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Loss of Intrinsic Organization of Cerebellar Networks in Spinocerebellar Ataxia Type 1: Correlates with Disease Severity and Duration

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Abstract

The spinocerebellar ataxias (SCAs) are a genetically heterogeneous group of cerebellar degenerative disorders, characterized by progressive gait unsteadiness, hand incoordination, and dysarthria. The mutational mechanism in SCA1, a dominantly inherited form of SCA, consists of an expanded trinucleotide CAG repeat. In SCA1, there is loss of Purkinje cells, neuronal loss in dentate nucleus, olives, and pontine nuclei. In the present study, we sought to apply intrinsic functional connectivity analysis combined with diffusion tensor imaging to define the state of cerebellar connectivity in SCA1. Our results on the intrinsic functional connectivity in lateral cerebellum and thalamus showed progressive organizational changes in SCA1 noted as a progressive increase in the absolute value of the correlation coefficients. In the lateral cerebellum, the anatomical organization of functional clusters seen as parasagittal bands in controls is lost, changing to a patchy appearance in SCA1. Lastly, only fractional anisotropy in the superior peduncle and changes in functional organization in thalamus showed a linear dependence to duration and severity of disease. The present pilot work represents an initial effort describing connectivity biomarkers of disease progression in SCA1. The functional changes detected with intrinsic functional analysis and diffusion tensor imaging suggest that disease progression can be analyzed as a disconnection syndrome.

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Notes

  1. Anatomically [21], the lateral cerebellum included the following lobules: V lat (culmen inferior), VI lat (simplex), VIIA_Crus I/1,2 (superior semilunar lobule), VIIA_Crus II/1,2 (inferior semilunar lobule), VIIB lat (paramedian/gracilis), VIIIA lat (biventer, pars copularis), and VIIIB lat (biventer, pars paraflocculus dorsalis).

References

  1. Koeppen AH. The hereditary ataxias. J Neuropathol Exp Neurol. 1998;57(6):531–43.

    Article  PubMed  CAS  Google Scholar 

  2. Klockgether T. Parkinsonism & related disorders. Ataxias. Parkinsonism Relat Disord. 2007;13 Suppl 3:S391–4.

    Article  PubMed  Google Scholar 

  3. Manto MU. The wide spectrum of spinocerebellar ataxias (SCAs). Cerebellum. 2005;4(1):2–6.

    Article  PubMed  CAS  Google Scholar 

  4. Mascalchi M. Spinocerebellar ataxias. Neurol Sci. 2008;29 Suppl 3:311–3.

    Article  PubMed  Google Scholar 

  5. Genis D, Matilla T, Volpini V, Rosell J, Davalos A, Ferrer I, et al. Clinical, neuropathologic, and genetic studies of a large spinocerebellar ataxia type 1 (SCA1) kindred: (CAG)n expansion and early premonitory signs and symptoms. Neurology. 1995;45(1):24–30.

    PubMed  CAS  Google Scholar 

  6. Gilman S, Sima AA, Junck L, Kluin KJ, Koeppe RA, Lohman ME, et al. Spinocerebellar ataxia type 1 with multiple system degeneration and glial cytoplasmic inclusions. Ann Neurol. 1996;39(2):241–55.

    Article  PubMed  CAS  Google Scholar 

  7. Matilla-Duenas A, Goold R, Giunti P. Clinical, genetic, molecular, and pathophysiological insights into spinocerebellar ataxia type 1. Cerebellum. 2008;7(2):106–14.

    Article  PubMed  CAS  Google Scholar 

  8. Orr HT, Chung MY, Banfi S, Kwiatkowski Jr TJ, Servadio A, Beaudet AL, et al. Expansion of an unstable trinucleotide CAG repeat in spinocerebellar ataxia type 1. Nat Genet. 1993;4(3):221–6.

