Brain Structure and Function

, Volume 218, Issue 4, pp 943–950 | Cite as

Superior temporal gyrus thickness correlates with cognitive performance in multiple sclerosis

  • Asaf Achiron
  • Joab Chapman
  • Sigal Tal
  • Eran Bercovich
  • Hararai Gil
  • Anat Achiron
Original Article

Abstract

Decreased cortical thickness that signifies gray matter pathology and its impact on cognitive performance is a research field with growing interest in relapsing–remitting multiple sclerosis (RRMS) and needs to be further elucidated. Using high-field 3.0 T MRI, three-dimensional T1-FSPGR (voxel size 1 × 1 × 1 mm) cortical thickness was measured in 82 regions in the left hemisphere (LH) and right hemisphere (RH) in 20 RRMS patients with low disease activity and in 20 age-matched healthy subjects that in parallel underwent comprehensive cognitive evaluation. The correlation between local cortical atrophy and cognitive performance was examined. We identified seven regions with cortical tissue loss that differed between RRMS and age-matched healthy controls. These regions were mainly located in the frontal and temporal lobes, specifically within the gyrus rectus, inferior frontal sulcus, orbital gyrus, parahippocampal gyrus, and superior temporal gyrus, with preferential left asymmetry. Increased cortical thickness was identified in two visual sensory regions, the LH inferior occipital gyrus, and the RH cuneus, implicating adaptive plasticity. Correlation analysis demonstrated that only the LH superior temporal gyrus thickness was associated with cognitive performance and its thickness correlated with motor skills (r = 0.65, p = 0.003), attention (r = 0.45, p = 0.042), and information processing speed (r = 0.50, p = 0.025). Our findings show that restricted cortical thinning occurs in RRMS patients with mild disease and that LH superior temporal gyrus atrophy is associated with cognitive dysfunction.

Keywords

Multiple sclerosis Cortical thickness MRI Cognitive performance Superior temporal gyrus 

