Dissecting the rewarding and motivational nature of social interaction: a role of ventral tegmental area dopaminergic activity

Thesis

Reference

Dissecting the rewarding and motivational nature of social interaction:

a role of ventral tegmental area dopaminergic activity

PREVOST-SOLIE, Clément

Abstract

Les interactions sociales sont des comportements hautement complexes qui nécessitent une adaptation constante à son environnement. Les neurones dopaminergiques (DA) de l'aire tegmentale ventrale (ATV) jouent un rôle majeur dans les processus de prises de décision, d'attribution de valeurs et de motivation en situation de récompense. Cependant leur implication dans les interactions avec un congénère reste encore incertaine. Dans cette étude nous investiguons l'activité DA de l'ATV chez la souris vigile pendant que celle-ci interagit avec un jeune congénère. Nous observons une augmentation de l'activité DA durant une interaction sociale libre. Pour mieux comprendre le rôle motivationnel d'une interaction sociale, une tâche de conditionnement opérant nous permet de quantifier la motivation de l'animal à interagir. Ainsi nous mettons en relief un apprentissage par renforcement conditionné par la simple interaction avec un congénère, ainsi que l'émergence d'une prédiction sociale encodée par les neurones DA. De plus, pour démontrer l'importance d'une activité DA de l'ATV intacte, à l'aide d'outils [...]

PREVOST-SOLIE, Clément. Dissecting the rewarding and motivational nature of social interaction: a role of ventral tegmental area dopaminergic activity. Thèse de doctorat : Univ. Genève et Lausanne, 2019, no. Neur. 248

Faculté des Sciences

DOCTORAT EN NEUROSCIENCES des Universités de Genève

et de Lausanne

UNIVERSITÉ DE GENÈVE FACULTÉ DES SCIENCES Professeure Camilla BELLONE, directrice de thèse

Professeur Ivan RODRIGUEZ, co-directeur de thèse

TITRE DE LA THESE

DISSECTING THE REWARDING AND MOTIVATIONAL NATURE OF SOCIAL INTERACTION : A ROLE OF THE VENTRAL TEGMENTAL

AREA DOPAMINERGIC ACTIVITY

THESE Présentée à la Faculté des Sciences de l’Université de Genève

pour obtenir le grade de Docteur en Neurosciences

par

Clément PRÉVOST-SOLIÉ de France

Thèse N° 248 Genève

Editeur ou imprimeur : Université de Genève 2019

Remerciements

Premièrement, je voudrais remercier tous les membres du laboratoire qui m’ont aidé à réaliser tous ces projets. Ainsi que pour leur gentillesse, les conversations scientifiques stimulantes et l’atmosphère plaisante au sein du laboratoire. Je n’oublie pas les anciens membres ainsi que les membres de mon ancien laboratoire à Paris.

J’aimerais aussi dire un énorme merci à tous mes amis qui m’ont énormément soutenu pendant toutes ces années. Le temps passé à vos côtés a été précieux pour relâcher la pression et engranger beaucoup de bons souvenirs. Je ne peux malheureusement pas tous les citer mais ils se reconnaîtront aisément, qu’ils soient à Genève, à Paris, dans l’Aveyron ou une autre région de France.

Un grand et doux merci à ma famille, spécialement à ma mère, ma grand-mère et Michel qui ont été d’un grand support pour moi.

Enfin, un grand merci à Camilla pour m’avoir accepté dans son laboratoire depuis presque 4 ans maintenant. Tu as été une merveilleuse mentor pour moi et j’ai énormément appris à tes côtés. Je suis fier et reconnaissant de faire parti de ton laboratoire et d’avoir partagé toutes ces années avec toi.

Résumé

Les interactions sociales sont des comportements hautement complexes qui nécessitent une adaptation constante à son environnement. Pour ce faire, l’attribution d’une valeur et d’une valence aux différentes situations sociales rencontrées est nécessaire afin d’aboutir à la réponse comportementale adéquate. Les neurones dopaminergiques (DA) de l’aire tegmentale ventrale (ATV) jouent un rôle majeur dans les processus de prises de décision, d’attribution de valeurs et de motivation en situation de récompense. Cependant son implication dans les interactions avec un congénère reste encore incertaine.

Dans cette étude nous investiguons l’activité DA de l’ATV chez la souris vigile pendant que celle-ci interagit avec un jeune congénère. Nous observons une augmentation de l’activité DA durant une interaction sociale libre alors que l’interaction avec un objet inanimé n’induit pas un tel changement. Pour mieux comprendre le rôle motivationnel d’une interaction sociale, nous avons développé une tâche de conditionnement opérant qui nous permet de quantifier la motivation de l’animal à interagir. Ainsi nous mettons en relief un apprentissage par renforcement conditionné par la simple interaction avec un congénère, ainsi que l’émergence d’une prédiction sociale encodée par les neurones DA. Ces résultats suggèrent donc des propriétés récompensantes et motivationnelles associées à l’interaction sociale.

De plus, pour démontrer l’importance d’une activité DA de l’ATV intacte, à l’aide d’outils chemogénétiques nous avons baissé l’excitabilité de ces neurones dans plusieurs tâches sociales. Nous relevons une baisse de l’exploration de la nouveauté sociale, mais aussi une abolition de la préférence pour la nouveauté

fournissent des entrées sur le Striatum Dorso-Lateral, et la stimulation optogénétique de cette voie, opposée au circuit ATV – Striatum Ventral, diminue l’interaction avec un congénère. Ce travail trace les contours d’un rôle précédemment insoupçonné de la voie CS – ATV dan le contrôle des comportements d’orientation pendant l’interaction sociale.

Finalement, les interactions sociales et la communication sont des aspects englobant du phénotype de l’autisme. De ce fait durant ma thèse, en utilisant deux modèles murins des Troubles du Spectre Autistique (TSA), j’ai exploré le circuit DA de l’ATV comme étant pertinent dans l’exploration des interactions sociales non-familières. Nos données suggèrent fortement que des altérations de l’activité des neurones DA de l’ATV peuvent sous-tendre les déficits sociaux dans les TSA.

Abstract

Social interactions are highly complex behaviors that adapt constantly to the environment. Attribution of a value and a valence to the different social situations is necessary to adopt an appropriate behavioral response. The ventral tegmental area (VTA) dopaminergic (DA) neurons play a main role in decision- making, values attribution and motivation in rewarding situations. However, their involvement in conspecific interaction remains unclear.