    Article  PubMed  CAS  Google Scholar 

  9. Schmitz-Hubsch T, Giunti P, Stephenson DA, Globas C, Baliko L, Sacca F, et al. SCA functional index: a useful compound performance measure for spinocerebellar ataxia. Neurology. 2008;71(7):486–92.

    Article  PubMed  CAS  Google Scholar 

  10. Lynch DR, Farmer JM, Tsou AY, Perlman S, Subramony SH, Gomez CM, et al. Measuring Friedreich ataxia: complementary features of examination and performance measures. Neurology. 2006;66(11):1711–6.

    Article  PubMed  CAS  Google Scholar 

  11. Lynch DR, Farmer JM, Wilson RL, Balcer LJ. Performance measures in Friedreich ataxia: potential utility as clinical outcome tools. Mov Disord. 2005;20(7):777–82.

    Article  PubMed  Google Scholar 

  12. Rabinovici GD, Roberson ED. Beyond diagnosis: what biomarkers are teaching us about the “bio”logy of Alzheimer disease. Ann Neurol. 2010;67(3):283–5.

    PubMed  CAS  Google Scholar 

  13. Schmahmann JD, Pandya DN. Disconnection syndromes of basal ganglia, thalamus, and cerebrocerebellar systems. Cortex. 2008;44(8):1037–66.

    Article  PubMed  Google Scholar 

  14. Schmitz-Hubsch T, du Montcel ST, Baliko L, Berciano J, Boesch S, Depondt C, et al. Scale for the assessment and rating of ataxia: development of a new clinical scale. Neurology. 2006;66(11):1717–20.

    Article  PubMed  CAS  Google Scholar 

  15. Noll DC, Cohen JD, Meyer CH, Schneider W. Spiral K-space MRI of cortical activation. J Magn Reson Imaging. 1995;5:49–56.

    Article  PubMed  CAS  Google Scholar 

  16. Cox RW, Jesmanowicz A. Real-time 3D image registration for functional MRI. Magn Reson Med. 1999;42(6):1014–8.

    Article  PubMed  CAS  Google Scholar 

  17. Habas C, Cabanis EA. Anatomical parcellation of the brainstem and cerebellar white matter: a preliminary probabilistic tractography study at 3 T. Neuroradiology. 2007;49(10):849–63.

    Article  PubMed  Google Scholar 

  18. Walsh RR, Small SL, Chen EE, Solodkin A. Network activation during bimanual movements in humans. Neuroimage. 2008;43:540–53.

    Article  PubMed  CAS  Google Scholar 

  19. Makris N, Schlerf JE, Hodge SM, Haselgrove C, Albaugh MD, Seidman LJ, et al. MRI-based surface-assisted parcellation of human cerebellar cortex: an anatomically specified method with estimate of reliability. Neuroimage. 2005;25(4):1146–60.

    Article  PubMed  Google Scholar 

  20. Schmahmann JD, Doyon J, Toga A, Petrides M, Evans A. MRI atlas of the human cerebellum. San Diego: Academic; 2000.

    Google Scholar 

  21. Makris N, Hodge SM, Haselgrove C, Kennedy DN, Dale A, Fischl B, et al. Human cerebellum: surface-assisted cortical parcellation and volumetry with magnetic resonance imaging. J Cogn Neurosci. 2003;15(4):584–99.

    Article  PubMed  Google Scholar 

  22. Raichle ME, MacLeod AM, Snyder AZ, Powers WJ, Gusnard DA, Shulman GL. A default mode of brain function. Proc Natl Acad Sci USA. 2001;98(2):676–82.

    Article  PubMed  CAS  Google Scholar 

  23. Auer DP. Spontaneous low-frequency blood oxygenation level-dependent fluctuations and functional connectivity analysis of the ‘resting’ brain. Magn Reson Imaging. 2008;26(7):1055–64.

    Article  PubMed  Google Scholar 

  24. Diedrichsen J, Verstynen T, Schlerf J, Wiestler T. Advances in functional imaging of the human cerebellum. Curr Opin Neurol. 2010;23(4):382–7.

