Journal of Neurology

, Volume 263, Issue 1, pp 89–99 | Cite as

The neural correlates of motor intentional disorders in patients with subcortical vascular cognitive impairment

  • Geon Ha Kim
  • Sang Won Seo
  • Kihyo Jung
  • Oh-Hun Kwon
  • Hunki Kwon
  • Jong Hun Kim
  • Jee Hoon Roh
  • Min-Jeong Kim
  • Byung Hwa Lee
  • Doo Sang Yoon
  • Jung Won Hwang
  • Jong Min Lee
  • Jee Hyang Jeong
  • Heecheon You
  • Kenneth M. Heilman
  • Duk L. Na
Original Communication


Subcortical vascular cognitive impairment (SVCI) refers to cognitive impairment associated with small vessel disease. Motor intentional disorders (MID) have been reported in patients with SVCI. However, there are no studies exploring the neuroanatomical regions related to MID in SVCI patients. The aim of this study, therefore, was to investigate the neural correlates of MID in SVCI patients. Thirty-one patients with SVCI as well as 10 healthy match control participants were included. A “Pinch-Grip” apparatus was used to quantify the force control capabilities of the index finger in four different movement phases including initiation, development, maintenance, and termination. All participants underwent magnetic resonance imaging (MRI). Topographical cortical areas and white matter tracts correlated with the performances of the four different movement phases were assessed by the surface-based morphometry and tract-based spatial statistics analyses. Poorer performance in the maintenance task was related to cortical thinning in bilateral dorsolateral prefrontal, orbitofrontal and parietal cortices, while poorer performance in the termination task was associated with the disruption of fronto-parietal cortical areas as well as the white matter tracts including splenium and association fibers such as superior longitudinal fasciculus. Our study demonstrates that cortical areas and underlying white matter tracts associated with fronto-parietal attentional system play an important role in motor impersistence and perseveration in SVCI patients.


Motor intentional disorder Subcortical vascular cognitive impairment Cortical thickness Tract-based spatial statistics 



This study was supported by a grant of the Korea Healthcare technology R&D Project, Ministry for Health, Welfare and Family Affairs, Republic of Korea (A090632), a grant of the Original Technology Research Program for Brain Science through the National Research Foundation of Korea (NRF) funded by the Korean government (MSIP) (No. 2014M3C7A1064752), by the Korean Science and Engineering Foundation (KOSEF) NRL program grant funded by the Korean government (MEST; 2011-0028333 & 2010-0014026), by Samsung Biomedical Research Institute grants (C-B0-217-3), and by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health &Welfare, Republic of Korea (HI14C3484).

Compliance with ethical standards

Ethical standards

Informed consent was obtained from all participants. The study protocol was approved by the Institutional Review Board of Samsung Medical Center.

Conflicts of interest

G. H. Kim, K. Jung, O. Kwon, H. Kwon, B. H. Lee, D. S. Yoon and J. W. Hwang report no disclosures. S. W. Seo, MD, J. H. Kim, J. H. Roh, M. J. Kim, J. H. Jeong, J. M. Lee, H. You and K. Heilman report no disclosures. D. L. Na reports no disclosures.

Supplementary material

415_2015_7946_MOESM1_ESM.doc (45 kb)
Supplementary material 1 (DOC 45 kb)