In this study we investigate the VTA DA activity in freely behaving mice during juvenile conspecific interaction. We observe an increase of VTA DA activity during free social interaction but not during object interaction. To better understand the motivational role of social interactions, we developed a conditioning operant task that allow us to quantify animal’s motivation to interact with conspecific. Thereby we highlight social-induced conditioned reinforcement learning, as well as the emergence of social prediction encoded by VTA DA neurons. Thus, these results suggest the rewarding and motivational properties associated with social interaction.

To demonstrate the importance of VTA DA activity, we used chemogenetic tools to decrease excitability during several social tasks. We reveal a decrease in social novelty exploration and an abolished preference to interact with a novel conspecific compare to a familiar social stimulus.

In order to understand how VTA DA neurons are modulated by different inputs during social interaction, we investigate the Superior Colliculus (SC) to VTA pathway. We show that this pathway is involved in conspecific interaction in mice. Specifically, we find that optogenetic manipulation of SC – VTA pathway

of Autism Spectrum Disorders (ASD), I have explored VTA DA circuit as relevant for the exploration of nonfamiliar conspecific interaction. Our data strongly suggest that alterations in VTA DA neuron activity underlie social deficits in ASD.

List of Abbreviations:

AAV: Associated Adeno-Virus AAVrg: AAV retrograde AC: Anterior Cortex

ASDs: Autism Spectrum Disorders

BOLD signal: Blood-Oxygen Level Dependent signal CaMKII: Ca²⁺/calmodulin-dependent protein kinase II ChR2: ChannelRhodopsin

CPA: Conditioned Place Aversion CPP: Conditioned Place Preference CS: Conditioned Stimulus

CTB 488: Cholera toxin subunit B Alexa Fluor 488 CTB 555: Cholera toxin subunit B Alexa Fluor 555 DA: Dopamine

DAT-Cre: Cre enzyme recombinase expressed under the promoter of Dopamine transporter DREADD: Designers Receptors Exclusively Activated by Designers Drugs

DS: lateral Dorsal Striatum FFA: Fusiform Face Area

GAD: Glutamic Acid Decarboxylase mRNA KO: Knockout

NAc: Nucleus Accumbens

mGluR: metabotropic receptor of glutamate PFC: Prefrontal Cortex

PSD: Post-Synaptic Density RPE: reward Prediction Error SC: Superior Colliculus

SNc: Substantia Nigra pars compacta TH: Tyrosine Hydroxylase

TS: Tail Striatum

US: Unconditioned Stimulus VTA: Ventral Tegmental Area

VGluT2: Vesicular Glutamate Transporter 2

TABLE OF CONTENT

Remerciements ... 1

Résumé ... 2

Abstract ... 4

List of Abbreviations: ... 7

Introduction I. Aim of the study ... 11

II. Social Behavior ... 12

A. How to define social behavior? ... 12

B. Study social behavior in mice ... 15

III. Dopamine ... 18

A. Ventral Tegmental Area: A Dopaminergic nucleus ... 18

B. Dopaminergic Activity ... 19

C. The Reward Prediction Error ... 20

D. Incentive Salience and Novelty ... 24

E. How sensory stimuli modulate DA neurons? ... 26

IV. The Autism Spectrum Disorders: a social pathology ... 28

A. Pathology in Human ... 28

B. Mouse model of ASDs: a synaptopathy ... 29

C. Dopamine hypothesis in sociability traits and ASDs ... 31

V. Questions, hypotheses and outline ... 35

Material & Methods Animals ... 37

Multi-unit recording system – Microdrive ... 37

Surgery ... 38

Optogenetic photolabeling of VTA DA neurons ... 40

Free social and object habituation task ... 41

Statistical analysis ... 52

Results I. VTA DA neuron activity increases during social interaction ... 55

II. Social interaction has intrinsic rewarding and motivational properties ... 61

III. Role of VTA DA neurons and neuroligin 3 in sociability traits related to nonfamiliar conspecific interaction ... 67

IV. Superior Colliculus sends mainly excitatory projections onto VTA DA neurons ... 105

V. Superior Colliculus to VTA pathway stimulation leads to social impairments ... 108

VI. VTA DA neurons receiving inputs from SC project to the lateral Dorsal Striatum ... 115

VII.VTA DA neuron activity is altered in Shank3 mice in social context ... 118

Discussion References

TABLE OF FIGURES

Figure 1: Social motivation hypothesis ... 14

Figure 2: Different social tasks ... 16

Figure 3: Reward system and VTA DA neurons ... 20

Figure 4: Activity of DA Neurons Complies with Formal Models of Reinforcement. ... 22

Figure 5: Reward and uncertainty ... 23

Figure 6: Reward and decision-making ... 24

Figure 7: VTA input and output ... 26

Figure 8: Post-synaptic density ... 31

Figure 9: Structural organization of VTA – NAc pathway in ASDs patients. ... 32

Figure 10: VTA DA neurons are involved in social interactions ... 34

Figure 11: Transformation of sensory inputs to social behavioral decisions ... 36

Figure 12: Recording electrode implantation and immunochemistry validation ... 55

Figure 13: Photo-labeling of VTA DA neurons recorded ... 56

Figure 14: VTA DA neuron activity increases during direct social interaction ... 57

Figure 15: VTA DA neuron activity increases during direct social interaction ... 59

Figure 16: VTA DA neuron activity increases during close social interaction ... 59

Figure 17: Social interaction promote motivated behaviors ... 62

Figure 18: Adaptation of VTA DA neurons during social operant task ... 64

Figure 19: Quantification of VTA DA neurons during social operant task ... 63

Figure 20: Anatomo-functionnal connectivity from SC to VTA DA neurons ... 107

Figure 21: SC – VTA pathway stimulation induces hyperlocomotion ... 108

Figure 22: SC – VTA pathway stimulation alters social preference and social novelty approach ... 110

Figure 23: Different social and non-social behaviors during free social interaction task 112 Figure 24: Stimulation of AC – VTA pathway increase social interaction ... 114

Figure 25: SC – VTA DA connected neurons project to DS. Stimulation of VTA DA – DS pathway induces similar social interaction alterations ... 117

Figure 26: VTA DA neuron activity is altered during social interaction in Shank3KO mice ... 119

Figure 27: VTA DA neuron activity is altered during close social interaction and at baseline level for Shank3KO mice ... 121

Figure 28: Shank3KO mice are impaired in social associative learning ... 121

Figure 29: Intrinsic excitability and Ih current of VTA DA cells are altered in Shank3KO mice ... 122

Introduction

I. Aim of the study

Animals, and more particularly mammals, have a broad range of specific and complex behaviors, but one of the most particular and difficult to study is certainly social behavior. Indeed, social interactions are highly complex and unpredictable behaviors. Every situation in a social context is different and individual needs to adapt constantly depending on the environment and on the output received from a conspecific.