    PubMed  Google Scholar 

  25. O’Reilly JX, Beckmann CF, Tomassini V, Ramnani N, Johansen-Berg H. Distinct and overlapping functional zones in the cerebellum defined by resting state functional connectivity. Cereb Cortex. 2010;20(4):953–65.

    Article  PubMed  Google Scholar 

  26. Allen G, McColl R, Barnard H, Ringe WK, Fleckenstein J, Cullum CM. Magnetic resonance imaging of cerebellar-prefrontal and cerebellar-parietal functional connectivity. Neuroimage. 2005;28(1):39–48.

    Article  PubMed  Google Scholar 

  27. Habas C, Kamdar N, Nguyen D, Prater K, Beckmann CF, Menon V, et al. Distinct cerebellar contributions to intrinsic connectivity networks. J Neurosci. 2009;29(26):8586–94.

    Article  PubMed  CAS  Google Scholar 

  28. Krienen FM, Buckner RL. Segregated fronto-cerebellar circuits revealed by intrinsic functional connectivity. Cereb Cortex. 2009;19(10):2485–97.

    Article  PubMed  Google Scholar 

  29. Baruchi I, Grossman D, Volman V, Hunter J, Towle VL, Ben-Jacob E. Functional holography analysis: simplifying the complexity of dynamical networks. In: Pecora L, Boccaletti S, editors. Stability of pattern formation in networks of dynamical systems. Chaos. 2006;16:15–112.

    Google Scholar 

  30. Baruchi I, Towle VL, Ben-Jacob E. Functional holography of complex networks activity—from cultures to the human brain. Complexity. 2005;10(3):38–51.

    Article  Google Scholar 

  31. Baruchi I, Ben-Jacob E. Functional holography of recorded neuronal networks activity. Neuroinformatics. 2004;2(3):333–52.

    Article  PubMed  Google Scholar 

  32. Wolfram S. The mathematica book. 4th ed. Cambridge: Cambridge University Press; 1999.

    Google Scholar 

  33. MacQueen JB. Some methods for classification and analysis of multivariate observations. Proceedings of 5-th Berkeley Symposium on Mathematical Statistics and Probability. Berkley: University of California Press; 1967. p. 281–97

  34. Grosberg AU. Statistical physics of macromolecules. New York: Springer; 1994.

    Google Scholar 

  35. Gavrilescu M, Stuart GW, Rossell S, Henshall K, McKay C, Sergejew AA, et al. Functional connectivity estimation in fMRI data: influence of preprocessing and time course selection. Hum Brain Mapp. 2008;29(9):1040–52.

    Article  PubMed  Google Scholar 

  36. Damoiseaux JS, Rombouts SA, Barkhof F, Scheltens P, Stam CJ, Smith SM, et al. Consistent resting-state networks across healthy subjects. Proc Natl Acad Sci USA. 2006;103(37):13848–53.

    Article  PubMed  CAS  Google Scholar 

  37. Miller RA, Strominger NL. An experimental study of the efferent connections of the superior cerebellar peduncle in the rhesus monkey. Brain Res. 1977;133(2):237–50.

    Article  PubMed  CAS  Google Scholar 

  38. Prakash N, Hageman N, Hua X, Toga AW, Perlman SL, Salamon N. Patterns of fractional anisotropy changes in white matter of cerebellar peduncles distinguish spinocerebellar ataxia-1 from multiple system atrophy and other ataxia syndromes. Neuroimage. 2009;47 Suppl 2:T72–81.

    Article  PubMed  Google Scholar 

  39. Globas C, du Montcel ST, Baliko L, Boesch S, Depondt C, DiDonato S, et al. Early symptoms in spinocerebellar ataxia type 1, 2, 3, and 6. Mov Disord. 2008;23(15):2232–8.

    Article  PubMed  Google Scholar 

  40. Mandelli ML, De Simone T, Minati L, Bruzzone MG, Mariotti C, Fancellu R, et al. Diffusion tensor imaging of spinocerebellar ataxias types 1 and 2. AJNR Am J Neuroradiol. 2007;28(10):1996–2000.