  1. 1.
    Kim SH, Park JS, Ahn HJ, Seo SW, Lee JM, Kim ST, Han SH, Na DL (2011) Voxel-based analysis of diffusion tensor imaging in patients with subcortical vascular cognitive impairment: correlates with cognitive and motor deficits. J Neuroimaging 21:317–324CrossRefPubMedGoogle Scholar
  2. 2.
    Kim CH, Seo SW, Kim GH, Shin JS, Cho H, Noh Y, Kim SH, Kim MJ, Jeon S, Yoon U, Lee JM, Oh SJ, Kim JS, Kim ST, Lee JH, Na DL (2012) Cortical thinning in subcortical vascular dementia with negative 11C-PiB PET. J Alzheimers Dis 31:315–323PubMedGoogle Scholar
  3. 3.
    Seo SW, Ahn J, Yoon U, Im K, Lee JM, Tae Kim S, Ahn HJ, Chin J, Jeong Y, Na DL (2010) Cortical thinning in vascular mild cognitive impairment and vascular dementia of subcortical type. J Neuroimag 20:37–45CrossRefGoogle Scholar
  4. 4.
    Heilman KM (2004) Intentional neglect. Front Biosci 9:694–705CrossRefPubMedGoogle Scholar
  5. 5.
    Seo SW, Jung K, You H, Lee BH, Kim GM, Chung CS, Lee KH, Na DL (2009) Motor-intentional disorders in right hemisphere stroke. Cogn Behav Neurol 22:242–248CrossRefPubMedGoogle Scholar
  6. 6.
    Yoon DS, Jung K, Kim GH, Kim SH, Lee BH, Seo SW, You H, Na DL (2014) Motor intentional disorders in vascular mild cognitive impairment and vascular dementia of subcortical type. Neurocase 20:53–60CrossRefGoogle Scholar
  7. 7.
    Chamorro A, Marshall RS, Valls-Sole J, Tolosa E, Mohr JP (1997) Motor behavior in stroke patients with isolated medial frontal ischemic infarction. Stroke 28:1755–1760CrossRefPubMedGoogle Scholar
  8. 8.
    Kertesz A, Nicholson I, Cancelliere A, Kassa K, Black SE (1985) Motor impersistence: a right-hemisphere syndrome. Neurology 35:662–666CrossRefPubMedGoogle Scholar
  9. 9.
    Inzitari D, Erkinjuntti T, Wallin A, Del Ser T, Romanelli M, Pantoni L (2000) Subcortical vascular dementia as a specific target for clinical trials. Ann N Y Acad Sci 903:510–521CrossRefPubMedGoogle Scholar
  10. 10.
    Gandola M, Toraldo A, Invernizzi P, Corrado L, Sberna M, Santilli I, Bottini G, Paulesu E (2013) How many forms of perseveration? Evidence from cancellation tasks in right hemisphere patients. Neuropsychologia 51:2960–2975CrossRefPubMedGoogle Scholar
  11. 11.
    Gmitrowicz A, Kucharska A (1994) Developmental disorders in the fourth edition of the American classification: diagnostic and statistical manual of mental disorders (DSM IV—optional book). Psychiatr Pol 28:509–521PubMedGoogle Scholar
  12. 12.
    Fazekas F, Kleinert R, Offenbacher H, Schmidt R, Kleinert G, Payer F, Radner H, Lechner H (1993) Pathologic correlates of incidental MRI white matter signal hyperintensities. Neurology 43:1683–1689CrossRefPubMedGoogle Scholar
  13. 13.
    Petersen RC (2004) Mild cognitive impairment as a diagnostic entity. J Intern Med 256:183–194CrossRefPubMedGoogle Scholar
  14. 14.
    Seo SW, Im K, Lee JM, Kim YH, Kim ST, Kim SY, Yang DW, Kim SI, Cho YS, Na DL (2007) Cortical thickness in single- versus multiple-domain amnestic mild cognitive impairment. Neuroimage 36:289–297CrossRefPubMedGoogle Scholar
  15. 15.