Individual need to attribute appropriate values to the conspecific they are interacting to, in order to adapt their behaviors. Typically, we will not behave the same way if we are confronted to people we do not know, friends or work hierarchy. This social behavior adaptation still remains unclear, but one actor that plays a main role in all the decision-making processes, and allows us to attribute good values in function of our internal estimation and environment, is the dopamine (DA).

The aim of this thesis is to study the involvement of the DAergic activity in social interactions, and to investigate how deficits in DA neuron activity could contribute to social deficits in Autism spectrum disorders (ASD), a neuropsychiatric disease characterized by alterations in social behaviors.

Thus, in this study, using mice models with a global loss of the ASD-associated post-synaptic scaffolding protein Shank3 or synaptic-adhesion protein Neuroligin3, we will strengthen the link between DA and social behaviors. We will furthermore explore possible multisensory inputs that regulate DAergic activity during social interactions.

II. Social Behavior

A. How to define social behavior?

“In a broad sense, social behaviors can be defined as any modality of communication and/or interaction between two conspecifics of a given species and are observed in species as simple as single-celled microorganisms to species as complex as humans” ¹.

Behind the words “social behavior” is hiding a tremendous variety of behaviors associated to interaction with conspecifics of the same species.

Communication, cooperation, visual and auditory interactions, touching, planning, hierarchy, empathy, sexuality, aggression, reproduction, etc., all these behaviors can be linked to social, but are broadly different. That is why the social behavior is particularly difficult to characterize, and no consensus merged around a clear definition.

From an evolutionary point of view, social behavior is indispensable to perpetuate the continuity of species. Typically, sexual reproduction is a social behavior necessary for the survival of the species as well as parenting in the most of mammals. Aggression and combative behaviors are also social behaviors that aim to compete for communes’ resources between groups, still for species continuity ¹.

In humans, where social behavior is highly developed and complex, civilizations and societies are built around specific norms where every individual

us to develop a proper bounding with the parents. This bounding is highly important to the good evolution of the social skills and for the acquisition of high-function cognitive processes like language and reciprocal interactions ⁴. A lot of reported cases show how isolation can influence human-being development. More isolation happens early during the postnatal development, more important the deficits are ⁵. Typically, lack of social interaction can lead to anxiety, depression, troubles in language acquisition and communication ⁶. Social behaviors are then a key factor, in humans, to guarantee a good bio-psycho- ontogenesis.

Interestingly, the brain, through evolution, developed a specialized structure, the fusiform face area (FFA), known to be involved specifically in face recognition ^7,8, proving the particularity and the importance of social recognition in humans’ behaviors. This FFA allows us to recognize the emotional state of a congener to predict the behavioral output: in function of the valence, positive or negative, associated with facial/body expression, our strategy changes to adapt the behavior (escape, fight, approach).

Furthermore, the social motivation hypothesis claims that a social stimulus would promote interest to orient the behavior toward it: “At the proximal level, social motivation can be described as a set of psychological dispositions and biological mechanisms biasing the individual to preferentially orient to the social world (social orienting), to seek and take pleasure in social interactions (social reward), and to work to foster and maintain social bonds (social maintaining). At the ultimate level, social motivation constitutes an evolutionary adaptation geared towards enhancing the individual’s fitness in collaborative environments.” ⁹ (Figure 1).

Figure 1: Social motivation hypothesis

Social motivation would be constituted of three components with social orienting, social reward and social maintaining (from Chevallier et al., 2012 ⁹).

Typically, in humans and animal models, positive social behaviors are considered to induce approaches while negative social behaviors are considered to induce active avoidance or escape behavior. Generally, we are speaking about social reward when a social interaction is able to create a positive reinforcement, and social avoidance when it creates a negative reinforcement. In humans, the

B. Study social behavior in mice

Mice are a good model to study social behavior due to their gregarious instinct and the broad range of social traits we can extract from different behavioral paradigms. Moreover, the ease of manipulate the genome of mice is a high advantage to study different genetic disorders associated with social deficits.

The easiest paradigm to look at sociability traits in mice is the free social interaction test. In this task, two mice, an experimental and a stimulus, are placed in a cage to interact freely. Using software, it is possible to extract different syllables, manually or automatically, in scoring the different behaviors seen by the experimenters or the tracking algorithm ^11,12. This task allows to have a large view of social behavior, in free conditions, and to play with different stimuli to compare them (for example a social stimulus versus an inanimate object). It is also possible to repeat several times the exposure to the same social stimulus. Thereby, the experimental mouse remembers the previous exposures and gets habituated, reflected by a decrease of time interacting between the animals. Usually, after 4 exposures of the same stimulus mouse, called habituation phase, a novel animal is used for the 5^th social interaction (Figure 2).

This phase is named the dishabituation phase or novelty exploration phase, and the reaction to social novelty is reflected by an increased social interaction ¹³.

A well-known behavioral paradigm, broadly used in literature, is the three- chamber test (Figure 2). In this assay, the mice have first the choice to interact either with a conspecific or an inanimate object. The time spent around the stimuli will define the preference of the animal. In a second time, it is given the choice to the mice to interact either with a novel or a familiar social stimuli ^14,15. This task is particularly interesting to study the attractiveness of a social stimulus compare to a non-social stimulus and to assess the preference for the novelty associated with social stimuli. In several studies this test has been employed using different techniques such as calcium imaging ¹⁶, optogenetic ¹⁷ or pharmacological agents to test the influence on the social behavior ^18,19.

To study the reinforcing properties of social interactions, a specific protocol of social reinforcement learning has to be performed. Several paradigms of conditioned place preference (CPP) using social stimulus have been used in the literature. The principle is to associate a specific environment with a conspecific,

while another different environment is left empty. With repeated exposures between the environment and the social stimulus, the mice learn the association.

After the associative learning, the animals are free to explore both environments without any stimuli. The time spent in the different places is quantified to establish the place preference (Figure 2). Usually the mice prefers to spend time in environment associated with the social stimulus ^20,21. At the opposite, using a conditioned place aversion (CPA) paradigm, with an aggressive conspecific, the mice tend to avoid the chamber associated with the social stimulus ²². In both cases, this task proves that the social per se is able to induce reinforcement learning and can be either rewarding, if the social interactions are non- aggressive (positive valence, See Box Definitions), either aversive, if the social interactions are aggressive (negative valence). It is then important to adapt properly the paradigm used depending on which aspect of social behavior we want to study. Typically, the social defeat task is used to look at how the mice that underwent a strong aversive social experience are resilient or susceptible

23–26. Resilient animals are able to perform tasks as well as before the social defeat without behavioral alterations. Susceptible mice, as for them, present strong cognitive deficits after social defeat: they interact less with a conspecific, have depressive-like behaviors, increased anxiety, etc. Thereby, it becomes possible to characterize different cellular and physiological basis between mice that are susceptible or resilient and can be a good model to better understand humans’ pathologies linked with a post-traumatic stress disorder.