    Article  PubMed  CAS  Google Scholar 

  41. Burk K, Abele M, Fetter M, Dichgans J, Skalej M, Laccone F, et al. Autosomal dominant cerebellar ataxia type I clinical features and MRI in families with SCA1, SCA2 and SCA3. Brain. 1996;119(Pt 5):1497–505.

    Article  PubMed  Google Scholar 

  42. Cummings CJ, Orr HT, Zoghbi HY. Progress in pathogenesis studies of spinocerebellar ataxia type 1. Philos Trans R Soc Lond B Biol Sci. 1999;354(1386):1079–81.

    Article  PubMed  CAS  Google Scholar 

  43. Ginestroni A, Dellanave R, Tessa C, Giannelli M, De Grandis D, Plasmati R, et al. Brain structural damage in spinocerebellar ataxia type 1: a VBM study. J Neurol. 2008;255(8):1153–8.

    Article  PubMed  Google Scholar 

  44. Klockgether T, Skalej M, Wedekind D, Luft AR, Welte D, Schulz JB, et al. Autosomal dominant cerebellar ataxia type I. MRI-based volumetry of posterior fossa structures and basal ganglia in spinocerebellar ataxia types 1, 2 and 3. Brain. 1998;121(Pt 9):1687–93.

    Article  PubMed  Google Scholar 

  45. Bowman AB, Lam YC, Jafar-Nejad P, Chen HK, Richman R, Samaco RC, et al. Duplication of Atxn1l suppresses SCA1 neuropathology by decreasing incorporation of polyglutamine-expanded ataxin-1 into native complexes. Nat Genet. 2007;39(3):373–9.

    Article  PubMed  CAS  Google Scholar 

  46. Burright EN, Clark HB, Servadio A, Matilla T, Feddersen RM, Yunis WS, et al. SCA1 transgenic mice: a model for neurodegeneration caused by an expanded CAG trinucleotide repeat. Cell. 1995;82(6):937–48.

    Article  PubMed  CAS  Google Scholar 

  47. Clark HB, Orr HT. Spinocerebellar ataxia type 1—modeling the pathogenesis of a polyglutamine neurodegenerative disorder in transgenic mice. J Neuropathol Exp Neurol. 2000;59(4):265–70.

    PubMed  CAS  Google Scholar 

  48. Lam YC, Bowman AB, Jafar-Nejad P, Lim J, Richman R, Fryer JD, et al. ATAXIN-1 interacts with the repressor Capicua in its native complex to cause SCA1 neuropathology. Cell. 2006;127(7):1335–47.

    Article  PubMed  CAS  Google Scholar 

  49. Yamada M, Sato T, Tsuji S, Takahashi H. CAG repeat disorder models and human neuropathology: similarities and differences. Acta Neuropathol. 2008;115(1):71–86.

    Article  PubMed  CAS  Google Scholar 

  50. Giovannoni R, Maggio N, Rosaria Bianco M, Cavaliere C, Cirillo G, Lavitrano M, et al. Reactive astrocytosis and glial glutamate transporter clustering are early changes in a spinocerebellar ataxia type 1 transgenic mouse model. Neuron Glia Biol. 2007;3(4):335–51.

    Article  PubMed  Google Scholar 

  51. Lin X, Antalffy B, Kang D, Orr HT, Zoghbi HY. Polyglutamine expansion down-regulates specific neuronal genes before pathologic changes in SCA1. Nat Neurosci. 2000;3(2):157–63.

    Article  PubMed  CAS  Google Scholar 

  52. Serra HG, Byam CE, Lande JD, Tousey SK, Zoghbi HY, Orr HT. Gene profiling links SCA1 pathophysiology to glutamate signaling in Purkinje cells of transgenic mice. Hum Mol Genet. 2004;13(20):2535–43.

