• Aucun résultat trouvé

VTA DA neuron activity is altered in Shank3 mice in social context

C. Dopamine hypothesis in sociability traits and ASDs

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

Based on all our previous data, we hypothesized that deficits in VTA DA neuron activity could underlie aberrant social behavior in Shank3KO mice. To test our hypothesis, we performed direct social interaction task with conspecific, while recording in-vivo the VTA DA neuron activity (Figure 26. A-C).

Shank3KO mice presented a habituation in time sniffing the conspecific when repeatedly exposed to the stimulus (Figure 26. D). Nevertheless, the behavioral phenotype seemed different from the control DAT-Cre mice. (Even though the good control to compare would be WT mice littermate, we will use the data from the DAT-Cre mice previously presented). Indeed, when comparing the %time sniffing, Shank3KO mice spent less time interacting with a conspecific compared to the DAT-Cre mice at every trial (Figure 26. E). These results suggest that the Shank3KO mice have less interest in approaching a conspecific.

Interestingly, during direct interaction, we did not observe an overall increase in DA neuron spontaneous frequency in Shank3 KO mice (Figure 26. F-H).

However, isolating the % of spike within the burst (SWB), we observed an increased bursting activity during social interaction (Figure 26. H).

Moreover, we observed a lower proportion of HFHB neurons compare to DAT-Cre mice (DAT-Cre: 31.8% HFHB at baseline – 54.5% HFHB during social / Shank3KO: 19.4% HFHB at baseline – 32.3% HFHB during social; Figure 26. I).

During nose-to-nose contact, VTA DA activity increases only during the 1st trial, (Figure 27. A-D). Finally, we observed a decrease of VTA DA activity during

nose-Figure 26: VTA DA neuron activity is altered during social interaction in Shank3KO mice (A) Schema of the free social interaction. (B) Experimental protocol of the task from the surgery to implant and record VTA DA neurons to the behavior. (C) Example traces of VTA pDA neuron under baseline and social interaction conditions. (D) Time sniffing the social stimulus during the free interaction task for the three different trials. Repeated measure (RM) one-way ANOVA (Time main effect: F(2,13) = 17.9472, P < 0.0001) followed by Bonferroni-Holm post-hoc test correction. (E) Comparisons of %time sniffing between DAT-Cre (control) and Shank3KO mice during the 3 social trials. RM two-way ANOVA (Time (trials) main effect: F(2,30) = 36.1465, P < 0.0001; Genotype main effect: F(2,30) = 15.9287, P = 0.0004; Interaction Time x Genotype: F(2,30) = 1.0554, P = 0.3544) followed by Bonferroni-Holm post-hoc test correction. (F) VTA DA neuron activity normalized during the three baseline and social conditions. RM one-way ANOVA (Time main effect: F(5,30) = 1.0102, P = 0.4138) followed by Bonferroni-Holm post-hoc test correction. (G) Difference of normalized VTA DA activity between social and baseline condition for DAT-Cre and Shank3KO mice,

during the 3 trials. RM two-way ANOVA (Time (trials) main effect: F(2,52) = 2.2271, P = 0.1130;

Genotype main effect: F(2,52) = 9.1643, P = 0.0038; Interaction Time x Genotype: F(2,52) = 1.3205, P = 0.2714). (H) Left: VTA DA neuron spontaneous frequency averaged for the three baseline and three social trials respectively. Paired t test (t(30) = -1.4856). Right: VTA DA neuron bursting activity averaged for the three baseline and three social trials respectively. Paired t test (t(30) = -4.5164). (G) Time sniffing the object stimulus during the free interaction task for the three different trials.

Repeated measure (RM) one-way ANOVA (Time main effect: F(2,15) = 4.7534, P = 0.0161) followed by Bonferroni-Holm post-hoc test correction. (I) Different VTA DA patterns depending of the spontaneous frequency and the %SWB for baseline activity (Left) and during social interaction (Right), with the proportion of the patterns during the 2 different conditions. N,n indicate number of mice and cells respectively. Errors bars report s.e.m.