All these behavioral tasks allow dissecting the social behavior and to study the social deficits observed in some neuropathologies by using different mouse models. Moreover, new tools allow manipulating neuronal activity, such as chemogenetic, optogenetic, in-vivo imaging and recording, and are powerful to study the circuitry that may be involved in social behavior.

III. Dopamine

The complexity of social behavior, as exposed previously, is due to the high unpredictability and the broad range of different behaviors associated with the social interactions. The constant adaptation that has to be performed asks to attribute values to the different situations and actions the individual has to face off. Making prediction about the future situation allow updating these values depending on the expected environmental output. One main actor permitting the attribution of values and making prediction is dopamine (DA).

Box: Definitions

Value of a stimulus: The value is the strength of a stimulus. If a stimulus is strongly rewarding or aversive the value will be high, if a stimulus is neutral the value will be null. A subjective value essentially depends on the internal estimation of the subject.

Valence of stimulus: The valence can be positive or negative depending the rewarding or aversive properties of a stimulus. Typically a reward will get a positive valence while a negative valence will be associated with a punisher.

Saliency of a stimulus: The saliency is the distinct subjective quality which makes some items in the world stand out from their neighbors and immediately grabs our attention (Laurent Itti 2007).

Novelty of a stimulus: A stimulus that is novel is salient with a high value and promotes motivation to orient the attention toward this stimulus. The repeated exposure will decrease the novelty and the saliency depending on the stimulus strength.

DOPA, precursor of the DA. Approximately 30 % of the VTA neurons were positive for the Glutamic Acid Decarboxylase mRNA (GAD⁺), indispensable for the GABA synthesis, and only 2 – 3% were expressing the Vesicular Glutamate Transporter 2 (vGluT2), important for glutamate re-uptake ²⁷.

Anatomically, the medial terminal nucleus of the accessory optic tract (MT) is used as reference point to distinguish the medially located VTA neurons ^28,29 from the laterally located substantia nigra neurons ³⁰ (see review Bariselli et al., 2016 ³¹ for more details)

DA is a neuromodulator from catecholamine family secreted by the midbrain from three different nuclei: the Retrorubral Area, the substantia nigra pars compacta (SNc) and the ventral tegmental area (VTA). Recently, some DAergic have been identified in the Dorsal Raphe Nuclei, known to release mainly serotonin ³². The DA neurons from the midbrain project to different structures using three different pathways: the mesostriatal pathway which projects to the Dorsal and Ventral Striatum (Nucleus Caudatus, Putamen and Nucleus Accumbens), the mesolimbic pathway which projects to the Amygdala, the Septum and the Olfactory Tubercle, and the mesocortical pathway, which projects to the Prefrontal, Perirhinal and Cingulate Cortices ³³.

B. Dopaminergic Activity

It has been described, in anesthetized rats, that VTA DA neurons have two different firing patterns: a) Tonic activity, with a slow and regular emission of action potential in the range of 1 – 12Hz; b) Phasic activity, with a bursting emission of action potentials (Figure 3). Typically, a burst is starting when the inter-spike interval (ISI) is lower than 80msec, and is ending when the ISI is higher than 160msec ³⁴. In-vivo recording showed that a DA spike is characterized by a specific bi- or tri-phasic waveform with a half-width duration higher or equal at 1.1msec ³⁵. To be able to distinguish, in-vivo, the nature of the neurons recorded between DA and GABA, the VTA GABA neurons have different electrophysiological criteria. Typically, they are described like having a high

firing rate (> 15Hz) with a short-duration action potential without any bursting activity ^36–38 that makes clear differences with the VTA DA neuron activity.

The transition between the tonic and the phasic/bursting activity of the VTA DA neurons is highly important to allow the consolidation of a behavior, to process the reward consumption, make prediction and promote motivation.

Figure 3: Reward system and VTA DA neurons

Reward system emerging from VTA DA neurons. The VTA projects toward different structures but also receive excitatory and inhibitory inputs. The VTA DA neurons have two firing patterns of tonic

association, the salivation occurs during the cue presentation and not anymore during the reward consumption (the non-conditioned stimulus, here the tone, becomes conditioned stimulus). These results suggest strongly that the animals make a prediction about the future reward. This prediction would be biologically encoded and would allow an appropriate learning of the rules of the environment.

To explain this classical conditioning, known also as Pavlovian conditioning, some models were built to formalize, in a mathematical way, how the association is made between the CS and the US. One of the most famous is the Rescorla- Wagner model ⁴⁰, a model of classical Pavlovian conditioning, where the learning is explained exclusively as an association between the CS and the US. The strength of the learning depends on how the strength of the prediction about the US. This model, although criticized, has been used a lot due to the clear predictions that can be inferred, but had some failures that needed to adapt it.

The Temporal Difference learning (TD-learning), a generalization of the Rescorla-Wagner model, allows to predict the values associated to a stimulus depending on a specific signal. The TD-learning is then more powerful and accurate and is used in routine in the field of classical and instrumental learning.

To better understand how the role of DA neurons during a Pavlovian conditioning task, monkeys were implanted with a recording electrode in the midbrain (VTA and SNc). The animals were trained to associate a sensory cue (tone) with a reward (juice). Before learning, a phasic increase of VTA DA activity has been observed during the reward consumption (US) exclusively (Figure 4 A). After learning of this association, the phasic activity increases during the predictor stimulus (CS) and not anymore during the reward delivery, suggesting that the animals make a prediction (Figure 4 B). But, if the delivery of the reward is omitted, the phasic increase of VTA DA activity still occurs during the cue, and a tonic inhibition appears when the reward should have been consumed ⁴¹ (Figure 4 C). These results strongly suggest that the VTA DA neurons are encoding a reward prediction error (RPE) that is the difference in value between the actual reward and the expected reward. This study proves that TD-learning, more than a model, have a neuronal substrate and DA neurons

encode a specific learning (RPE), based on a constant update of the value predicted, computed as:

! = !−!(!)

