Brain Imaging and Behavior

, Volume 13, Issue 5, pp 1292–1301 | Cite as

The impact of localized grey matter damage on neighboring connectivity: posterior cortical atrophy and the visual network

  • Haya Glick-Shames
  • Yael Backner
  • Atira Bick
  • Noa Raz
  • Netta LevinEmail author
Original Research


Posterior cortical atrophy (PCA), a localized neurodegenerative syndrome involving the occipito-parietal cortices, can serve as a good model to elaborate on the consequence of a localized damage on the anatomical and functional connectivity within an affected system. Ten PCA patients and 14 aged-matched controls were enrolled. Structural connectivity was measured via Diffusion Tensor Imaging (DTI) and probabilistic tractography. The optic tracts and radiations and the splenial fibers were delineated and their microstructural properties were evaluated. Functional connectivity was measured by resting state functional MRI (rsfMRI). Voxel-based morphometry (VBM) was used to assess atrophy. Dorsal stream visual functions were tested and correlation between these behavioral data, volume measures, white matter integrity and connectivity were examined. Impaired white matter integrity was evident in patients’ optic radiations and occipito-callosal fibers, in the segments located in close proximity to the occipital cortex, suggesting a localized damage. Degeneration did not proceed to the optic tracts, opposing trans-synaptic changes. rsfMRI revealed reduced connectivity within the visual network and between the visual and other related areas such as the frontal eye field. Correlations were found between grey matter volume and spatial perception abilities and between the integrity of the affected fibers and motion perception. White matter involvement in PCA seems to be grey matter dependent. Functional connectivity, on the other hand, showed a more diffuse pattern of damage. Correlations were found between the integrity of the affected fibers and patients’ visual abilities suggesting that fiber integrity plays a role in determining behavioral manifestation.


Diffusion tensor imaging Functional connectivity Motion perception Resting state fMRI and visual cortex 


Compliance with ethical standards

Author disclosures

Haya Glick Shames – Reports no disclosures.

Yael Backner- Reports no disclosures.

Atira Bick - Reports no disclosures.

Noa Raz– Reports no disclosures.

Netta Levin- Reports no disclosures.

Ethics committee

The study was approved by the Helsinki Committee of Hadassah Hospital.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Supplementary material

11682_2018_9952_MOESM1_ESM.docx (35 kb)
ESM 1 (DOCX 34 kb)


