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Unexpected global impact of VTA dopamine neuron activation as measured by opto-fMRI

Abstract

Dopamine neurons in the ventral tegmental area (VTA) are strongly implicated in cognitive and affective processing as well as in psychiatric disorders, including schizophrenia, depression, attention-deficit hyperactivity disorder and substance abuse disorders. In human studies, dopamine-related functions are routinely assessed using functional magnetic resonance imaging (fMRI) measures of blood oxygenation-level-dependent (BOLD) signals during the performance of dopamine-dependent tasks. There is, however, a critical void in our knowledge about whether and how activation of VTA dopamine neurons specifically influences regional or global fMRI signals. Here, we used optogenetics in Th::Cre rats to selectively stimulate VTA dopamine neurons while simultaneously measuring global hemodynamic changes using BOLD and cerebral blood volume-weighted (CBVw) fMRI. Phasic activation of VTA dopamine neurons increased BOLD and CBVw fMRI signals in VTA-innervated limbic regions, including the ventral striatum (nucleus accumbens). Surprisingly, basal ganglia regions that receive sparse or no VTA dopaminergic innervation, including the dorsal striatum and the globus pallidus, were also activated. In fact, the most prominent fMRI signal increase in the forebrain was observed in the dorsal striatum that is not traditionally associated with VTA dopamine neurotransmission. These data establish causation between phasic activation of VTA dopamine neurons and global fMRI signals. They further suggest that mesolimbic and non-limbic basal ganglia dopamine circuits are functionally connected and thus provide a potential novel framework for understanding dopamine-dependent functions and interpreting data obtained from human fMRI studies.

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References

  1. Koob GF, Volkow ND . Neurocircuitry of addiction. Neuropsychopharmacology 2010; 35: 217–238.

    Article  Google Scholar 

  2. Everitt BJ, Belin D, Economidou D, Pelloux Y, Dalley JW, Robbins TW . Review. Neural mechanisms underlying the vulnerability to develop compulsive drug-seeking habits and addiction. Philos Trans R Soc Lond B Biol Sci 2008; 363: 3125–3135.

    Article  Google Scholar 

  3. Grace AA . Gating of information flow within the limbic system and the pathophysiology of schizophrenia. Brain Res Brain Res Rev 2000; 31: 330–341.

    Article  CAS  Google Scholar 

  4. Nestler EJ, Carlezon WA Jr . The mesolimbic dopamine reward circuit in depression. Biol Psychiatry 2006; 59: 1151–1159.

    Article  CAS  Google Scholar 

  5. Polter AM, Kauer JA . Stress and VTA synapses: implications for addiction and depression. Eur J Neurosci 2014; 39: 1179–1188.

    Article  Google Scholar 

  6. Bjorklund A, Dunnett SB . Dopamine neuron systems in the brain: an update. Trends Neurosci 2007; 30: 194–202.

    Article  Google Scholar 

  7. Graybiel AM, Grafton ST . The striatum: where skills and habits meet. Cold Spring Harb Perspect Biol 2015; 7: a021691.

    Article  Google Scholar 

  8. Smith Y, Kieval JZ . Anatomy of the dopamine system in the basal ganglia. Trends Neurosci 2000; 23: S28–S33.

    Article  CAS  Google Scholar 

  9. Howes OD, Williams M, Ibrahim K, Leung G, Egerton A, McGuire PK et al. Midbrain dopamine function in schizophrenia and depression: a post-mortem and positron emission tomographic imaging study. Brain 2013; 136 (Pt 11): 3242–3251.

    Article  Google Scholar 

  10. Yoon JH, Minzenberg MJ, Raouf S, D'Esposito M, Carter CS . Impaired prefrontal-basal ganglia functional connectivity and substantia nigra hyperactivity in schizophrenia. Biol Psychiatry 2013; 74: 122–129.

    Article  Google Scholar 

  11. Volkow ND, Wang GJ, Fowler JS, Tomasi D . Addiction circuitry in the human brain. Annu Rev Pharmacol Toxicol 2012; 52: 321–336.

    Article  CAS  Google Scholar 

  12. Juckel G, Schlagenhauf F, Koslowski M, Wustenberg T, Villringer A, Knutson B et al. Dysfunction of ventral striatal reward prediction in schizophrenia. Neuroimage 2006; 29: 409–416.

    Article  Google Scholar 

  13. Morris RW, Vercammen A, Lenroot R, Moore L, Langton JM, Short B et al. Disambiguating ventral striatum fMRI-related bold signal during reward prediction in schizophrenia. Mol Psychiatry 2012; 17: 280–289.