To assess the social motivation in Shank3KO mice, we performed the operant social task previously described (Figure 28. A). DAT-Cre mice learn the association between the lever-press and the door opening to interact with a novel conspecific (as shown previously). However, Shank3KO mice present a dramatic deficit in the associative learning with very low number of lever-presses across the days (Figure 28. B). Indeed, while 83.3% of DAT-Cre mice learn the task, 100% of Shank3KO mice do not learn the association (Figure 28.

C) between the CS (lever-press) and the US (social stimulus). Preliminary results (not shown here) suggest a global dysfunction in associative learning task not only related to conspecific interaction.

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

(A) Schema of the free social interaction task for nose-to-nose contact quantification. (B) Raster plot example of a single VTA DA neuron during several trials of nose-to-nose contact. (C) Left: VTA DA neuron activity normalized and averaged for all the cells around the nose-to-nose contact during the 1st exposure to social stimulus. Right: VTA DA neuron activity normalized and averaged for all the cells around the nose-to-nose contact during the 3rd exposure to social stimulus. RM two-way ANOVA (Time (Trial) main effect: F(1,60) = 1.8926, P = 0.1740; Stimulus main effect: F(1,60) = 20.7051, P < 0.0001; Interaction Time x Stimulus: F(1,60) = 6.0535, P = 0.0168) followed by Bonferroni-Holm post-hoc test correction. (D) Comparison of VTA DA activity normalized between the 1st and the 3rd trial. Statistics applied are from the previous RM two-way ANOVA. (E) Difference of normalized VTA DA activity between social and baseline condition for DAT-Cre and Shank3KO mice, during the 1st and the 3rd trials. RM two-way ANOVA (Time (trials) main effect: F(1,52) = 15.2623, P = 0.0003; Genotype main effect: F(1,52) = 7.9378, P = 0.0068; Interaction Time x Genotype:

F(1,52) = 2.3599, P = 0.1306).

Considering our results so far, we hypothesized that downregulation of Shank3 would change intrinsic properties of DA neurons. To test this hypothesis, we compared baseline DA activity between DAT-Cre and Shank3KO mice.

Remarkably, while the spontaneous frequency is not different between the 2 strains, the Shank3KO mice have a lower %SWB (Figure 29. A).

Figure 28: Shank3KO mice are impaired in social associative learning

(A) Schema of social operant task. (B) Number of lever-presses for both DAT-Cre and Shank3KO mice during the shaping phase and the instrumental phase. RM two-way ANOVA by both factors

(Time main effect: F(24,480) = 11.22, P < 0.0001; Genotype main effect: F(1,20) = 26.83, P < 0.0001;

Interaction Time x Genotype: F(24,480) = 10.76, P < 0.0001) followed by Bonferroni post-hoc test. (C) Quantification of learner vs non-learners for DAT-Cre and Shank3KO mice.

These results could reflect changes in intrinsic VTA DA cell physiology and more specifically at bursting activity level. Preliminary ex-vivo recording data, in collaboration with Stefano Musardo, revealed that VTA DA cells of Shank3KO mice are less excitable compare to WT animals (Figure 29. B). Interestingly, previous studies showed that Shank3 protein directly binds to the Hyperpolarization-activated cyclic nucleotide–gated (HCN) channels117. Furthermore, overexpression of HCN2 channels increases cell excitability and the firing rate of VTA DA neurons in-vitro118. For these reasons, we decided to look at the Ih current of Shank3KO mice VTA DA cells. Remarkably, by using two different protocols111,119, we revealed a decreased Ih current for Shank3KO mice (Figure 29. C-F) compare to WT littermate.

Thereby, these electrophysiological results could explain the VTA DA activity alterations in-vivo and the behavioral phenotype deficits in social interactions.