    Ahn HJ, Chin J, Park A, Lee BH, Suh MK, Seo SW, Na DL (2010) Seoul Neuropsychological Screening Battery-dementia version (SNSB-D): a useful tool for assessing and monitoring cognitive impairments in dementia patients. J Korean Med Sci 25:1071–1076PubMedCentralCrossRefPubMedGoogle Scholar
  16. 16.
    Kang Y, Na DL (2003) Seoul neuropsychological screening battery. Human Brain Research & Consulting Co, IncheonGoogle Scholar
  17. 17.
    Kim SH, Seo SW, Go SM, Chin J, Lee BH, Lee JH, Han SH, Na DL (2011) Pyramidal and extrapyramidal scale (PEPS): a new scale for the assessment of motor impairment in vascular cognitive impairment associated with small vessel disease. Clin Neurol Neurosurg 113:181–187CrossRefPubMedGoogle Scholar
  18. 18.
    Zijdenbos AP, Forghani R, Evans AC (2002) Automatic “pipeline” analysis of 3-D MRI data for clinical trials: application to multiple sclerosis. IEEE Trans Med Imagin 21:1280–1291CrossRefGoogle Scholar
  19. 19.
    Kabani N, Le Goualher G, MacDonald D, Evans AC (2001) Measurement of cortical thickness using an automated 3-D algorithm: a validation study. Neuroimage 13:375–380CrossRefPubMedGoogle Scholar
  20. 20.
    Lerch JP, Pruessner JC, Zijdenbos A, Hampel H, Teipel SJ, Evans AC (2005) Focal decline of cortical thickness in Alzheimer’s disease identified by computational neuroanatomy. Cereb Cortex 15:995–1001CrossRefPubMedGoogle Scholar
  21. 21.
    Lee JK, Lee JM, Kim JS, Kim IY, Evans AC, Kim SI (2006) A novel quantitative cross-validation of different cortical surface reconstruction algorithms using MRI phantom. Neuroimage 31:572–584CrossRefPubMedGoogle Scholar
  22. 22.
    Singh V, Chertkow H, Lerch JP, Evans AC, Dorr AE, Kabani NJ (2006) Spatial patterns of cortical thinning in mild cognitive impairment and Alzheimer’s disease. Brain 129:2885–2893CrossRefPubMedGoogle Scholar
  23. 23.
    Collins DL, Neelin P, Peters TM, Evans AC (1994) Automatic 3D intersubject registration of MR volumetric data in standardized Talairach space. J Comput Assist Tomogr 18:192–205CrossRefPubMedGoogle Scholar
  24. 24.
    Zijdenbos A, Evans A, Riahi F, Sled J, Chui J, Kollokian V (1996) Automatic quantification of multiple sclerosis lesion volume using stereotaxic space. Vis Biomed Comput 1131:439–448CrossRefGoogle Scholar
  25. 25.
    Sled JG, Zijdenbos AP, Evans AC (1998) A nonparametric method for automatic correction of intensity nonuniformity in MRI data. IEEE Trans Med Imagin 17:87–97CrossRefGoogle Scholar
  26. 26.
    MacDonald D, Kabani N, Avis D, Evans AC (2000) Automated 3-D extraction of inner and outer surfaces of cerebral cortex from MRI. Neuroimage 12:340–356CrossRefPubMedGoogle Scholar
  27. 27.
    Kim JS, Singh V, Lee JK, Lerch J, Ad-Dab’bagh Y, MacDonald D, Lee JM, Kim SI, Evans AC (2005) Automated 3-D extraction and evaluation of the inner and outer cortical surfaces using a Laplacian map and partial volume effect classification. Neuroimage 27:210–221CrossRefPubMedGoogle Scholar
  28. 28.
    Lerch JP, Evans AC (2005) Cortical thickness analysis examined through power analysis and a population simulation. Neuroimage 24:163–173CrossRefPubMedGoogle Scholar
  29. 29.
    Robbins S, Evans AC, Collins DL, Whitesides S (2004) Tuning and comparing spatial normalization methods. Med Image Anal 8:311–323CrossRefPubMedGoogle Scholar