    Article  Google Scholar 

  14. Rolland B, Amad A, Poulet E, Bordet R, Vignaud A, Bation R et al. Resting-state functional connectivity of the nucleus accumbens in auditory and visual hallucinations in schizophrenia. Schizophr Bull 2015; 41: 291–299.

    Article  Google Scholar 

  15. Nauczyciel C, Robic S, Dondaine T, Verin M, Robert G, Drapier D et al. The nucleus accumbens: a target for deep brain stimulation in resistant major depressive disorder. J Mol Psychiatry 2013; 1: 17.

    Article  Google Scholar 

  16. Arrondo G, Segarra N, Metastasio A, Ziauddeen H, Spencer J, Reinders NR et al. Reduction in ventral striatal activity when anticipating a reward in depression and schizophrenia: a replicated cross-diagnostic finding. Front Psychol 2015; 6: 1280.

    Article  Google Scholar 

  17. O'Doherty JP, Dayan P, Friston K, Critchley H, Dolan RJ . Temporal difference models and reward-related learning in the human brain. Neuron 2003; 38: 329–337.

    Article  CAS  Google Scholar 

  18. Carter RM, Macinnes JJ, Huettel SA, Adcock RA . Activation in the VTA and nucleus accumbens increases in anticipation of both gains and losses. Front Behav Neurosci 2009; 3: 21.

    Article  Google Scholar 

  19. Attwell D, Buchan AM, Charpak S, Lauritzen M, Macvicar BA, Newman EA . Glial and neuronal control of brain blood flow. Nature 2010; 468: 232–243.

    Article  CAS  Google Scholar 

  20. Lauritzen M . Reading vascular changes in brain imaging: is dendritic calcium the key? Nat Rev Neurosci 2005; 6: 77–85.

    Article  CAS  Google Scholar 

  21. Knutson B, Gibbs SE . Linking nucleus accumbens dopamine and blood oxygenation. Psychopharmacology (Berl) 2007; 191: 813–822.

    Article  CAS  Google Scholar 

  22. Chen YC, Choi JK, Andersen SL, Rosen BR, Jenkins BG . Mapping dopamine D2/D3 receptor function using pharmacological magnetic resonance imaging. Psychopharmacology (Berl) 2004; 180: 705–715.

    Article  Google Scholar 

  23. Marota JJ, Mandeville JB, Weisskoff RM, Moskowitz MA, Rosen BR, Kosofsky BE . Cocaine activation discriminates dopaminergic projections by temporal response: an fMRI study in rat. Neuroimage 2000; 11: 13–23.

    Article  CAS  Google Scholar 

  24. Underhill SM, Wheeler DS, Li M, Watts SD, Ingram SL, Amara SG . Amphetamine modulates excitatory neurotransmission through endocytosis of the glutamate transporter EAAT3 in dopamine neurons. Neuron 2014; 83: 404–416.

    Article  CAS  Google Scholar 

  25. Schultz W . Predictive reward signal of dopamine neurons. J Neurophysiol 1998; 80: 1–27.

    Article  CAS  Google Scholar 

  26. Mandeville JB, Marota JJ . Vascular filters of functional MRI: spatial localization using BOLD and CBV contrast. Magn Reson Med 1999; 42: 591–598.

    Article  CAS  Google Scholar 

  27. Zhao F, Wang P, Hendrich K, Ugurbil K, Kim S-G . Cortical layer-dependent BOLD and CBV responses measured by spin-echo and gradient-echo fMRI: Insights into hemodynamic regulation. NeuroImage 2006; 30: 1149–1160.

    Article  Google Scholar 

  28. Poplawsky AJ, Fukuda M, Murphy M, Kim SG . Layer-specific fMRI responses to excitatory and inhibitory neuronal activities in the olfactory bulb. J Neurosci 2015; 35: 15263–15275.

    Article  CAS  Google Scholar 

  29. Witten IB, Steinberg EE, Lee SY, Davidson TJ, Zalocusky KA, Brodsky M et al. Recombinase-driver rat lines: tools, techniques, and optogenetic application to dopamine-mediated reinforcement. Neuron 2011; 72: 721–733.

    Article  CAS  Google Scholar 

  30. Paxinos G, Watson C . The Rat Brain in Stereotaxic Coordinates. 6th edn. Elsevier Academic Press: New York, USA, 2007.

    Google Scholar 

  31. Silva AC, Koretsky AP, Duyn JH . Functional MRI impulse response for BOLD and CBV contrast in rat somatosensory cortex. Magn Reson Med 2007; 57: 1110–1118.

    Article  Google Scholar 

  32. Kim SG, Harel N, Jin T, Kim T, Lee P, Zhao F . Cerebral blood volume MRI with intravascular superparamagnetic iron oxide nanoparticles. NMR Biomed 2013; 26: 949–962.