    Article  PubMed  CAS  Google Scholar 

  53. Brochu G, Maler L, Hawkes R. Zebrin II: a polypeptide antigen expressed selectively by Purkinje cells reveals compartments in rat and fish cerebellum. J Comp Neurol. 1990;291(4):538–52.

    Article  PubMed  CAS  Google Scholar 

  54. Hawkes R, Herrup K. Aldolase C/zebrin II and the regionalization of the cerebellum. J Mol Neurosci. 1995;6(3):147–58.

    Article  PubMed  CAS  Google Scholar 

  55. Leclerc N, Dore L, Parent A, Hawkes R. The compartmentalization of the monkey and rat cerebellar cortex: zebrin I and cytochrome oxidase. Brain Res. 1990;506(1):70–8.

    Article  PubMed  CAS  Google Scholar 

  56. Leclerc N, Schwarting GA, Herrup K, Hawkes R, Yamamoto M. Compartmentation in mammalian cerebellum: zebrin II and P-path antibodies define three classes of sagittally organized bands of Purkinje cells. Proc Natl Acad Sci USA. 1992;89(11):5006–10.

    Article  PubMed  CAS  Google Scholar 

  57. Pakan JM, Iwaniuk AN, Wylie DR, Hawkes R, Marzban H. Purkinje cell compartmentation as revealed by zebrin II expression in the cerebellar cortex of pigeons (Columba livia). J Comp Neurol. 2007;501(4):619–30.

    Article  PubMed  CAS  Google Scholar 

  58. Sillitoe RV, Kunzle H, Hawkes R. Zebrin II compartmentation of the cerebellum in a basal insectivore, the Madagascan hedgehog tenrec Echinops telfairi. J Anat. 2003;203(3):283–96.

    Article  PubMed  Google Scholar 

  59. Sillitoe RV, Malz CR, Rockland K, Hawkes R. Antigenic compartmentation of the primate and tree shrew cerebellum: a common topography of zebrin II in Macaca mulatta and Tupaia belangeri. J Anat. 2004;204(4):257–69.

    Article  PubMed  Google Scholar 

  60. Buono P, D’Armiento FP, Terzi G, Alfieri A, Salvatore F. Differential distribution of aldolase A and C in the human central nervous system. J Neurocytol. 2001;30(12):957–65.

    Article  PubMed  CAS  Google Scholar 

  61. Armstrong CL, Hawkes R. Pattern formation in the cerebellar cortex. Biochem Cell Biol. 2000;78(5):551–62.

    Article  PubMed  CAS  Google Scholar 

  62. Pijpers A, Voogd J, Ruigrok TJ. Topography of olivo-cortico-nuclear modules in the intermediate cerebellum of the rat. J Comp Neurol. 2005;492(2):193–213.

    Article  PubMed  Google Scholar 

  63. Sugihara I, Quy PN. Identification of aldolase C compartments in the mouse cerebellar cortex by olivocerebellar labeling. J Comp Neurol. 2007;500(6):1076–92.

    Article  PubMed  CAS  Google Scholar 

  64. Sugihara I, Shinoda Y. Molecular, topographic, and functional organization of the cerebellar cortex: a study with combined aldolase C and olivocerebellar labeling. J Neurosci. 2004;24(40):8771–85.

    Article  PubMed  CAS  Google Scholar 

  65. Eccles J, Llinas R, Sasaki K. Excitation of cerebellar Purkinje cells by the climbing fibres. Nature. 1964;203:245–6.

    Article  PubMed  CAS  Google Scholar 

  66. Kazantsev VB, Nekorkin VI, Makarenko VI, Llinas R. Olivo-cerebellar cluster-based universal control system. Proc Natl Acad Sci USA. 2003;100(22):13064–8.

