.1460-9568.2008.06596.x pmid:19175405
OpenUrl CrossRef PubMed

[197] May PJ,

[198] McHaffie JG,

[199] Stanford TR,

[200] Jiang H,

[201] Costello MG,

[202] Coizet V,

[203] Hayes LM,

[204] Haber SN,

[205] Redgrave P

[206] ↵
McHaffie J,
Jiang H,
May P,
Coizet V,
Overton P,
Stein B,
Redgrave P
(2006) A direct projection from superior colliculus to substantia nigra pars compacta in the cat. Neuroscience 138:221–234. https://doi.org/10.1016/j.neuroscience.2005.11.015
OpenUrl CrossRef PubMed

[207] McHaffie J,

[208] Jiang H,

[209] May P,

[210] Coizet V,

[211] Overton P,

[212] Stein B,

[213] Redgrave P

[214] ↵
Molochnikov I,
Cohen D
(2014) Hemispheric differences in the mesostriatal dopaminergic system. Front Syst Neurosci 8:110. https://doi.org/10.3389/fnsys.2014.00110 pmid:24966817
OpenUrl CrossRef PubMed

[215] Molochnikov I,

[216] Cohen D

[217] ↵
Moss MM,
Zatka-Haas P,
Harris KD,
Carandini M,
Lak A
(2021) Dopamine axons in dorsal striatum encode contralateral visual stimuli and choices. J Neurosci 41:7197–7205. https://doi.org/10.1523/JNEUROSCI.0490-21.2021 pmid:34253628
OpenUrl Abstract/FREE Full Text

[218] Moss MM,

[219] Zatka-Haas P,

[220] Harris KD,

[221] Carandini M,

[222] Lak A

[223] ↵
Nair-Roberts RG,
Chatelain-Badie SD,
Benson E,
White-Cooper H,
Bolam JP,
Ungless MA
(2008) Stereological estimates of dopaminergic, GABAergic and glutamatergic neurons in the ventral tegmental area, substantia nigra and retrorubral field in the rat. Neuroscience 152:1024–1031. https://doi.org/10.1016/j.neuroscience.2008.01.046 pmid:18355970
OpenUrl CrossRef PubMed

[224] Nair-Roberts RG,

[225] Chatelain-Badie SD,

[226] Benson E,

[227] White-Cooper H,

[228] Bolam JP,

[229] Ungless MA

[230] ↵
Pachitariu M,
Steinmetz NA,
Kadir S,
Carandini M,
Harris KD
(2016) Kilosort: realtime spike-sorting for extracellular electrophysiology with hundreds of channels. bioRxiv 061481:1–14. https://doi.org/10.1101/061481
OpenUrl

[231] Pachitariu M,

[232] Steinmetz NA,

[233] Kadir S,

[234] Carandini M,

[235] Harris KD

[236] ↵
Paxinos G,
Watson C
(2007) The rat brain in stereotaxic coordinates, Ed 6. Elsevier.

[237] Paxinos G,

[238] Watson C

[239] ↵
Peters AJ,
Fabre JMJ,
Steinmetz NA,
Harris KD,
Carandini M
(2021) Striatal activity topographically reflects cortical activity. Nature 591:420–425. https://doi.org/10.1038/s41586-020-03166-8 pmid:33473213
OpenUrl CrossRef PubMed

[240] Peters AJ,

[241] Fabre JMJ,

[242] Steinmetz NA,

[243] Harris KD,

[244] Carandini M

[245] ↵
Pradel K,
Drwięga G,
Błasiak T
(2021) Superior colliculus controls the activity of the rostromedial tegmental nuclei in an asymmetrical manner. J Neurosci 41:4006–4022. https://doi.org/10.1523/JNEUROSCI.1556-20.2021 pmid:33741724
OpenUrl Abstract/FREE Full Text

[246] Pradel K,

[247] Drwięga G,

[248] Błasiak T

[249] ↵
Redgrave P,
Coizet V,
Comoli E,
McHaffie JG,
Leriche M,
Vautrelle N,
Hayes LM,
Overton P
(2010) Interactions between the midbrain superior colliculus and the basal ganglia. Front Neuroanat 4:132. https://doi.org/10.3389/fnana.2010.00132 pmid:20941324
OpenUrl PubMed