    Article  CAS  Google Scholar 

  33. Cox RW . AFNI: Software for analysis and visualization of functional magnetic resonance neuroimages. Comput Biomed Res 1996; 29: 162–173.

    Article  CAS  Google Scholar 

  34. Kim T, Masamoto K, Fukuda M, Vazquez A, Kim SG . Frequency-dependent neural activity, CBF, and BOLD fMRI to somatosensory stimuli in isoflurane-anesthetized rats. Neuroimage 2010; 52: 224–233.

    Article  Google Scholar 

  35. Swanson L . The projection of the ventral tegmental area and adjacent regions: a combined fluorescent retrograde tracer and immunofluorescence study in the rat. Brain Res Bull 1982; 9: 321–353.

    Article  CAS  Google Scholar 

  36. Berger B, Casper P, Verney C . Dopaminergic innervation of the cerebral cortex: Unexpected differences between rodents and primates. Trends Neurosci 1991; 14: 21–27.

    Article  CAS  Google Scholar 

  37. Klitenick MA, Deutch AY, Churchill L, Kalivas PW . Topography and functional role of dopaminergic projections from the ventral mesencephalic tegmentum to the ventral pallidum. Neuroscience 1992; 50: 371–386.

    Article  CAS  Google Scholar 

  38. Yetnikoff L, Lavezzi HN, Reichard RA, Zahm DS . An update on the connections of the ventral mesencephalic dopaminergic complex. Neuroscience 2014; 282C: 23–48.

    Article  Google Scholar 

  39. Liljeholm M, O’Doherty JP . Contributions of the striatum to learning, motivation, and performance: an associative account. Trends Cogn Sci 2012; 16: 467–475.

    Article  Google Scholar 

  40. Van Waes V, Beverley JA, Siman H, Tseng KY, Steiner H . CB1 cannabinoid receptor expression in the striatum: association with corticostriatal circuits and developmental regulation. Front Pharmacol 2012; 3: 21.

    Article  Google Scholar 

  41. Boyden ES, Zhang F, Bamberg E, Nagel G, Deisseroth K . Millisecond-timescale, genetically targeted optical control of neural activity. Nat Neurosci 2005; 8: 1263–1268.

    Article  CAS  Google Scholar 

  42. Beier Kevin T, Steinberg Elizabeth E, DeLoach Katherine E, Xie S, Miyamichi K, Schwarz L et al. Circuit architecture of VTA dopamine neurons revealed by systematic input-output mapping. Cell 2015; 162: 622–634.

    Article  CAS  Google Scholar 

  43. Bass CE, Grinevich VP, Gioia D, Day-Brown JD, Bonin KD, Stuber GD et al. Optogenetic stimulation of VTA dopamine neurons reveals that tonic but not phasic patterns of dopamine transmission reduce ethanol self-administration. Front Behav Neurosci 2013; 7: 173.

    Article  Google Scholar 

  44. Tritsch NX, Ding JB, Sabatini BL . Dopaminergic neurons inhibit striatal output through non-canonical release of GABA. Nature 2012; 490: 262–266.

    Article  CAS  Google Scholar 

  45. Tritsch NX, Oh WJ, Gu C, Sabatini BL . Midbrain dopamine neurons sustain inhibitory transmission using plasma membrane uptake of GABA, not synthesis. Elife 2014; 3: e01936.

    Article  Google Scholar 

  46. Iordanova B, Vazquez AL, Poplawsky AJ, Fukuda M, Kim S-G . Neural and hemodynamic responses to optogenetic and sensory stimulation in the rat somatosensory cortex. J Cereb Blood Flow Metab 2015; 35: 922–932.

    Article  CAS  Google Scholar 

  47. Sibson NR, Dhankhar A, Mason GF, Rothman DL, Behar KL, Shulman RG . Stoichiometric coupling of brain glucose metabolism and glutamatergic neuronal activity. Proc Natl Acad Sci USA 1998; 95: 316–321.

    Article  CAS  Google Scholar 

  48. Haber SN, Calzavara R . The cortico-basal ganglia integrative network: the role of the thalamus. Brain Res Bull 2009; 78: 69–74.

    Article  Google Scholar 

  49. Voorn P, Vanderschuren LJ, Groenewegen HJ, Robbins TW, Pennartz CM . Putting a spin on the dorsal-ventral divide of the striatum. Trends Neurosci 2004; 27: 468–474.

    Article  CAS  Google Scholar 

  50. Nauta WJ, Smith GP, Faull RL, Domesick VB . Efferent connections and nigral afferents of the nucleus accumbens septi in the rat. Neuroscience 1978; 3: 385–401.