  1. Alegret, M., Boada-Rovira, M., Vinyes-Junqué, G., Valero, S., Espinosa, A., Hernández, I., Modinos, G., Rosende-Roca, M., Mauleón, A., Becker, J. T., & Tárraga, L. (2009). Detection of visuoperceptual deficits in preclinical and mild Alzheimer's disease. Journal of Clinical and Experimental Neuropsychology, 31(7), 860–867.CrossRefGoogle Scholar
  2. Alves, J., Soares, J. M., Sampaio, A., & Goncalves, O. F. (2013). Posterior cortical atrophy and Alzheimer's disease: a meta-analytic review of neuropsychological and brain morphometry studies. Brain Imaging and Behavior, 7(3), 353–361. Scholar
  3. Balachandar, R., John, J. P., Saini, J., Kumar, K. J., Joshi, H., Sadanand, S., Aiyappan, S., Sivakumar, P. T., Loganathan, S., Varghese, M., & Bharath, S. (2015). A study of structural and functional connectivity in early Alzheimer's disease using rest fMRI and diffusion tensor imaging. International Journal of Geriatric Psychiatry, 30(5), 497–504. Scholar
  4. Bartzokis, G. (2004). Age-related myelin breakdown: a developmental model of cognitive decline and Alzheimer's disease. Neurobiology of Aging, 25(1), 5–18 author reply 49-62.CrossRefGoogle Scholar
  5. Benson, D. F., Davis, R. J., & Snyder, B. D. (1988). Posterior cortical atrophy. Archives of Neurology, 45(7), 789–793.CrossRefGoogle Scholar
  6. Braddick, O., Atkinson, J., & Wattam-Bell, J. (2003). Normal and anomalous development of visual motion processing: motion coherence and ‘dorsal-stream vulnerability’. Neuropsychologia, 41(13), 1769–1784.CrossRefGoogle Scholar
  7. Burns, J. M., Church, J. A., Johnson, D. K., Xiong, C., Marcus, D., Fotenos, A. F., Snyder, A. Z., Morris, J. C., & Buckner, R. L. (2005). White matter lesions are prevalent but differentially related with cognition in aging and early Alzheimer disease. Archives of Neurology, 62(12), 1870–1876. Scholar
  8. Canu, E., Frisoni, G. B., Agosta, F., Pievani, M., Bonetti, M., & Filippi, M. (2012). Early and late onset Alzheimer's disease patients have distinct patterns of white matter damage. Neurobiology of Aging, 33(6), 1023–1033. Scholar
  9. Caso, F., Agosta, F., Mattavelli, D., Migliaccio, R., Canu, E., Magnani, G., Marcone, A., Copetti, M., Falautano, M., Comi, G., Falini, A., & Filippi, M. (2015). White matter degeneration in atypical Alzheimer disease. Radiology, 277(1), 162–172. Scholar
  10. Caso, F., Agosta, F., & Filippi, M. (2016). Insights into white matter damage in Alzheimer's disease: from postmortem to in vivo diffusion tensor MRI studies. Neurodegenerative Diseases, 16(1–2), 26–33. Scholar
  11. Cerami, C., Crespi, C., Della Rosa, P. A., Dodich, A., Marcone, A., Magnani, G., Coppi, E., Falini, A., Cappa, S. F., & Perani, D. (2015). Brain changes within the visuo-spatial attentional network in posterior cortical atrophy. Journal of Alzheimer's Disease, 43(2), 385–395. CrossRefGoogle Scholar
  12. Crutch, S. J., Schott, J. M., Rabinovici, G. D., Murray, M., Snowden, J. S., van der Flier, W. M., et al. (2017). Consensus classification of posterior cortical atrophy. Alzheimer's & Dementia, 13, 870884.CrossRefGoogle Scholar
  13. Csete, G., Szabo, N., Rokszin, A., Toth, E., Braunitzer, G., Benedek, G., et al. (2014). An investigation of the white matter microstructure in motion detection using diffusion MRI. Brain Research, 1570, 35–42. Scholar
  14. de la Monte, S. M. (1989). Quantitation of cerebral atrophy in preclinical and end-stage Alzheimer's disease. Annals of Neurology, 25(5), 450–459. Scholar
  15. Della Sala, S., Laiacona, M., Trivelli, C., & Spinnler, H. (1995). Poppelreuter-Ghent's overlapping figures test: its sensitivity to age, and its clinical use. Archives of Clinical Neuropsychology, 10(6), 511–534. Scholar
  16. Evans, A. C., Collins, D. L., Mills, S. R., Brown, E. D., Kelly, R. L., & Peters, T. M. (1993). 3D statistical neuroanatomical models from 305 MRI volumes. 1993 IEEE Conference Record Nuclear Science Symposium and Medical Imaging Conference. 31 Oct-6 Nov 1993, 3, 1813–1817.CrossRefGoogle Scholar
  17. Frisoni, G. B., Pievani, M., Testa, C., Sabattoli, F., Bresciani, L., Bonetti, M., Beltramello, A., Hayashi, K. M., Toga, A. W., & Thompson, P. M. (2007). The topography of grey matter involvement in early and late onset Alzheimer's disease. Brain, 130(Pt 3), 720–730. CrossRefGoogle Scholar
  18. Gollin, E. S. (1960). Developmental studies of visual recognition of incomplete objects. Perceptual and Motor Skills, 11, 289–298. Scholar
  19. Gress, D. R. (2001). Aging and dementia: more gray hair and less gray matter. AJNR. American Journal of Neuroradiology, 22(9), 1641–1642.Google Scholar
  20. Greve, K. W., Lindberg, R. F., Bianchini, K. J., & Adams, D. (2000). Construct validity and predictive value of the Hooper visual organization test in stroke rehabilitation. Applied Neuropsychology, 7(4), 215–222. Scholar
  21. Hof, P. R., Vogt, B. A., Bouras, C., & Morrison, J. H. (1997). Atypical form of Alzheimer's disease with prominent posterior cortical atrophy: a review of lesion distribution and circuit disconnection in cortical visual pathways. Vision Research, 37(24), 3609–3625. Scholar