VTA DA cells for WT and Shank3KO mice. RM two-way ANOVA (Current main effect: F(1.712,15.41) = 24.31, P < 0.0001; Genotype main effect: F(1,9) = 8.243, P = 0.0182; Interaction Current x Genotype:

F(10,90) = 5.846, P < 0.0001). (C) Example traces of chirp signal (alternative current) applied to the VTA DA cells and responses of WT and Shank3KO VTA DA cells. (D) Traces of impedance amplitude at different potentials for WT and Shank3KO mice. The maximum amplitude is different for Shank3KO mice at lower higher potentials. (E) Average of maximum frequency at different potentials for WT and Shank3KO mice. Linear Regression. (F) Classical protocol for Ih current amplitude at different clamped membrane potentials. RM two-way ANOVA (Current main effect:

F(1.136,21.45) = 70.15, P < 0.0001; Genotype main effect: F(1,19) = 3.714, P = 0.0690; Interaction Current x Genotype: F(8,151) = 4.708, P < 0.0001) followed by Bonferroni post-hoc test.

Discussion

In this study we have established the role of VTA DA neurons during social interactions. More specifically we have shown that the activity of VTA DA neurons increase during conspecific interaction. Although previous studies provided information about the link between DA and social stimuli using fiber photometry16, the strength of our study is to demonstrate directly, using in-vivo recording in freely behaving mice, the change in spike activity.

Increase DA activity could reflect rewarding and saliency properties of a stimulus44,53,56,120. Our results not only suggest that social stimuli have intrinsic rewarding properties, but the presence of a prediction signal in a social learning task indicates that interaction with a conspecific is per se reinforcing.

Furthermore, we have shown that DA neurons responses to the conditioned stimulus (lever-press) are greatly increased when the delay to go to interact with the conspecific is reduced. These data strengthen the hypothesis that DA neurons encode reward prediction error41 related to social interaction (social prediction error). In future experiments, we will need to design unexpected omission paradigms to validate if VTA DA neurons follow the common formal computational models already described for natural rewards41,43,47,120. Understand such a neuronal mechanism involved in social interactions is fundamental to better dissect the neurobiological circuits of social behaviors.

In our studies, we also proved that chemogenetic inhibition of VTA DA neurons attenuates exploration toward nonfamiliar conspecifics and interferes with the reinforcing properties of nonfamiliar conspecific interaction in mice121. It has been previously shown that inhibition of DA activity at the time of the prediction is sufficient to alter the reinforced behaviors during natural reward consumption122. In line with these results, we now would like to test the hypothesis that inhibition of DA neurons impairs associative learning during the operant task for social interaction. These results would eventually causally link the activity of DA neurons with social reinforcement learning.

Social behaviors need the integration of the environmental sensory cues with social internal states (motivation, reward, arousal, etc.) in order to adopt the proper behavioral output. The Superior Colliculus (SC) has been described as a multi-sensory integration structure, and has been involved in several behaviors:

orientation, attention, decision-making as well as visual and auditory perception71,72,123,124. Our data highlight the role of a new excitatory pathway between the SC and the VTA in social interactions. Stimulation of this SC – VTA pathway alters social preference versus an inanimate object, social novelty preference over a social familiar stimulus and social novelty exploration.

Interestingly, this over-stimulation leads to less head orientation toward social stimulus while the locomotor activity is increased in a new environment. These data suggest an increase exploratory behavior with less interest to orient toward salient stimuli as social. It is known SC projections can induce fast response of SNc DA neurons during strong and transient sensory stimuli (visual an auditory mainly)66,68. Our findings strengthen the importance of SC modulation of midbrain DA neurons during multi-sensory stimuli interaction. Although previous studies have described DA midbrain neurons modulation from the SC66,68, the role of this pathway in social interaction has been neglected.