    Article  CAS  Google Scholar 

  51. Helbing C, Brocka M, Scherf T, Lippert MT, Angenstein F . The role of the mesolimbic dopamine system in the formation of blood-oxygen-level dependent responses in the medial prefrontal/anterior cingulate cortex during high-frequency stimulation of the rat perforant pathway. J Cereb Blood Flow Metab (e-pub ahead of print 5 November 2015).

  52. Matsumoto M, Hikosaka O . How do dopamine neurons represent positive and negative motivational events? Nature 2009; 459: 837–841.

    Article  CAS  Google Scholar 

  53. Csernansky JG, Bardgett ME . Limbic-cortical neuronal damage and the pathophysiology of schizophrenia. Schizophr Bull 1998; 24: 231–248.

    Article  CAS  Google Scholar 

  54. Kumari V, Gray JA, Honey GD, Soni W, Bullmore ET, Williams SCR et al. Procedural learning in schizophrenia: a functional magnetic resonance imaging investigation. Schizophrenia Research 2002; 57: 97–107.

    Article  Google Scholar 

  55. Reiss JP, Campbell DW, Leslie WD, Paulus MP, Ryner LN, Polimeni JO et al. Deficit in schizophrenia to recruit the striatum in implicit learning: A functional magnetic resonance imaging investigation. Schizophr Res 2006; 87: 127–137.

    Article  Google Scholar 

  56. Murray GK, Corlett PR, Clark L, Pessiglione M, Blackwell AD, Honey G et al. Substantia nigra/ventral tegmental reward prediction error disruption in psychosis. Mol Psychiatry 2008; 13: 239–276.

    Article  CAS  Google Scholar 

  57. Weickert TW, Goldberg TE, Callicott JH, Chen Q, Apud JA, Das S et al. Neural correlates of probabilistic category learning in patients with schizophrenia. J Neurosci 2009; 29: 1244–1254.

    Article  CAS  Google Scholar 

  58. Kegeles LS, Abi-Dargham A, Frankle WG, Gil R, Cooper TB, Slifstein M et al. Increased synaptic dopamine function in associative regions of the striatum in schizophrenia. Arch Gen Psychiatry 2010; 67: 231–239.

    Article  CAS  Google Scholar 

  59. Howes OD, Montgomery AJ, Asselin MC, Murray RM, Valli I, Tabraham P et al. Elevated striatal dopamine function linked to prodromal signs of schizophrenia. Arch Gen Psychiatry 2009; 66: 13–20.

    Article  Google Scholar 

  60. Claus ED, Ewing SW, Filbey FM, Sabbineni A, Hutchison KE . Identifying neurobiological phenotypes associated with alcohol use disorder severity. Neuropsychopharmacology 2011; 36: 2086–2096.

    Article  Google Scholar 

  61. Vollstädt-Klein S, Wichert S, Rabinstein J, Bühler M, Klein O, Ende G et al. Initial, habitual and compulsive alcohol use is characterized by a shift of cue processing from ventral to dorsal striatum. Addiction 2010; 105: 1741–1749.

    Article  Google Scholar 

  62. Lammel S, Steinberg EE, Foldy C, Wall NR, Beier K, Luo L et al. Diversity of transgenic mouse models for selective targeting of midbrain dopamine neurons. Neuron 2015; 85: 429–438.

    Article  CAS  Google Scholar 

  63. Totah NK, Kim Y, Moghaddam B . Distinct prestimulus and poststimulus activation of VTA neurons correlates with stimulus detection. J Neurophysiol 2013; 110: 75–85.

    Article  CAS  Google Scholar 

  64. Kim YB, Matthews M, Moghaddam B . Putative gamma-aminobutyric acid neurons in the ventral tegmental area have a similar pattern of plasticity as dopamine neurons during appetitive and aversive learning. Eur J Neurosci 2010; 32: 1564–1572.

    Article  Google Scholar 

  65. Desai M, Kahn I, Knoblich U, Bernstein J, Atallah H, Yang A et al. Mapping brain networks in awake mice using combined optical neural control and fMRI. J Neurophysiol 2011; 105: 1393–1405.

    Article  CAS  Google Scholar 

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Acknowledgements

This work was supported by the National Institutes of Health grants R01 (MH048404 and EB003324), R21 (EB018903), Multimodal Neuroimaging Training Fellowship (University of Pittsburgh) and the Institute for Basic Science (IBS-R015-D1).

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SL and AJP performed the experiments and analyzed data. All authors designed the experiments. SL, AJP and BM wrote the paper.

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Correspondence to B Moghaddam.

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Lohani, S., Poplawsky, A., Kim, SG. et al. Unexpected global impact of VTA dopamine neuron activation as measured by opto-fMRI. Mol Psychiatry 22, 585–594 (2017). https://doi.org/10.1038/mp.2016.102

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