    Article  PubMed  CAS  Google Scholar 

  67. Llinas R, Leznik E, Makarenko VI. On the amazing olivocerebellar system. Ann NY Acad Sci. 2002;978:258–72.

    Article  PubMed  CAS  Google Scholar 

  68. Llinas R, Nicholson C. Reversal properties of climbing fiber potential in cat Purkinje cells: an example of a distributed synapse. J Neurophysiol. 1976;39(2):311–23.

    PubMed  CAS  Google Scholar 

  69. Llinas RR. Inferior olive oscillation as the temporal basis for motricity and oscillatory reset as the basis for motor error correction. Neuroscience. 2009;162(3):797–804.

    Article  PubMed  CAS  Google Scholar 

  70. Sugihara I, Lang EJ, Llinas R. Serotonin modulation of inferior olivary oscillations and synchronicity: a multiple-electrode study in the rat cerebellum. Eur J Neurosci. 1995;7(4):521–34.

    Article  PubMed  CAS  Google Scholar 

  71. Welsh JP, Lang EJ, Suglhara I, Llinas R. Dynamic organization of motor control within the olivocerebellar system. Nature. 1995;374(6521):453–7.

    Article  PubMed  CAS  Google Scholar 

  72. Yamamoto T, Fukuda M, Llinas R. Bilaterally synchronous complex spike Purkinje cell activity in the mammalian cerebellum. Eur J Neurosci. 2001;13(2):327–39.

    Article  PubMed  CAS  Google Scholar 

  73. Sugihara I, Lang EJ, Llinas R. Uniform olivocerebellar conduction time underlies Purkinje cell complex spike synchronicity in the rat cerebellum. J Physiol. 1993;470:243–71.

    PubMed  CAS  Google Scholar 

  74. Welsh JP, Llinas R. Some organizing principles for the control of movement based on olivocerebellar physiology. Prog Brain Res. 1997;114:449–61.

    Article  PubMed  CAS  Google Scholar 

  75. Sugihara I, Marshall SP, Lang EJ. Relationship of complex spike synchrony bands and climbing fiber projection determined by reference to aldolase C compartments in crus IIa of the rat cerebellar cortex. J Comp Neurol. 2007;501(1):13–29.

    Article  PubMed  CAS  Google Scholar 

  76. Lang EJ. Organization of olivocerebellar activity in the absence of excitatory glutamatergic input. J Neurosci. 2001;21(5):1663–75.

    PubMed  CAS  Google Scholar 

  77. Lang EJ. GABAergic and glutamatergic modulation of spontaneous and motor-cortex-evoked complex spike activity. J Neurophysiol. 2002;87(4):1993–2008.

    PubMed  CAS  Google Scholar 

  78. Blenkinsop TA, Lang EJ. Block of inferior olive gap junctional coupling decreases Purkinje cell complex spike synchrony and rhythmicity. J Neurosci. 2006;26(6):1739–48.

    Article  PubMed  CAS  Google Scholar 

  79. Marshall SP, Lang EJ. Inferior olive oscillations gate transmission of motor cortical activity to the cerebellum. J Neurosci. 2004;24(50):11356–67.

    Article  PubMed  CAS  Google Scholar 

  80. Serra HG, Duvick L, Zu T, Carlson K, Stevens S, Jorgensen N, et al. RORalpha-mediated Purkinje cell development determines disease severity in adult SCA1 mice. Cell. 2006;127(4):697–708.

    Article  PubMed  CAS  Google Scholar 

  81. Duenas AM, Goold R, Giunti P. Molecular pathogenesis of spinocerebellar ataxias. Brain. 2006;129(Pt 6):1357–70.

    Article  PubMed  Google Scholar 

  82. Ross CA, Poirier MA. Protein aggregation and neurodegenerative disease. Nat Med. 2004;10(Suppl):S10–7.

    Article  PubMed  Google Scholar 

  83. Skinner PJ, Vierra-Green CA, Clark HB, Zoghbi HY, Orr HT. Altered trafficking of membrane proteins in Purkinje cells of SCA1 transgenic mice. Am J Pathol. 2001;159(3):905–13.