  22. Huang, H., Zhang, J., Jiang, H., Wakana, S., Poetscher, L., Miller, M. I., van Zijl, P. C. M., Hillis, A. E., Wytik, R., & Mori, S. (2005). DTI tractography based parcellation of white matter: application to the mid-sagittal morphology of corpus callosum. Neuroimage, 26(1), 195–205. Scholar
  23. Johansen-Berg, H. (2010). Behavioural relevance of variation in white matter microstructure. Current Opinion in Neurology, 23(4), 351–358. Google Scholar
  24. Kaeser, P. F., Ghika, J., & Borruat, F. X. (2015). Visual signs and symptoms in patients with the visual variant of Alzheimer disease. BMC Ophthalmology, 15, 65. Scholar
  25. Lacadie, C. M., Fulbright, R. K., Constable, R. T., & Papademetris, X. (2008). More accurate Talairach coordinates for neuroImaging using nonlinear registration. NeuroImage, 42(2), 717–725. Scholar
  26. Lehmann, M., Madison, C., Ghosh, P. M., Miller, Z. A., Greicius, M. D., Kramer, J. H., Coppola, G., Miller, B. L., Jagust, W. J., Gorno-Tempini, M. L., Seeley, W. W., & Rabinovici, G. D. (2015). Loss of functional connectivity is greater outside the default mode network in nonfamilial early-onset Alzheimer's disease variants. Neurobiology of Aging, 36(10), 2678–2686. Scholar
  27. Liberman, J., Stewart, W., Seines, O., & Gordon, B. (1994). Rater agreement for the Rey-Osterrieth complex figure test. Journal of Clinical Psychology, 50(4), 615–624.CrossRefGoogle Scholar
  28. Madhavan, A., Schwarz, C. G., Duffy, J. R., Strand, E. A., Machulda, M. M., Drubach, D. A., Kantarci, K., Przybelski, S. A., Reid, R. I., Senjem, M. L., Gunter, J. L., Apostolova, L. G., Lowe, V. J., Petersen, R. C., Jack, C. R., Josephs, K. A., & Whitwell, J. L. (2015). Characterizing white matter tract degeneration in syndromic variants of Alzheimer's disease: a diffusion tensor imaging study. Journal of Alzheimer's Disease, 49(3), 633–643. Scholar
  29. Migliaccio, R., Agosta, F., Scola, E., Magnani, G., Cappa, S. F., Pagani, E., Canu, E., Comi, G., Falini, A., Gorno-Tempini, M. L., Bartolomeo, P., & Filippi, M. (2012). Ventral and dorsal visual streams in posterior cortical atrophy: a DT MRI study. Neurobiology of Aging, 33(11), 2572–2584. Scholar
  30. Neitzel, J., Ortner, M., Haupt, M., Redel, P., Grimmer, T., Yakushev, I., Drzezga, A., Bublak, P., Preul, C., Sorg, C., & Finke, K. (2016). Neuro-cognitive mechanisms of simultanagnosia in patients with posterior cortical atrophy. Brain, 139(Pt 12), 3267–3280. CrossRefGoogle Scholar
  31. Pillon, B., Dubois, B., Bonnet, A., Esteguy, M., Guimaraes, J., Vigouret, J., et al. (1989). Cognitive slowing in Parkinson's disease fails to respond to levodopa treatment the 15-objects test. Neurology, 39(6), 762–762.CrossRefGoogle Scholar
  32. Raz, N., Dotan, S., Chokron, S., Ben-Hur, T., & Levin, N. (2012). Demyelination affects temporal aspects of perception: an optic neuritis study. Annals of Neurology, 71(4), 531–538. Scholar
  33. Raz, N., Bick, A. S., Ben-Hur, T., & Levin, N. (2015). Focal demyelinative damage and neighboring white matter integrity: an optic neuritis study. Multiple Sclerosis, 21(5), 562–571. Scholar
  34. Reiner, A., Yekutieli, D., & Benjamini, Y. (2003). Identifying differentially expressed genes using false discovery rate controlling procedures. Bioinformatics, 19(3), 368–375.CrossRefGoogle Scholar
  35. Shames, H., Raz, N., & Levin, N. (2015). Functional neural substrates of posterior cortical atrophy patients. Journal of Neurology, 262(7), 1751–1761. Scholar
  36. Sherbondy, A. J., Dougherty, R. F., Ben-Shachar, M., Napel, S., & Wandell, B. A. (2008). ConTrack: finding the most likely pathways between brain regions using diffusion tractography. Journal of Vision, 8(15), 1–16. Scholar
  37. Shin, M.-S., Park, S.-Y., Park, S.-R., Seol, S.-H., & Kwon, J. S. (2006). Clinical and empirical applications of the Rey–Osterrieth complex figure test. Nature Protocols, 1(2), 892–899.CrossRefGoogle Scholar
  38. Son, S. J., Kim, J., & Park, H. (2017). Structural and functional connectional fingerprints in mild cognitive impairment and Alzheimer's disease patients. PLoS One, 12(3), e0173426. Scholar
  39. Tamkin, A. S., & Jacobsen, R. (1984). Age-related norms for the Hooper visual organization test. Journal of Clinical Psychology, 40(6), 1459–1463.CrossRefGoogle Scholar
  40. Tuovinen, T., Rytty, R., Moilanen, V., Abou Elseoud, A., Veijola, J., Remes, A. M., & Kiviniemi, V. J. (2016). The effect of gray matter ICA and coefficient of variation mapping of BOLD data on the detection of functional connectivity changes in Alzheimer's disease and bvFTD. Frontiers in Human Neuroscience, 10, 680. Google Scholar
  41. Yeatman, J. D., Dougherty, R. F., Myall, N. J., Wandell, B. A., & Feldman, H. M. (2012). Tract profiles of white matter properties: automating fiber-tract quantification. PLoS One, 7(11), e49790. Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Haya Glick-Shames
    • 1
  • Yael Backner
    • 1
  • Atira Bick
    • 1
  • Noa Raz
    • 1
  • Netta Levin
    • 1
    Email author
  1. 1.fMRI lab, Neurology DepartmentHadassah-Hebrew University Medical CenterJerusalemIsrael

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