Interestingly, we identify that VTA DA neurons receiving SC connections are a specific subpopulation of DA neurons sending projections to the Dorso Lateral Striatum (DS). Even though VTA DA to NAc pathway is one of the major DA bundle, we did not find strong connections between SC and DA neurons projecting to NAc. Historically, SNc DA neurons projecting to DS have been described to be involved in locomotor activity of motivated behavior, self-paced motor task and goal-directed behavior125,126. Thus, our data suggest that the SC –

behaviors115. The VTADA – NAc projections are part of the reward system involved in motivation to seek rewards127–129. We demonstrate in this study that over-stimulation of AC – VTA pathway or VTADA – NAc projections both increase social interaction. These data strongly suggest that AC – VTADA – NAc is a complementary pathway to the SC – VTADA – DS that would encode seeking behavior. Thereby, while the SC would send information to orient toward a salient stimulus, the AC would send information about the interest to initiate and maintain the interaction with it, all of this through the different VTA DA neurons subpopulations. This hypothesis would provide explanations about our head orientations results.

Altered social interactions and communication are defining aspects of the autism phenotype. However, “such alterations may arise from a plethora of neuronal processing defects, ranging from alterations in perception, sensory processing, multisensory integration, or positive and negative valence assigned to conspecific stimuli”121. During my thesis I have explored DA VTA circuit as the relevant circuit for the exploration to nonfamiliar conspecific. Two different mouse models have been used. In the first study, in collaboration with Peter Scheiffele from University of Basel, we proved that global or VTA DA neuron-specific loss of the ASD-associated synaptic adhesion molecule neuroligin 3 alters the behavioral response toward nonfamiliar conspecifics and the reinforcing properties of conspecific interaction121. In a second study, we proved that global loss of the ASD-associated scaffolding protein Shank3 (Shank3KO) not only alters conspecific interaction, but affect VTA DA neuron activity as well.

Furthermore, our data strongly indicate that Shank3KO are also not able to learn the social operant task and build the association between the CS (lever-press) and the US (social interaction). This phenotype suggests a deficit in the prediction during associative learning. Interestingly, preliminary results within the laboratory indicate that Shank3KO mice present alterations to associate a CS (lever-press) with a natural reward (food pellet). These deficits are in line with previous reports110 and suggest a general deficit in associative learning in this mouse line and that alterations in VTA DA neuron activity could lead to prediction defaults during learning.

However, in Shank3KO mice Shank3 gene deletion is constitutive, and a modified VTA DA neuron activity could be explained by global network changes.

Previous studies of the laboratory (Bariselli, Tzanoulinou et al. 17), showed that the specific inactivation of Shank3 at the level of VTA (Shank3-VTA KD) results in a reduced activity of DA neurons in anesthetized mice and in social deficits.

Although Shank3 downregulation was not cell type specific, these results strengthen the major role of VTA DA neurons in sociability. Intriguingly, Bariselli, Tzanoulinou et al. also found changes in GABA neuronal activity within the VTA in Shank3-VTA KD mice. Future studies will need to investigate the role of VTA GABA neurons in social interaction.

In Shank3KO mice the decrease of social exploration and the lower VTA DA neuron activity during conspecific interaction could be explained by an altered modulation of VTA DA neurons. Investigating the role of the SC – VTA DA – DS and AC – VTADA – NAc pathways in these mice could bring additional information about the VTA DA modulation. Acting on the SC – VTADA – DS and/or AC – VTADA – NAc pathways could be a strategy to rescue social deficits in Shank3KO mice.

Additionally, our ex-vivo electrophysiological data suggest Shank3KO mice present intrinsic alterations of VTA DA neurons physiology. Indeed, we show decreased cell excitability associated with lower Ih current in VTA DA neurons.

Thereby HCN channels could be a good potential target to rescue cell intrinsic excitability properties. Nevertheless, since the Shank3KO mice phenotype is very strong, a contingency of altered input modulation and intrinsic cell physiology could explain it.

collaboration with Marie Schaer from University of Geneva, our animal’s experimental design and data, allowed to recapitulate social deficits in humans with ASDs, using similar protocols. By this way, cellular basis of such deficits become clearer and potential treatments can be explored and tested.