    Article  PubMed  CAS  Google Scholar 

  84. Lang EJ, Sugihara I, Llinas R. GABAergic modulation of complex spike activity by the cerebellar nucleoolivary pathway in rat. J Neurophysiol. 1996;76(1):255–75.

    PubMed  CAS  Google Scholar 

  85. Della Nave R, Ginestroni A, Tessa C, Salvatore E, De Grandis D, Plasmati R, et al. Brain white matter damage in SCA1 and SCA2. An in vivo study using voxel-based morphometry, histogram analysis of mean diffusivity and tract-based spatial statistics. Neuroimage. 2008;43(1):10–9.

    Article  PubMed  Google Scholar 

  86. Guerrini L, Lolli F, Ginestroni A, Belli G, Della Nave R, Tessa C, et al. Brainstem neurodegeneration correlates with clinical dysfunction in SCA1 but not in SCA2. A quantitative volumetric, diffusion and proton spectroscopy MR study. Brain. 2004;127(Pt 8):1785–95.

    Article  PubMed  CAS  Google Scholar 

  87. Akkal D, Dum RP, Strick PL. Supplementary motor area and presupplementary motor area: targets of basal ganglia and cerebellar output. J Neurosci. 2007;27(40):10659–73.

    Article  PubMed  CAS  Google Scholar 

  88. Dum RP, Strick PL. An unfolded map of the cerebellar dentate nucleus and its projections to the cerebral cortex. J Neurophysiol. 2003;89(1):634–9.

    Article  PubMed  Google Scholar 

  89. Hoover JE, Strick PL. The organization of cerebellar and basal ganglia outputs to primary motor cortex as revealed by retrograde transneuronal transport of herpes simplex virus type 1. J Neurosci. 1999;19(4):1446–63.

    PubMed  CAS  Google Scholar 

  90. Kelly RM, Strick PL. Cerebellar loops with motor cortex and prefrontal cortex of a nonhuman primate. J Neurosci. 2003;23(23):8432–44.

    PubMed  CAS  Google Scholar 

  91. Middleton FA, Strick PL. Cerebellar output channels. Int Rev Neurobiol. 1997;41:61–82.

    Article  PubMed  CAS  Google Scholar 

  92. Middleton FA, Strick PL. Dentate output channels: motor and cognitive components. Prog Brain Res. 1997;114:553–66.

    Article  PubMed  CAS  Google Scholar 

  93. Schmahmann JD. Disorders of the cerebellum: ataxia, dysmetria of thought, and the cerebellar cognitive affective syndrome. J Neuropsychiatry Clin Neurosci. 2004;16(3):367–78.

    Article  PubMed  Google Scholar 

  94. Schmahmann JD, Caplan D. Cognition, emotion and the cerebellum. Brain. 2006;129(Pt 2):290–2.

    PubMed  Google Scholar 

  95. Della Nave R, Foresti S, Tessa C, Moretti M, Ginestroni A, Gavazzi C, et al. ADC mapping of neurodegeneration in the brainstem and cerebellum of patients with progressive ataxias. Neuroimage. 2004;22(2):698–705.

    Article  PubMed  Google Scholar 

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Acknowledgments

We want to thank Mr. R. Lyons for technical help in performing the scan sessions, Ms. N. Sansone for assisting in the generation of anatomical ROIs, and Ms. N. Lobo for assisting in primary MRI analysis. Special thanks go to Dr. Christian Hansel for his valuable comments. The work was supported by grants from the Center for Integrative Neuroscience and Neuroengineering Research (CINNR), NIH RO1-NS-54942, and the James McDonnell Foundation (NRG group).

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The authors declare no conflict of interest.

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Solodkin, A., Peri, E., Chen, E.E. et al. Loss of Intrinsic Organization of Cerebellar Networks in Spinocerebellar Ataxia Type 1: Correlates with Disease Severity and Duration. Cerebellum 10, 218–232 (2011). https://doi.org/10.1007/s12311-010-0214-5

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