[250] Redgrave P,

[251] Coizet V,

[252] Comoli E,

[253] McHaffie JG,

[254] Leriche M,

[255] Vautrelle N,

[256] Hayes LM,

[257] Overton P

[258] ↵
Sahibzada N,
Dean P,
Redgrave P
(1986) Movements resembling orientation or avoidance elicited by electrical stimulation of the superior colliculus in rats. J Neurosci 6:723–733. https://doi.org/10.1523/JNEUROSCI.06-03-00723.1986 pmid:3958791
OpenUrl Abstract/FREE Full Text

[259] Sahibzada N,

[260] Dean P,

[261] Redgrave P

[262] ↵
Solié C,
Contestabile A,
Espinosa P,
Musardo S,
Bariselli S,
Huber C,
Carleton A,
Bellone C
(2022) Superior colliculus to VTA pathway controls orienting response and influences social interaction. Nat Commun 13:817. https://doi.org/10.1038/s41467-022-28512-4 pmid:35145124
OpenUrl CrossRef PubMed

[263] Solié C,

[264] Contestabile A,

[265] Espinosa P,

[266] Musardo S,

[267] Bariselli S,

[268] Huber C,

[269] Carleton A,

[270] Bellone C

[271] ↵
Tai LH,
Lee AM,
Benavidez N,
Bonci A,
Wilbrecht L
(2012) Transient stimulation of distinct subpopulations of striatal neurons mimics changes in action value. Nat Neurosci 15:1281–1289. https://doi.org/10.1038/nn.3188 pmid:22902719
OpenUrl CrossRef PubMed

[272] Tai LH,

[273] Lee AM,

[274] Benavidez N,

[275] Bonci A,

[276] Wilbrecht L

[277] ↵
Takakuwa N,
Kato R,
Redgrave P,
Isa T
(2017) Emergence of visually-evoked reward expectation signals in dopamine neurons via the superior colliculus in V1 lesioned monkeys. Elife 6:e24459. https://doi.org/10.7554/eLife.24459 pmid:28628005
OpenUrl CrossRef PubMed

[278] Takakuwa N,

[279] Kato R,

[280] Redgrave P,

[281] Isa T

[282] ↵
Tecuapetla F,
Matias S,
Dugue GP,
Mainen ZF,
Costa RM
(2014) Balanced activity in basal ganglia projection pathways is critical for contraversive movements. Nat Commun 5:4315. https://doi.org/10.1038/ncomms5315 pmid:25002180
OpenUrl CrossRef PubMed

[283] Tecuapetla F,

[284] Matias S,

[285] Dugue GP,

[286] Mainen ZF,

[287] Costa RM

[288] ↵
Ungless MA,
Grace AA
(2012) Are you or aren’t you? Challenges associated with physiologically identifying dopamine neurons. Trends Neurosci 35:422–430. https://doi.org/10.1016/j.tins.2012.02.003 pmid:22459161
OpenUrl CrossRef PubMed

[289] Ungless MA,

[290] Grace AA

[291] ↵
Walczak M,
Błasiak T
(2017) Midbrain dopaminergic neuron activity across alternating brain states of urethane anaesthetized rat. Eur J Neurosci 45:1068–1077. https://doi.org/10.1111/ejn.13533
OpenUrl CrossRef PubMed

[292] Walczak M,

[293] Błasiak T

[294] ↵
Watabe-Uchida M,
Zhu L,
Ogawa SK,
Vamanrao A,
Uchida N
(2012) Whole-brain mapping of direct inputs to midbrain dopamine neurons. Neuron 74:858–873. https://doi.org/10.1016/j.neuron.2012.03.017
OpenUrl CrossRef PubMed

[295] Watabe-Uchida M,

[296] Zhu L,

[297] Ogawa SK,

[298] Vamanrao A,

[299] Uchida N

[300] ↵
Wilson JJ,
Alexandre N,
Trentin C,
Tripodi M
(2018) Three-dimensional representation of motor space in the mouse superior colliculus. Curr Biol 28:1744–1755.e12. https://doi.org/10.1016/j.cub.2018.04.021 pmid:29779875
OpenUrl CrossRef PubMed