  30. 30.
    Lyttelton O, Boucher M, Robbins S, Evans A (2007) An unbiased iterative group registration template for cortical surface analysis. Neuroimage 34:1535–1544CrossRefPubMedGoogle Scholar
  31. 31.
    Smith SM, Zhang Y, Jenkinson M, Chen J, Matthews PM, Federico A, De Stefano N (2002) Accurate, robust, and automated longitudinal and cross-sectional brain change analysis. Neuroimage 17:479–489CrossRefPubMedGoogle Scholar
  32. 32.
    Pierpaoli C, Basser PJ (1996) Toward a quantitative assessment of diffusion anisotropy. Magn Reson Med 36:893–906CrossRefPubMedGoogle Scholar
  33. 33.
    Basser PJ, Mattiello J, LeBihan D (1994) MR diffusion tensor spectroscopy and imaging. Biophys J 66:259–267PubMedCentralCrossRefPubMedGoogle Scholar
  34. 34.
    Genovese CR, Lazar NA, Nichols T (2002) Thresholding of statistical maps in functional neuroimaging using the false discovery rate. Neuroimage 15:870–878CrossRefPubMedGoogle Scholar
  35. 35.
    Smith SM, Nichols TE (2009) Threshold-free cluster enhancement: addressing problems of smoothing, threshold dependence and localisation in cluster inference. Neuroimage 44:83–98CrossRefPubMedGoogle Scholar
  36. 36.
    Hua K, Zhang J, Wakana S, Jiang H, Li X, Reich DS, Calabresi PA, Pekar JJ, van Zijl PC, Mori S (2008) Tract probability maps in stereotaxic spaces: analyses of white matter anatomy and tract-specific quantification. Neuroimage 39:336–347PubMedCentralCrossRefPubMedGoogle Scholar
  37. 37.
    Wakana S, Caprihan A, Panzenboeck MM, Fallon JH, Perry M, Gollub RL, Hua K, Zhang J, Jiang H, Dubey P, Blitz A, van Zijl P, Mori S (2007) Reproducibility of quantitative tractography methods applied to cerebral white matter. Neuroimage 36:630–644PubMedCentralCrossRefPubMedGoogle Scholar
  38. 38.
    Corbetta M, Shulman GL (2002) Control of goal-directed and stimulus-driven attention in the brain. Nat Rev Neurosci 3:201–215CrossRefPubMedGoogle Scholar
  39. 39.
    Fan J, McCandliss BD, Fossella J, Flombaum JI, Posner MI (2005) The activation of attentional networks. Neuroimage 26:471–479CrossRefPubMedGoogle Scholar
  40. 40.
    Lopez OL, Becker JT, Boller F (1991) Motor impersistence in Alzheimer’s disease. Cortex 27:93–99CrossRefPubMedGoogle Scholar
  41. 41.
    Passingham RE (1996) Attention to action. Philos Trans R Soc Lond B Biol Sci 351:1473–1479CrossRefPubMedGoogle Scholar
  42. 42.
    Cummings JL (1993) Frontal-subcortical circuits and human behavior. Arch Neurol 50:873–880CrossRefPubMedGoogle Scholar
  43. 43.
    Rolls ET, Grabenhorst F (2008) The orbitofrontal cortex and beyond: from affect to decision-making. Prog Neurobiol 86:216–244CrossRefPubMedGoogle Scholar
  44. 44.
    Gusnard DA, Ollinger JM, Shulman GL, Cloninger CR, Price JL, Van Essen DC, Raichle ME (2003) Persistence and brain circuitry. Proc Natl Acad Sci 100:3479–3484PubMedCentralCrossRefPubMedGoogle Scholar
  45. 45.
    Frank MJ, Claus ED (2006) Anatomy of a decision: striato-orbitofrontal interactions in reinforcement learning, decision making, and reversal. Psychol Rev 113:300–326CrossRefPubMedGoogle Scholar
  46. 46.