References

1. Chen, P. & Hong, W. Neural Circuit Mechanisms of Social Behavior. Neuron 98, 16–30 (2018).

2. Mastropieri, D. & Turkewitz, G. Prenatal experience and neonatal

responsiveness to vocal expressions of emotion. Dev. Psychobiol. 35, 204–

214 (1999).

3. Bushnell, I. W. . Mother’s Face Recognition in newborn infants: Learning and Memory. Infant Child Dev. 10, 67–74 (2001).

4. Winston, R. & Chicot, R. The importance of early bonding on the long-term mental health and resilience of children. London J. Prim. Care (Abingdon).

8, 12–14 (2016).

5. Nelson, C. A. et al. Cognitive Recovery in Socially Deprived Young Children:

the Bucharest Early Intervention Project. Science (80-. ). 318, 1937–1940 (2007).

6. Cacioppo, J. T. & Hawkley, L. C. Perceived social isolation and cognition.

Trends Cogn. Sci. 13, 447–454 (2009).

7. Kanwisher, N., McDermott, J. & Chun, M. M. The Fusiform Face Area: A Module in Human Extrastriate Cortex Specialized for Face Perception. J.

Neurosci. 17, 4302–4311 (1997).

8. Barton, J. J. S., Press, D. Z., Keenan, J. P. & O’Connor, M. Lesions of the fusiform face area impair perception of facial configuration in prosopagnosia. Neurology 58, 71–78 (2002).

9. Chevallier, C., Kohls, G., Troiani, V., Brodkin, E. S. & Schultz, R. T. The social motivation theory of autism. Trends Cogn. Sci. 16, 231–238 (2012).

10. Habib, M., Cassotti, M., Moutier, S., Houdé, O. & Borst, G. Fear and anger have opposite effects on risk seeking in the gain frame. Front. Psychol. 6, 1–

7 (2015).

11. Markowitz, J. E. et al. The Striatum Organizes 3D Behavior via Moment-to- Moment Action Selection Normal syllable sequence Lesion Syllable A. Cell 174, 1–15 (2018).

12. de Chaumont, F. et al. Computerized video analysis of social interactions in mice. Nat. Methods 9, 410–417 (2012).

13. Ferguson, J. N. et al. Social amnesia in mice lacking the oxytocin gene. Nat.

Genet. 25, 284–288 (2000).

14. Nadler, J. J. et al. Automated apparatus for quantitation of social approach behaviors in mice. Genes, Brain Behav. 3, 303–314 (2004).

15. Moy, S. S. et al. Sociability and preference for social novelty in five inbred strains: An approach to assess autistic-like behavior in mice. Genes, Brain Behav. 3, 287–302 (2004).

16. Gunaydin, L. a. et al. Natural neural projection dynamics underlying social behavior. Cell 157, 1535–1551 (2014).

17. Bariselli, S. et al. SHANK3 controls maturation of social reward circuits in the VTA. Nat. Neurosci. 19, (2016).

18. Mei, Y. et al. Adult restoration of Shank3 expression rescues selective autistic-like phenotypes. Nature 1–17 (2016). doi:10.1038/nature16971 19. Leite, I. S., Castelhano, A. S. S. & Cysneiros, R. M. Effect of diazepam on

sociability of rats submitted to neonatal seizures. data Br. 7, 686–691 (2016).

20. Hung, LW; Neuner, S; Plepalli, JS; Beier, K; Wright, M; Walsh, J; Luo, L;

Deisseroth, K; Dölen, G; Malenka, R. Gating of social reward by oxytocin in the ventral tegmental area. Science (80-. ). 1411, 1406–1411 (2017).

21. Bariselli, S., Contestabile, A., Tzanoulinou, S., Musardo, S. & Bellone, C.

SHANK3 Downregulation in the Ventral Tegmental Area Accelerates the Extinction of Contextual Associations Induced by Juvenile Non-familiar Conspecific Interaction. Front. Mol. Neurosci. 11, 1–16 (2018).

26. Knowland, D. et al. Distinct Ventral Pallidal Neural Populations Mediate Separate Symptoms of Depression. Cell 170, 284–297.e18 (2017).