Where !is the reward prediction error, R the actual reward and V(t) the expected value of the reward. This value is constantly updated at each trial to adapt the behavior and allow an appropriate response to a situation. The reinforcement learning theory postulate that this RPE is a learning signal of the actions’ values leading to the reward ⁴²: the value of a stimulus or an action bringing more reward than expected (positive RPE) would be increased, while a negative RPE would decrease the value of the stimulus or the associated action (depending of the learning speed !):

! !+! = ! ! +!"

Figure 4: Activity of DA Neurons Complies with Formal Models of Reinforcement.

The TD-learning is able to model a RPE that would be encoded by the DA neurons. (A) Before learning the DA phasic increase occurs during the reward delivery, (B) while after learning this phasic increase occurs during the cue (C). A reward omission leads to DA inhibition when the

increase (prediction) is following the probabilistic values associated to the reward monotonically. Interestingly, the VTA DA tonic activity would encode, instead of the value, the uncertainty associated to a reward. Using probabilities to obtain a reward, it is then possible to modulate the uncertainty intensity.

Thereby, the VTA DA tonic activity is following a parabolic increase linked with the mathematical increase of the uncertainty, to reach the maximum at 50% of reward delivery (maximum uncertainty, Figure 5) ⁴⁵.

Figure 5: Reward and uncertainty

Expected reward (prediction) and Expected Uncertainty as a function of reward probability delivery. While the prediction is encoded by the phasic increase of VTA DA neurons and follows a monotonic slope, the uncertainty is encoded by tonic activity and follow a parabolic function (copied from Naudé et al., 2016 with authorization⁴⁶).

In several studies, it has been shown that the VTA DA neurons are following the rules of reinforcement learning model. Typically, the mathematical link between the prediction and the RPE is robust and well physiologically encoded

47–50. However, not all the VTA DA neurons are responding according the RPE concept, showing the heterogeneity of DA population within the VTA.

Interestingly, when animals have the choice between different rewarding stimuli (typically two different juices with two different flavors), the subjective value they attribute to the reward, depending on the internal estimation state and their preference, will trigger the intensity of the RPE ⁵¹. But this subjective value, more than self-reward estimation, can also depend on partner-reward estimation. Typically, in a social Pavlovian conditioning task, two monkeys are placed in face to face with a monitor showing two different cues, one predicting the self-reward probability and the other one the partner-reward probability.

Importantly, one reward is kept constant for one monkey while the other is varying for the second animal. Interestingly, looking at the licking rate to

consume the reward, the authors show that the subjective value of the reward depends on the social context, whereas the objective value of the reward remains exactly the same across the trials ⁵².

Figure 6: Reward and decision-making

(A) Schema of identification of a reward. Typically a broad range of processes has to occur to react properly to a reward. The sensory components are important to identify a reward as a reward. The saliency and the novelty are necessary to promote the attention and to orient toward the stimulus.

The value will allow a good motivation to consume the reward. Once processed, the behavioral outcome is adapted to the environmental input. (B) “Feedback circuit diagram for prediction updating by error. An error is generated when outcome (reward, punisher) differs from its prediction.” (from Schultz, 2015⁵³).

D. Incentive Salience and Novelty

The value and the valence associated to a stimulus would be two properties developing the saliency of an object or a situation. Typically, as shown previously, the VTA DA phasic activity increases when the animal consumes a reward (positive valence and high value) and decreases when the mouse receives an aversive stimulus such as an air-puff (negative valence and high value) ^56,57. Here, the VTA DA activity follows the valence associated to the stimulus (increase or decrease) and modulated according the value (intensity of the variation). Interestingly, another subpopulation of VTA DA neuron activity is increased both during reward consumption and aversive stimulus. This subpopulation of DA neurons reacts to the saliency associated to a stimulus and not anymore to the valence ⁵⁸. These results show the heterogeneity of the VTA DA neurons responses to a stimulus depending on its properties: the value and the valence typically.

The novelty associated to a stimulus, independently of its nature, is also a fundamental parameter that drives the VTA DA neuron activity. Indeed, as a stimulus, a non-predictable opening of a door is able to induce a phasic activity of DA at the level of the VTA ⁵⁹. Interestingly, this increase activity is observable during the firsts opening of the door, when the event is novel, and disappears across time with the repeated exposure, showing a habituation in the VTA DA activity. The novelty is a key concept to understand how an animal is able to adapt rapidly to a situation; the novelty induces the exploration to gain information to understand the laws governing the environment. Several studies in humans show an increase of BOLD signal in fMRI, at the level of the midbrain (VTA/SNc), when the individuals have to process novelty during a task, instead of familiar events ^60,61.

Kakade and Dayan ⁶² suggested that novelty would be a bonus associated to a reward. The novel aspect of stimulus would promote an interest and would add a value to the stimulus. This bonus would decrease with the time and repeated exposures, and would promote the learning, the exploration and the exploitation of a reward ⁵³.

E. How sensory stimuli modulate DA neurons?

The VTA is an important structure that sends projections in several targeted regions. The specific physiology of DA neurons plays a major role and allows explaining how a restricted region as the VTA can have a main influence in a broad range of behaviors. But how these VTA DA neurons are modulated is also a key component to understand what kind of information they receive and how they process them. VTA DA neurons receive mainly excitatory and inhibitory monosynaptic inputs that have been mapped using a retrograde transsynaptic virus coupled with a DAT-Cre/loxP system ⁶³. For more details about inputs and outputs of the VTA DA neurons, consult the review Bariselli et al., 2016 ³¹ (Figure 7).

Figure 7: VTA input and output

Excitatory and inhibitory inputs projecting to the VTA DA neurons. This modulation is highly important because the VTA DA neurons project to main structures involved in reward processing, but also in social behaviors (copied from Bariselli et al. 2016 with authorization

31).

One main interest remains how the environmental sensory cues are able to

Although there is no direct evidence of a connection between the Superior Colliculus and the VTA, a direct pathway between the Superior Colliculus and the SNc has been established ^67,68. While the midbrain DA neurons do not receive inputs from sensory cortex, the Superior Colliculus would be a good candidate to explain how midbrain DA neurons respond to sensory cues. Indeed, the Superior Colliculus is a multisensory integration structure that receives auditory and visual input mainly ^69–71. Due to this integration, this structure is then highly involved in attention and decision making task ⁷². Furthermore, it has been hypothesized that the Superior Colliculus would encode a visual saliency map of the environmental scene ⁷¹.

Interestingly, the Superior Colliculus is involved in a lot of common processes with the midbrain DA neurons, and the short-latency activity contingency between these structures during sensory stimulation lets think to a tight connection between them.