References

  1. Achiron A, Gicquel S, Miron S, Faibel M (2002) Brain MRI lesion load quantification in multiple sclerosis: a comparison between automated multispectral and semi-automated thresholding computer-assisted techniques. Magn Reson Imaging 20:713–720PubMedCrossRefGoogle Scholar
  2. Achiron A, Doniger GM, Harel Y, Appleboim-Gavish N, Lavie M, Simon ES (2007) Prolonged response times characterize cognitive performance in multiple sclerosis. Eur J Neurol 14:1102–1108PubMedCrossRefGoogle Scholar
  3. Amato MP, Bartolozzi ML, Zipoli V, Portaccio E, Mortilla M, Guidi L, Siracusa G, Sorbi S, Federico A, De Stefano N (2004) Neocortical volume decrease in relapsing–remitting MS patients with mild cognitive impairment. Neurology 63:89–93PubMedCrossRefGoogle Scholar
  4. Amato MP, Portaccio E, Goretti B, Zipoli V, Battaglini M, Bartolozzi ML, Stromillo ML, Guidi L, Siracusa G, Sorbi S, Federico A, De Stefano N (2007) Association of neocortical volume changes with cognitive deterioration in relapsing–remitting multiple sclerosis. Arch Neurol 64:1157–1161PubMedCrossRefGoogle Scholar
  5. Anderson BJ, Eckburg PB, Relucio KI (2002) Alterations in the thickness of motor cortical subregions after motor-skill learning and exercise. Learn Mem 9:1–9PubMedCrossRefGoogle Scholar
  6. Audoin B, Ibarrola D (2005) Functional MRI study of PASAT in normal subjects. MAGMA 18:96–102PubMedCrossRefGoogle Scholar
  7. Bozzali M, Cercignani M, Sormani MP, Comi G, Filippi M (2002) Quantification of brain gray matter damage in different MS phenotypes by use of diffusion tensor MR imaging. AJNR Am J Neuroradiol 23:985–988PubMedGoogle Scholar
  8. Brunet E, Sarfati Y, Hardy-Bayle MC, Decety J (2000) A PET investigation of the attribution of intentions with a nonverbal task. Neuroimage 11:157–166PubMedCrossRefGoogle Scholar
  9. Calabrese M, Atzori M, Bernardi V, Morra A, Romualdi C, Rinaldi L, McAuliffe MJ, Barachino L, Perini P, Fischl B, Battistin L, Gallo P (2007) Cortical atrophy is relevant in multiple sclerosis at clinical onset. J Neurol 254:1212–1220PubMedCrossRefGoogle Scholar
  10. Calabrese M, Rinaldi F, Mattisi I, Grossi P, Favaretto A, Atzori M, Bernardi V, Barachino L, Romualdi C, Rinaldi L, Perini P, Gallo P (2010) Widespread cortical thinning characterizes patients with MS with mild cognitive impairment. Neurology 7:321–328CrossRefGoogle Scholar
  11. Chard DT, Griffin CM, Rashid W, Davies GR, Altmann DR, Kapoor R, Barker GJ, Thompson AJ, Miller DH (2004) Progressive grey matter atrophy in clinically early relapsing–remitting multiple sclerosis. Mult Scler 10:387–391PubMedCrossRefGoogle Scholar
  12. Demerens C, Stankoff B, Logak M, Anglade P, Allinquant B, Couraud F, Zalc B, Lubetzki C (1996) Induction of myelination in the central nervous system by electrical activity. Proc Natl Acad Sci USA 93:9887–9892PubMedCrossRefGoogle Scholar
  13. Draganski B, Gaser C, Busch V, Schuierer G, Bogdahn U, May A (2004) Neuroplasticity: changes in grey matter induced by training. Nature 427:311–312PubMedCrossRefGoogle Scholar
  14. Ge Y, Grossman RI, Udupa JK, Babb JS, Kolson DL, McGowan JC (2001) Magnetization transfer ratio histogram analysis of gray matter in relapsing–remitting multiple sclerosis. AJNR Am J Neuroradiol 22:470–475PubMedGoogle Scholar
  15. Geurts JJ, Barkhof F (2008) Grey matter pathology in multiple sclerosis. Lancet Neurol 7:841–851PubMedCrossRefGoogle Scholar
  16. Geuze E, Westenberg HG, Heinecke A, de Kloet CS, Goebel R, Vermetten E (2008) Thinner prefrontal cortex in veterans with posttraumatic stress disorder. Neuroimage 41:675–681PubMedCrossRefGoogle Scholar
  17. Goldberg II, Harel M, Malach R (2006) When the brain loses its self: prefrontal inactivation during sensorimotor processing. Neuron 50:329–339PubMedCrossRefGoogle Scholar
  18. Haidar H, Soul JS (2006) Measurement of cortical thickness in 3D brain MRI data: validation of the Laplacian method. J Neuroimaging 16:146–153PubMedCrossRefGoogle Scholar
  19. Inglese M, Ge Y, Filippi M, Falini A, Grossman RI, Gonen O (2004) Indirect evidence for early widespread gray matter involvement in relapsing–remitting multiple sclerosis. Neuroimage 21:1825–1829PubMedCrossRefGoogle Scholar
  20. Kurtzke JF (2008) Historical and clinical perspectives of the expanded disability status scale. Neuroepidemiology 31:1–9PubMedCrossRefGoogle Scholar
  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 31:572–584PubMedCrossRefGoogle Scholar
  22. Maguire EA, Mummery CJ (1999) Differential modulation of a common memory retrieval network revealed by positron emission tomography. Hippocampus 9:54–61PubMedCrossRefGoogle Scholar
  23. Moll J, de Oliveira-Souza R, Eslinger PJ, Bramati IE, Mourão-Miranda J, Andreiuolo PA, Pessoa L (2002) The neural correlates of moral sensitivity: a functional magnetic resonance imaging investigation of basic and moral emotions. J Neurosci 22:2730–2736PubMedGoogle Scholar