[301] Wilson JJ,

[302] Alexandre N,

[303] Trentin C,

[304] Tripodi M

[305] ↵
Wise RA
(2004) Dopamine, learning and motivation. Nat Rev Neurosci 5:483–494. https://doi.org/10.1038/nrn1406
OpenUrl CrossRef PubMed

[306] Wise RA

[307] ↵
Yetnikoff L,
Cheng AY,
Lavezzi HN,
Parsley KP,
Zahm DS
(2015) Sources of input to the rostromedial tegmental nucleus, ventral tegmental area, and lateral habenula compared: a study in rat. J Comp Neurol 523:2426–2456. https://doi.org/10.1002/cne.23797 pmid:25940654
OpenUrl CrossRef PubMed

[308] Yetnikoff L,

[309] Cheng AY,

[310] Lavezzi HN,

[311] Parsley KP,

[312] Zahm DS

[313] ↵
Zhou Z, et al.
(2019) A VTA GABAergic neural circuit mediates visually evoked innate defensive responses. Neuron 103:473–488.e6. https://doi.org/10.1016/j.neuron.2019.05.027
OpenUrl PubMed

[314] Zhou Z, et al.

[315] ↵
Zimmerberg B,
Glick SD,
Jerussi TP
(1974) Neurochemical correlate of a spatial preference in rats. Science 185:623–625. https://doi.org/10.1126/science.185.4151.623
OpenUrl Abstract/FREE Full Text

[316] Zimmerberg B,

[317] Glick SD,

[318] Jerussi TP

[319] ↵
Zingg B,
Chou XL,
Zhang ZG,
Mesik L,
Liang F,
Tao HW,
Zhang LI
(2017) AAV-mediated anterograde transsynaptic tagging: mapping corticocollicular input-defined neural pathways for defense behaviors. Neuron 93:33–47. https://doi.org/10.1016/j.neuron.2016.11.045 pmid:27989459
OpenUrl CrossRef PubMed

[320] Zingg B,

[321] Chou XL,

[322] Zhang ZG,

[323] Mesik L,

[324] Liang F,

[325] Tao HW,

[326] Zhang LI

Main menu

User menu

Search

Superior Colliculus Controls the Activity of the Substantia Nigra Pars Compacta and Ventral Tegmental Area in an Asymmetrical Manner

Abstract

Significance Statement

Introduction

Materials and Methods

Animals

Brain injection surgeries

Anatomical experiments

In vivo electrophysiological experiments

Ex vivo electrophysiological experiments

Data analysis

Experimental design and statistical analysis

Code/software accessibility

Results

Anatomical lateralization of the innervation from the SC to the SNc and VTA

The SC stimulation activates neurons in the SNc and VTA in vivo

Stimulation of SC terminals within ventral midbrain ex vivo excites the ipsilaterally located neurons

Discussion

Footnotes

References

In this issue

Citation Manager Formats

Keywords

Responses to this article

Jump to comment:

Related Articles

Cited By...

More in this TOC Section

Research Articles

Systems/Circuits

Main menu

User menu

Search

Superior Colliculus Controls the Activity of the Substantia Nigra Pars Compacta and Ventral Tegmental Area in an Asymmetrical Manner

Abstract

Significance Statement

Introduction

Materials and Methods

Animals

Brain injection surgeries

Anatomical experiments

In vivo electrophysiological experiments

Ex vivo electrophysiological experiments

Data analysis

Experimental design and statistical analysis

Code/software accessibility

Results

Anatomical lateralization of the innervation from the SC to the SNc and VTA

The SC stimulation activates neurons in the SNc and VTA in vivo

Stimulation of SC terminals within ventral midbrain ex vivo excites the ipsilaterally located neurons

Discussion

Footnotes

References

In this issue

Citation Manager Formats

Jump to section

Keywords

Responses to this article

Jump to comment:

Related Articles

Cited By...

More in this TOC Section

Research Articles

Systems/Circuits