However, the Superior Colliculus to VTA DA neurons projections have been poorly described contrary to the projections onto SNc DA neurons. Thereby, how the Superior Colliculus projections modulate the VTA DA neurons could be interesting, especially in a social context.

IV. The Autism Spectrum Disorders: a social pathology

Autism spectrum disorders (ASDs) are neurodevelopmental disorders that affect several aspects of the behavior, more specifically the sociability traits and communication with congeners. The term ASDs regroups a high variability of symptoms and deficits associated with autism, that is why it is still tricky to categorized clearly the different forms.

A. Pathology in Human

The Diagnostic and Statistical Manual for Mental Disorders (DSM-V, 5^th edition, American Psychiatric association, 2013) reorganized the diagnosis criteria of the autism compare to the DSM-IV. Typically, now the term ASDs includes: the autistic trouble, Asperger syndrome, pervasive development disorders and childhood disintegrative disorder. The DSM-V also includes a new diagnostic, social communication trouble, for people having deficits in verbal and non-verbal communication but without any stereotypy.

To establish a diagnosis of ASDs, doctors based on the following criteria:

- Persistent deficits in communication skills and social interactions in multiple contexts.

- Repetitive and restrain modes of behaviors, interests or activities.

- Symptoms have to be present in the early phase of development.

- Symptoms lead to a significant clinical alteration of actual functioning in social domains, scholar or professional, or other important domains.

presents in 40 – 55% of ASDs patients. In addition, some others medical and neurological symptoms, such as gastro-intestinal deficits or sleep disturbances, may appear in 10% of ASDs patients ⁷³.

Some psychotherapeutic technics can improve the symptoms in ASDs patients. Typically, the ABA (Applied Behavioral Analysis) intervention is based on strong reinforcement learning associated with reward ⁷⁴. Although this psychotherapy is efficient for a part of ASDs patients, the specialized psychologists are rare and its cost is high.

A pharmacological approach does not exist yet and is challenging to emerge due the broad list of symptoms. However, ASDs patients have a lack of motivation to interact socially, and it has been hypothesized that they would express a default in reward value attribution of social interaction ⁷⁵, react less to social reward ⁷⁶ and would get a disorder of prediction ⁷⁷. As shown previously, DAergic neurons is an important actor for these attributions and predictions and, thereby, would be a good target for a future pharmacological treatment especially since Risperdone, a D2 antagonist, has been shown to enhance social deficits ^78,79.

Several forms of ASDs are known to have molecular and genetic basis.

Importantly, in monozygotic twins it exists 88% of concordance and 31% for dizygotic twins ⁸⁰. Thereby, animals’ models may help to understand better the cellular, physiological and behavioral dysfunctions of ASDs patients.

B. Mouse model of ASDs: a synaptopathy

Many genes involved in certain forms of ASDs are encoding synapses proteins, suggesting that ASDs would have a common feature based on a synaptic level ⁸¹ characterizing ASDs as a synaptopathy ^82,83. Among these genes we find two mains family such as NEUROLIGINS with the Neurexins complex, and SHANKs family. These genes are encoding proteins that are respectively scaffolding proteins and synaptic adhesion proteins that are indispensable for the normal development of the synapse ^84,85. More specifically, in these families of genes, two are particularly important and involved in specific forms of ASDs.

First, the SHANK3 gene is encoding the scaffolding protein SHANK3 that is present in the post-synaptic density (PSD). The haploinsufficiency of SHANK3 gene has been associated with a specific form of ASDs known as the Phelan McDermid Syndrome, which consist of a deletion in the distal region of the chromosome 22, 22q13.3 ⁸⁶. This SHANK3 mutation is present in 0.5% of ASDs patients and it is one of the most common genetic causes in ASDs ⁸⁷.

Interestingly, in-situ hybridization showed that the mRNA of SHANK3 increases after P16, showing that the synapse is following a progressive development in its cohesion suggesting the neurodevelopmental aspect of ASDs

88. Moreover, different genetic models of Shank3 Knock-out (KO) mice show different alterations, specifically at a social level such as social novelty recognition, but also in others behaviors such as anxiety or self-grooming, showing stereotypical behaviors in these mice ^85,89,90. Thereby, the Shank3 KO mouse model represents a good tool to study the cellular and physiological basis underlying the deficits in ASDs.

Neuroligin3 is a gene encoding a post-synaptic adhesion protein that allows a good cohesion of the synapse. It has been identified as a category 2 (strong candidate) classified ASD-linked gene (http://gene.sfari.org) ^91–93. The global loss of Neuroligin3 gene (Nlgn3 KO) in mice induces a reduced ultrasonic vocalization and social memory in male-female interactions ^94,95, but also alterations in general social behaviors ⁹⁶. Furthermore, these mice are presenting motors dysfunctions with an increase locomotors activity and repetitive behavior ⁹⁷. In a study with 2 patients from the same family presenting

important to modulate specifically the neuronal targets hypothesized to be important in ASDs, such as the DA neurons.

Figure 8: Post-synaptic density

Schematic of the post-synaptic density with the scaffolding protein SHANK3 and adhesion protein NGL3 (copied from O’Connor et al., 2014 with authorization⁹⁹).

C. Dopamine hypothesis in sociability traits and ASDs

Several neuropathologies are known to involve the midbrain DAergic system like Parkinson disease or Schizophrenia ^101–103. While Parkinson is a neurodegenerative disease, schizophrenia is a neurodevelopmental pathology involving mutations that can be found in ASDs in some cases. In schizophrenic patients, several social deficits have been noticed ¹⁰⁴ and grouped as a part of negative symptoms. The link between the DA activity and this psychiatric disorder is established since a while. Naturally the DA hypothesis concerning the social traits has emerged and scientists started to think the social interactions as rewarding ^105–107.

In humans, a recent study shows that the typical development of the VTA-NAc pathway is altered in ASD patients ¹⁰⁸. The preserved integrity of the connection between these two structures would be correlated with the severity of social

deficits: weaker is the pathway, more severe are the deficits (Figure 9 A, B & C).

As shown previously, this pathway, one of the main DAergic output from the VTA, plays an important role to make association between two stimuli and make prediction about a future event. The predictions are highly important to adapt properly a behavior to a situation and even more in social conditions. One study used a computational model to explain ASDs as a disorder of prediction ⁷⁷. The authors, based on DSM-IV, used criteria to diagnose ASDs (language processing, social interactions, and behavioral repertoire) to build a model of Markovian decision process. A Markov system is evolving with the time and is linked by transition probabilities between the different modalities. In this study, the authors say the ASDs patients would have a problem to manage the different probabilities of the different transitions states by a lack of prediction. Thereby, the detection of inter-event relationship would be affected, especially in social skills, creating deficits in social behaviors.