    Jung YC, Ku J, Namkoong K, Lee W, Kim SI, Kim JJ (2010) Human orbitofrontal-striatum functional connectivity modulates behavioral persistence. NeuroReport 21:502–506CrossRefPubMedGoogle Scholar
  47. 47.
    Rushworth MF, Johansen-Berg H, Gobel SM, Devlin JT (2003) The left parietal and premotor cortices: motor attention and selection. Neuroimage 20(Suppl 1):S89–S100CrossRefPubMedGoogle Scholar
  48. 48.
    Rushworth MF, Krams M, Passingham RE (2001) The attentional role of the left parietal cortex: the distinct lateralization and localization of motor attention in the human brain. J Cogn Neurosci 13:698–710CrossRefPubMedGoogle Scholar
  49. 49.
    Rushworth MF, Nixon PD, Renowden S, Wade DT, Passingham RE (1997) The left parietal cortex and motor attention. Neuropsychologia 35:1261–1273CrossRefPubMedGoogle Scholar
  50. 50.
    Pekkala S, Albert ML, Spiro A 3rd, Erkinjuntti T (2008) Perseveration in Alzheimer’s disease. Dement Geriatr Cogn Disord 25:109–114CrossRefPubMedGoogle Scholar
  51. 51.
    Possin KL, Filoteo JV, Roesch SC, Zizak V, Rilling LM, Davis JD (2005) Is a perseveration a perseveration? An evaluation of cognitive error types in patients with subcortical pathology. J Clin Exp Neuropsychol 27:953–966CrossRefPubMedGoogle Scholar
  52. 52.
    Paulesu E, Goldacre B, Scifo P, Cappa SF, Gilardi MC, Castiglioni I, Perani D, Fazio F (1997) Functional heterogeneity of left inferior frontal cortex as revealed by fMRI. NeuroReport 8:2011–2017CrossRefPubMedGoogle Scholar
  53. 53.
    Smith EE, Jonides J (1999) Storage and executive processes in the frontal lobes. Science 283:1657–1661CrossRefPubMedGoogle Scholar
  54. 54.
    Luria AR (1965) Two kinds of motor perseveration in massive injury of the frontal lobes. Brain 88:1–10CrossRefPubMedGoogle Scholar
  55. 55.
    Sandson J, Albert ML (1984) Varieties of perseveration. Neuropsychologia 22:715–732CrossRefPubMedGoogle Scholar
  56. 56.
    Sandson J, Albert ML (1987) Perseveration in behavioral neurology. Neurology 37:1736–1741CrossRefPubMedGoogle Scholar
  57. 57.
    Aron AR, Fletcher PC, Bullmore ET, Sahakian BJ, Robbins TW (2003) Stop-signal inhibition disrupted by damage to right inferior frontal gyrus in humans. Nat Neurosci 6:115–116CrossRefPubMedGoogle Scholar
  58. 58.
    Aron AR, Robbins TW, Poldrack RA (2004) Inhibition and the right inferior frontal cortex. Trends Cogn Sci 8:170–177CrossRefPubMedGoogle Scholar
  59. 59.
    Gusnard DA, Akbudak E, Shulman GL, Raichle ME (2001) Medial prefrontal cortex and self-referential mental activity: relation to a default mode of brain function. Proc Natl Acad Sci 98:4259–4264PubMedCentralCrossRefPubMedGoogle Scholar
  60. 60.
    Cassaday HJ, Nelson AJ, Pezze MA (2014) From attention to memory along the dorsal-ventral axis of the medial prefrontal cortex: some methodological considerations. Front Syst Neurosci 8:160PubMedCentralCrossRefPubMedGoogle Scholar
  61. 61.
    Ragozzino ME (2007) The contribution of the medial prefrontal cortex, orbitofrontal cortex, and dorsomedial striatum to behavioral flexibility. Ann N Y Acad Sci 1121:355–375CrossRefPubMedGoogle Scholar
  62. 62.