27. Nair-Roberts, R. G. et al. 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 (2008).

28. Margolis, E. B., Lock, H., Hjelmstad, G. O. & Fields, H. L. The ventral tegmental area revisited: Is there an electrophysiological marker for dopaminergic neurons? J. Physiol. 577, 907–924 (2006).

29. Brown, M. T. C. et al. Ventral tegmental area GABA projections pause accumbal cholinergic interneurons to enhance associative learning. Nature 492, 452–456 (2012).

30. Kramer, P. F. & Williams, J. T. Cocaine Decreases Metabotropic Glutamate Receptor mGluR1 Currents in Dopamine Neurons by Activating mGluR5.

Neuropsychopharmacology 40, 2418–2424 (2015).

31. Bariselli, S., Glangetas, C., Tzanoulinou, S. & Bellone, C. Ventral tegmental area subcircuits process rewarding and aversive experiences. J.

Neurochem. 139, 1071–1080 (2016).

32. Matthews, G. A. et al. Dorsal Raphe Dopamine Neurons Represent the Experience of Social Isolation. Cell 164, 617–631 (2016).

33. Björklund, A. & Dunnett, S. B. Dopamine neuron systems in the brain: an update. Trends Neurosci. 30, 194–202 (2007).

34. Grace, a a & Bunney, B. S. The control of firing pattern in nigral dopamine neurons: burst firing. J. Neurosci. 4, 2877–2890 (1984).

35. Ungless, M. A. & Grace, A. A. Are you or aren’t you: Challenes associated with physiologically identifying Ddpamine Neurons. Trends Neurosci. 35, 422–430 (2012).

36. Steffensen, S. C., Svingos, A. L., Pickel, V. M. & Henriksen, S. J.

Electrophysiological Characterization of GABAergic Neurons in the Ventral Tegmental Area. J. Neurosci. 18, 8003–8015 (1998).

37. Tan, K. R. et al. GABA Neurons of the VTA Drive Conditioned Place Aversion. Neuron 73, 1173–1183 (2012).

38. Bocklisch, C. et al. Cocaine Disinhibits Dopamine Neurons by Potentiation of GABA Transmission in the Ventral Tegmental Area. Science (80-. ). 341,

1521–1526 (2013).

39. Pavlov, I. P. Conditioned reflexes: An investigation of the physiological activity of the cerebral cortex. Ann. Neurosci. 17, 136–141 (1927).

40. Rescorla, R. A. & Wagner, A. R. A theory of Pavlovian Conditioning:

Variations in the Effectiveness of Reinforcement and Nonreinforcement.

A.H. Black W.F. Prokasy (eds.), Class. Cond. II Curr. Res. theory 64–99 (1972).

doi:10.1101/gr.110528.110

41. Schultz, W., Dayan, P. & Montague, P. R. A neural substrate of prediction and reward. Science 275, 1593–1599 (1997).

42. Sutton, R. S. & Barto, A. G. Reinforcement learning: An Introduction. IEEE Trans. Neural Networks 16, (1998).

43. Keiflin, R. & Janak, P. H. Review Dopamine Prediction Errors in Reward Learning and Addiction : From Theory to Neural Circuitry. Neuron 88, 247–263 (2015).

44. Tobler, P. N., Fiorillo, C. D. & Schultz, W. Adaptive coding of reward value by dopamine neurons. Science 307, 1642–1645 (2005).

45. Fiorillo, C. D., Tobler, P. N. & Schultz, W. Discrete coding of reward probability and uncertainty by dopamine neurons. Science 299, 1898–

1902 (2003).

46. Naudé, J. et al. Nicotinic receptors in the ventral tegmental area promote uncertainty-seeking. Nat. Neurosci. (2016). doi:10.1038/nn.4223

47. Eshel, N. et al. Arithmetic and local circuitry underlying dopamine

47. Eshel, N. et al. Arithmetic and local circuitry underlying dopamine