In mice, when the VTA DA neuron activity is perturbed using optogenetic, social behaviors change. While the increase of VTA DA activity, using Channel Rhodopsin (ChR2), increase the time spent interacting with a conspecific (Figure 10), the inhibition (using HaloRhodopsin) of the VTA DA activity decreases the social interaction. Interestingly, the manipulation of the VTA DA neurons using optogenetic does not modify the interaction with an inanimate object ¹⁶. Moreover, in the same study, the authors show an increase of the calcium waves in the VTA when the animals are in the social chamber during the three- chambered task. These results highlight the importance of the VTA DA activity during social behaviors.

To further link the VTA DA neuron activity with neurodevelopmental pathology like ASDs, Bariselli, Tzanoulinou et al. ¹⁷ downregulated specifically Shank3 in the VTA, using a short hairpin RNA (Sh-RNA). Mice expressing this Sh- RNA, specific for Shank3, show an alteration in social interaction, with a decrease of time sniffing the conspecific during the three-chambered task. Interestingly, at a synaptic level, the VTA DA neurons expressing the Sh-RNA have an increase of the rectification index (RI), a proxy of the presence of the Calcium-permeable AMPA receptors lacking the GluA2 subunit (GluA2-lacking AMPARs). This increase of RI is conjointly linked with an increase of the AMPA/NMDA ratio, showing the importance of the excitatory inputs onto VTA DA neurons to express an appropriate social behavior. Moreover, in anesthetized mice, this down- regulation of Shank3 in the VTA leads to a decrease in the burst firing rate of VTA DA neurons, and an increased firing rate of the VTA GABA neurons. Importantly, the injection of a positive allosteric modulator (PAM) of metabotropic receptor of glutamate 5 (mGluR5), known to promote the removal of GluA2-lacking AMPARs when there are activated, is able to rescue the synaptic alterations and the phenotype of the mice.

Moreover, VTA DA neuron activity is modified during aversive social experiences, such as aggression ¹⁰⁹. In a context of sub-threshold social defeat task, the optogenetic perturbation of the VTA-NAc pathway is able to change the phenotype of the mice. Typically, while a stimulation of this projection induces a susceptible phenotype to aversive social stimulus, inhibition allows the emergence of a resilient phenotype. Interestingly the stimulation of the VTA- mPFC pathway does not induce any behavioral changes ²⁴.

Altogether, these findings reveal and strengthen the importance of the VTA DA neuronal population in social behaviors and in ASDs.

Figure 10: VTA DA neurons are involved in social interactions

(A) Schema of optic fiber placement and infection with the DIO-ChR2-eYFP in the VTA DA neurons using TH-Cre mice. (B) Pictures of infection with the ChR2 and optic fiber placement. (D) Schema of the direct social interaction task using optogenetic stimulation with ChR2 or inhibition with NpHR.

The animals are interacting during 2 mins while the experimental mouse is receiving optogenetic modulation. (E) There is an increase of social interaction when the VTA DA neurons are stimulated while there is a decrease when the VTA DA neurons are inhibited (from Gunaydin et al., 2014¹⁶).

V. Questions, hypotheses and outline

How VTA DA activity is involved in social interactions is still unclear and need further investigations. To this aim, we will use in-vivo recording in freely behaving mice to record the VTA DA neuron activity during free and direct social interactions in DAT-Cre mice (to target specifically VTA DA neurons using opto- photolabeling). We will also look at the VTA DA activity during free interaction with an inanimate object, as a control, to investigate the specificity of the social stimulus. Interestingly, we developed a specific task based on social reinforcement learning that will allow investigating the rewarding and motivational aspects of social stimuli.

We then hypothesized that the DAergic activity is a main actor underlying social behaviors. That is why, in this study, we will modulate the VTA DA activity, using several tools such as chemogenetic (inhibitory DREADD) and optogenetic (ChannelRhodopsin), during social tasks. We will focus our attention how the novelty, strongly salient, can influence the attraction to a social stimulus. For this, we developed and adapted specific social tasks to investigate the social novelty recognition, preference and learning. To strongly link the VTA DA activity with ASDs, we will use a specific model of Nlgn3 KO but also an Associated Adeno-Virus (AAV) using the Cre-lox system in DAT-Cre mice to specifically down-regulate the Nlgn3 gene in VTA DA neurons. Furthermore, we will investigate the synaptic plasticity associated to social novelty and social learning, at excitatory synapses of DA neuron.

We then hypothesized that the environmental sensory inputs integrated by the Superior Colliculus, which is a multisensory integration structure, would play a major role especially during social interactions due to the high complexity of social stimuli. Using optogenetic constructs, we will identify a new pathway between the Superior Colliculus and the VTA, and we will highlight the role of this circuit during social behaviors. Thereby, the Superior Colliculus would encode the social multisensory cues and would modulate the VTA DA neuron activity to adapt the behavior to express appropriate social decision-making.

Finally, exploring the VTA DA activity in a model of ASDs, as the Shank3 KO mice will allow to strengthen the link between the social deficits and an altered VTA DA neuron activity. For this, we will repeat the free interaction task using in- vivo recording in freely behaving Shank3 KO mice and will perform the social operant task to look at the alteration in social motivation and social reward.

Figure 11: Transformation of sensory inputs to social behavioral decisions

The multi-sensory inputs are processed and integrated, in social condition. Depending the internal states and estimation, a social decision-making will be made to adopt the proper social behavior depending the environmental situation (from Chen et al., 2018¹).

Material & Methods

Animals

The study was conducted using WT and transgenic mice with C57BL/6J background. WT mice were obtained from Charles River. For DA neuron-specific manipulations DAT-iresCre (Slc6a3tm1.1(cre)Bkmn/J, called DAT-Cre in the rest of manuscript) were employed. Shank3KO mice were previously described¹¹⁰. Only males’ animals were used for all the experiments conducted. Mice were housed in groups (weaning at P21 – P23) or isolated, depending the different experiments, under a 12 hours light – dark cycle (7:00 a.m.–7:00 p.m.). All physiology and behavior experiments were performed during the light cycle. For Shank3KO, WT and DAT-Cre mice, multiple behavioral tests were performed with the same group of animals, with a minimum of 7 days in-between tests. All the procedures performed at UNIGE complied with the Swiss National Institutional Guidelines on Animal Experimentation and were approved by the respective Swiss Cantonal Veterinary Office Committees for Animal Experimentation.