    Smith E, Salat D, Jeng J, McCreary C, Fischl B, Schmahmann J, Dickerson B, Viswanathan A, Albert M, Blacker D (2011) Correlations between MRI white matter lesion location and executive function and episodic memory. Neurology 76:1492–1499PubMedCentralCrossRefPubMedGoogle Scholar
  63. 63.
    Román GC, Kalaria RN (2006) Vascular determinants of cholinergic deficits in Alzheimer disease and vascular dementia. Neurobiol Aging 27:1769–1785CrossRefPubMedGoogle Scholar
  64. 64.
    Jensen AR, Rohwer WD Jr (1966) The stroop color-word test: a review. Acta Psychol (Amst) 25:36–93CrossRefGoogle Scholar
  65. 65.
    Polk TA, Drake RM, Jonides JJ, Smith MR, Smith EE (2008) Attention enhances the neural processing of relevant features and suppresses the processing of irrelevant features in humans: a functional magnetic resonance imaging study of the stroop task. J Neurosci 28:13786–13792PubMedCentralCrossRefPubMedGoogle Scholar
  66. 66.
    Wood AG, Saling MM, Abbott DF, Jackson GD (2001) A neurocognitive account of frontal lobe involvement in orthographic lexical retrieval: an fMRI study. Neuroimage 14:162–169CrossRefPubMedGoogle Scholar
  67. 67.
    Smith SM, Jenkinson M, Johansen-Berg H, Rueckert D, Nichols TE, Mackay CE, Watkins KE, Ciccarelli O, Cader MZ, Matthews PM, Behrens TE (2006) Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data. Neuroimage 31:1487–1505CrossRefPubMedGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Geon Ha Kim
    • 1
    • 2
    • 3
  • Sang Won Seo
    • 2
    • 4
    • 5
  • Kihyo Jung
    • 6
  • Oh-Hun Kwon
    • 7
  • Hunki Kwon
    • 7
  • Jong Hun Kim
    • 8
  • Jee Hoon Roh
    • 9
  • Min-Jeong Kim
    • 10
  • Byung Hwa Lee
    • 2
    • 4
  • Doo Sang Yoon
    • 2
    • 4
  • Jung Won Hwang
    • 11
  • Jong Min Lee
    • 7
  • Jee Hyang Jeong
    • 1
  • Heecheon You
    • 12
  • Kenneth M. Heilman
    • 13
  • Duk L. Na
    • 2
    • 4
    • 14
  1. 1.Department of NeurologyEwha Womans University Mokdong Hospital, Ewha Womans University School of MedicineSeoulKorea
  2. 2.Department of NeurologySamsung Medical Center, Sungkyunkwan University School of MedicineSeoulKorea
  3. 3.Ewha Brain Institute, Ewha Womans UniversitySeoulKorea
  4. 4.Neuroscience Center, Samsung Medical CenterSeoulKorea
  5. 5.Department of Clinical Research Design and EvaluationSAIHST, Sungkyunkwan UniversitySeoulKorea
  6. 6.School of Industrial Engineering, University of UlsanUlsanKorea
  7. 7.Department of Biomedical EngineeringHanyang UniversitySeoulKorea
  8. 8.Department of Neurology, National Health Insurance CorporationIlsan HospitalGoyangKorea
  9. 9.Department of NeurologyAsan Medical Center, University of Ulsan College of MedicineSeoulKorea
  10. 10.Department of NeurologySeoul National University Hospital Healthcare System Gangnam CenterSeoulKorea
  11. 11.Samsung Advanced Institute for Health Sciences and Technology, Sungkyunkwan UniversitySeoulKorea
  12. 12.Department of Industrial and Management EngineeringPohang University of Science and TechnologyPohangKorea
  13. 13.Department of NeurologyUniversity of Florida College of Medicine, and the Veterans Affairs Medical CenterGainesvilleUSA
  14. 14.Department of Health Sciences and TechnologySAIHST, Sungkyunkwan UniversitySeoulKorea

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