  24. Morgen K, Sammer G, Courtney SM, Wolters T, Melchior H, Blecker CR, Oschmann P, Kaps M, Vaitl D (2006) Evidence for a direct association between cortical atrophy and cognitive impairment in relapsing–remitting MS. Neuroimage 30:891–898PubMedCrossRefGoogle Scholar
  25. Pan JW, Krupp LB, Elkins LE, Coyle PK (2001) Cognitive dysfunction lateralizes with NAA in multiple sclerosis. Appl Neuropsychol 8:155–160PubMedCrossRefGoogle Scholar
  26. Pelvig DP, Pakkenberg H, Stark AK, Pakkenberg B (2008) Neocortical glial cell numbers in human brains. Neurobiol Aging 29:1754–1762PubMedCrossRefGoogle Scholar
  27. Pozzilli C, Passafiume D, Bernardi S, Pantano P, Incoccia C, Bastianello S, Bozzao L, Lenzi GL, Fieschi C (1991) SPECT, MRI and cognitive functions in multiple sclerosis. J Neurol Neurosurg Psychiatry 54:110–115PubMedCrossRefGoogle Scholar
  28. Pozzilli C, Fieschi C, Perani D, Paulesu E, Comi G, Bastianello S, Bernardi S, Bettinardi V, Bozzao L, Canal N (1992) Relationship between corpus callosum atrophy and cerebral metabolic asymmetries in multiple sclerosis. J Neurol Sci 112:51–57PubMedCrossRefGoogle Scholar
  29. Price JL (2007) Definition of the orbital cortex in relation to specific connections with limbic and visceral structures and other cortical regions. Ann N Y Acad Sci 1121:54–71PubMedCrossRefGoogle Scholar
  30. Prinster A, Quarantelli M, Orefice G, Lanzillo R, Brunetti A, Mollica C, Salvatore E, Morra VB, Coppola G, Vacca G, Alfano B, Salvatore M (2006) Grey matter loss in relapsing–remitting multiple sclerosis: a voxel-based morphometry study. Neuroimage 29:859–867PubMedCrossRefGoogle Scholar
  31. Rocca MA, Pagani E, Ghezzi A, Falini A, Zaffaroni M, Colombo B, Scotti G, Comi G, Filippi M (2003) Functional cortical changes in patients with multiple sclerosis and nonspecific findings on conventional magnetic resonance imaging scans of the brain. Neuroimage 19:826–836PubMedCrossRefGoogle Scholar
  32. Rudick RA, Trapp BD (2009) Gray-matter injury in multiple sclerosis. N Engl J Med 361:1505–1506PubMedCrossRefGoogle Scholar
  33. Sailer M, Fischl B, Salat D, Tempelmann C, Schönfeld MA, Busa E, Bodammer N, Heinze HJ, Dale A (2003) Focal thinning of the cerebral cortex in multiple sclerosis. Brain 126:1734–1744PubMedCrossRefGoogle Scholar
  34. Schaechter JD, Moore CI, Connell BD, Rosen BR, Dijkhuizen RM (2006) Structural and functional plasticity in the somatosensory cortex of chronic stroke patients. Brain 129:2722–2733PubMedCrossRefGoogle Scholar
  35. Sfagos C, Papageorgiou CC, Kosma KK, Kodopadelis E, Uzunoglu NK, Vassilopoulos D, Rabavilas AD (2003) Working memory deficits in multiple sclerosis: a controlled study with auditory P600 correlates. J Neurol Neurosurg Psychiatry 74:1231–1235PubMedCrossRefGoogle Scholar
  36. Smith AM, Walker LA, Freedman MS, DeMeulemeester C, Hogan MJ, Cameron I (2009) fMRI investigation of disinhibition in cognitively impaired patients with multiple sclerosis. J Neurol Sci 281:58–63PubMedCrossRefGoogle Scholar
  37. Staffen W, Mair A, Zauner H, Unterrainer J, Niederhofer H, Kutzelnigg A, Ritter S, Golaszewski S, Iglseder B, Ladurner G (2002) Cognitive function and fMRI in patients with multiple sclerosis: evidence for compensatory cortical activation during an attention task. Brain 125:1275–1282PubMedCrossRefGoogle Scholar
  38. Tekok-Kilic A, Benedict RH, Weinstock-Guttman B, Dwyer MG, Carone D, Srinivasaraghavan B, Yella V, Abdelrahman N, Munschauer F, Bakshi R, Zivadinov R (2007) Independent contributions of cortical gray matter atrophy and ventricle enlargement for predicting neuropsychological impairment in multiple sclerosis. Neuroimage 36:1294–1300PubMedCrossRefGoogle Scholar
  39. Tiberio M, Chard DT, Altmann DR, Davies G, Griffin CM, Rashid W, Sastre-Garriga J, Thompson AJ, Miller DH (2005) Gray and white matter volume changes in early RRMS: a 2-year longitudinal study. Neurology 64:1001–1007PubMedCrossRefGoogle Scholar
  40. Vercellino M, Plano F, Votta B, Mutani R, Giordana MT, Cavalla P (2005) Grey matter pathology in multiple sclerosis. J Neuropathol Exp Neurol 64:1101–1107PubMedCrossRefGoogle Scholar
  41. Zivadinov R, Minagar A (2009) Evidence for gray matter pathology in multiple sclerosis: a neuroimaging approach. J Neurol Sci 282:1–4PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  • Asaf Achiron
    • 1
  • Joab Chapman
    • 1
  • Sigal Tal
    • 2
  • Eran Bercovich
    • 3
  • Hararai Gil
    • 3
  • Anat Achiron
    • 3
  1. 1.Department of Neurology, Multiple Sclerosis Center, Sheba Medical Center, Sackler School of MedicineTel-Aviv UniversityTel-HashomerIsrael
  2. 2.Department of Radiology, Sheba Medical Center, Sackler School of MedicineTel-Aviv UniversityTel-HashomerIsrael
  3. 3.Multiple Sclerosis Center, Sheba Medical Center, Sackler School of MedicineTel-Aviv UniversityTel-HashomerIsrael

Personalised recommendations