Multi-unit recording system – Microdrive

The VTA DA neurons recording is realized thanks to 2 octrodes, each constituted of 8 Nickel-Chrome (NiCr) coated wires of 15µm diameter. The octrodes are inserted in a homemade microdrive composed of a central piece containing a cannula as guide and a connector (Electrode interface board EIB) where the recording and amplifier cable will be plugged. The central piece has a moving part allowing the depth modulation thanks to a micro-screw after implantation. The cannula receives the 2 octrodes and an optic fiber that are glued together and will be implanted at the same time with a difference of 200 – 500µm between the tips of the octrodes and the optic fiber. Once the ensemble mounted, the impedance is uniformed (≈ 300 kOhms) at the octrodes tips with a

diluted gold plating in a polyethylene glycol (C2H4O) solution.

The neuronal activity was recorded using Digital Lynx 4SX acquisition system, with 32kHz sampling rate (Neuralynx). A high band-pass filter (600Hz – 6000Hz) was applied during the recording to extract the fast electrical impulsions (the spikes).

Surgery

In-vivo electrophysiology experiments:

Injection of rAAV5-Ef1α-DIO-hChR2(H134R)-eYFP was performed in DAT-Cre mice at 4–7 weeks. For additional information on optogenetic viral vectors see virus part in Methods. Mice were anesthetized with a mixture of oxygen (1 L/min) and isoflurane 3% (Baxter AG, Vienna, Austria) and placed in a stereotactic frame (Angle One; Leica, Germany). The skin was shaved, locally anesthetized with 40–50 µL lidocaine 0.5% and disinfected. Unilateral craniotomy (1 mm in diameter) was then performed over the VTA at following stereotactic coordinates: ML ± 0.5 mm, AP −3.2 mm, DV −4.20 ± 0.05 mm from Bregma. The virus was injected via a glass micropipette (Drummond Scientific Company, Broomall, PA) into the VTA at the rate of 100 nl/min for a total volume of 500 nL. The implantation of the homemade Microdrive (see previous part) was then performed 2 weeks later using the same coordinates. Unilateral craniotomy was made above the VTA and bilateral craniotomy above the cerebellum to implant references wires. The Microdrive was then fixed on the skull using dental acrylic.

craniotomy was made over the Superior Colliculus (SC) at the following stereotactic coordinates: ML ± 0.8 mm, AP -3.4 mm, DV −1.5 mm from Bregma, for a total volume of 500 nL for each side. For the Anterior Cortex (AC), bilateral injections were performed, at 4 different sites, at the following coordinates: ML ± 2.2 mm, AP +2.1 mm, DV −2.1 mm from Bregma, 300 nL each side, and ML ± 0.3 mm, AP +1.95 mm, DV −2.1 mm, 200 nL each side. Injections sites were confirmed post hoc by immunostaining on SC. The virus was incubated for 3–4 weeks and subsequently mice were implanted with optic fibers above the VTA.

The animals were anesthetized, placed in a stereotactic frame, the skin was shaved and a unilateral craniotomy was performed as previously described. The optic fiber was implanted with a 10° angle at the following coordinates: ML ± 0.9 mm, AP −3.2 mm, DV −3.95 ± 0.05 mm from Bregma above the VTA and fixed to the skull with dental acrylic.

For optogenetic experiments using DAT-Cre mice, the animals were injected with rAAV5-Ef1α-DIO-hChR2(H134R)-eYFP or rAAV5-Ef1α-DIO-eYFP in the VTA. The animals were anesthetized, placed in a stereotactic frame, the skin was shaved and bilateral craniotomies were performed as previously described. The virus was incubated for 3–4 weeks and subsequently mice were implanted with optic fibers above either the Nucleus Accumbens (NAc) with 15° angle at the following coordinates: ML ± 2.0 mm, AP +1.2 mm, DV −4.2 mm from Bregma ;or the lateral Dorsal Striatum (DS) at the following coordinates: ML ± 2.0 mm, AP +1.0 mm, DV −2.5 mm from Bregma. The optic fibers were then fixed using dental acrylic.

For ex-vivo electrophysiological recording experiments, injections of AAVrg- pCAG-FLEX-tdTomato-WPRE and rAAV5-hSyn-hChR2(H134R)-eYFP were performed in DAT-Cre mice. The animals were anesthetized, placed in a stereotactic frame, the skin was shaved and bilateral craniotomies were performed as previously described. rAAV5-hSyn-hChR2(H134R)-eYFP was first injected in the SC at the same coordinates previously described and then the AAVrg-pCAG-FLEX-TdTomato was bilateraly injected either in the NAc at these coordinates: ML ± 1.0 mm, AP +1.2 mm, DV −4.4 / −4.0 mm from Bregma, 500 nL each side; either the DS at following coordinates: ML ± 2.0 mm, AP +1.0 mm, DV

−2.8 mm from Bregma, 500 nL each side; or the Tail Striatum (TS) at these coordinates: ML ± 3.2 mm, AP −1.75 mm, DV −2.1 mm from Bregma, 500 nL each

side. The viruses were incubated 3 – 4 weeks before to perform ex-vivo electrophysiological recordings. rAAV5-hSyn-hChR2(H134R)-eYFP was also injected in the SC in WT mice as described above at the same coordinates.

For anatomical validation experiments, bilateral injections of rAAV5-hSyn- eYFP in the SC were performed as described above. The virus was incubated 3 – 4 weeks before immunostaining procedures. CAV-2 Cre and rAAV5-hSyn-DIO- mCherry were injected in WT mice. The mice underwent the same surgical procedure, as described above, and the CAV-2 Cre was bilaterally injected in the VTA at the following coordinates: ML ± 0.5 mm, AP −3.2 mm, DV −4.20 ± 0.05 mm from Bregma, 500 nL each side. Then the rAAV5-hSyn-DIO-mCherry was bilaterally injected in the SC at the same coordinates described previously. The viruses were incubated 3 – 4 weeks prior immunostaining experiments.

Finally, WT mice were bilaterally injected using Cholera Toxin subunit-B Alexa fluor 555 (CTB 555) or CTB 488 respectively in the DS (ML ± 2.0 mm, AP +1.0 mm, DV −2.8 mm from Bregma, 200 nL each side) and the NAc (ML ± 1.0 mm, AP +1.2 mm, DV −4.4 / −4.0 mm from Bregma, 200 nL each side). The CTB 488 and CTB 555 were incubated during 2 weeks before immunostaining procedures.

Optogenetic photolabeling of VTA DA neurons

DAT-cre mice injected with AAV-DIO-ChR2 and implanted with the Microdrive underwent the optogenetic protocol to validate the DAergic nature of the neuron. When a recorded neuron was suspected to be DA, based on the