Skip to main content
SpringerLink
Log in

Proof of principle: Transformation approach alters caudate nucleus volume and structure-function associations

  • Original Research
  • Published:
Brain Imaging and Behavior Aims and scope Submit manuscript

Abstract

Brain magnetic resonance image (MRI) registration alters structure orientation, size, and/or shape. To determine whether linear registration methods (image transformation to 6, 9, and 12° of freedom) alter structural volume and cognitive associations, we examined transformation alterations to the caudate nucleus within individuals diagnosed with Parkinson’s disease (PD) and demographically matched non-PD peers. Volumes from native and six were expected be significantly different from 9 and 12° of freedom methods. Caudate nucleus volumes were expected to be associated with measures of processing speed and mental flexibility, but the strength of the association based on transformation approach was unknown. MRI brain scans from individuals with Parkinson’s disease (n = 40) and age-matched controls (n = 40) were transformed using 6, 9, and 12° of freedom to an average brain template. Correlations controlling for total intracranial volume assessed expected structural-behavioral associations. Volumetric: Raw 9 and 12° transformed volumes were significantly larger than native and 6° volumes. Only 9 and 12° volumes revealed group differences with PD less than controls. Intracranial volume considerations were essential for native and 6° between group comparisons. Structural-Behavioral: The 9 and 12° caudate nucleus volume transformations revealed the expected brain-behavioral associations. Linear registration techniques alter volumetric and cognitive-structure associations. The study highlights the need to communicate transformation approach and group intracranial volume considerations.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  • Alexander, G. E., Delong, M. R., & Strick, P. L. (1986). Parallel organization of functionally segregated circuits linking basal ganglia and cortex. Annual Review of Neuroscience, 9, 357–381.

    Article  CAS  PubMed  Google Scholar 

  • Allen, J. S., Damasio, H., & Grabowski, T. J. (2002). Normal neuroanatomical variation in the human brain: an MRI-volumetric study. American Journal of Anthropology, 118, 341–358.

    Article  Google Scholar 

  • American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders (4th ed.). Washington, DC: American Psychiatric Association.

    Google Scholar 

  • Ashburner, J., & Friston, K. J. (2000). Voxel-based morphometry—the methods. NeuroImage, 11, 805–821.

    Article  CAS  PubMed  Google Scholar 

  • Baldo, J. V., Arevalo, A., Patterson, J. P., & Dronkers, N. F. (2013). Grey and white matter correlations of picture naming: evidence from a voxel based lesion analysis of the Boston Naming Test. Cortex, 49(3), 658–667.

    Article  PubMed Central  PubMed  Google Scholar 

  • Bigler, E. D., & Tate, D. F. (2001). Brain volume, intracranial volume, and dementia. Investigations in Radiology, 36, 539–546.

    Article  CAS  Google Scholar 

  • Camicioli, R., Moore, M. M., Kinney, A., Corbridge, E., Glassberg, K., & Kaye, J. A. (2003). Parkinson’s disease is associated with hippocampal atrophy. Movement Disorders, 18(7), 784–790.

    Article  PubMed  Google Scholar 

  • Cools, R., Stefanova, E., Barker, R. A., Robbins, T. W., & Owen, A. M. (2002). Dopaminergic modulation of high level cognition in Parkinson’s disease: the role of the prefrontal cortex revealed by PET. Brain, 125, 584–594.

    Article  PubMed  Google Scholar 

  • Dagher, A., Owen, A. M., Boecker, H., & Brooks, D. J. (2001). The role of the stiatum and hippocampus in planning: a PET activation study in Parkinson’s disease. Brain, 124, 1020–1032.

    Article  CAS  PubMed  Google Scholar 

  • Evans, A. C., Janke, A. L., Collins, D. L., & Baillet, S. (2012). Brain templates and atlases. NeuroImage, 62, 911–922.

    Article  PubMed  Google Scholar 

  • Fahn, S. R. L. E., Elton, R., & UPDRS Development Committee. (1987). Unified Parkinson’s disease rating scale. Recent Developments in Parkinson’s Disease, 2, 153–163.

    Google Scholar 

  • Fischl, B. (2012). FreeSurfer. NeuroImage, 62, 774–781. doi:10.1016/j.neuroimage.2012.01.021.

    Article  PubMed Central  PubMed  Google Scholar 

  • Gitelman, D. R., Klein-Gitelman, M. S., Ying, J., Sagcal-Gironella, A. C. P., Zelko, F., Beebe, D. W., …, & Brunner, H. I. (2013). Brain morphometric changes associated with childhood-onset systemic lupus erythematosus and neurocognitve deficit. Arthritis and Rheumatism, 65, 2190–2200.

  • Goetz, C. G., Tilley, B. C., Shaftman, S. R., Stebbins, G. T., Fahn, S., Martinez-Martin, P., …, & LaPelle, N. (2008). Movement Disorder Society-sponsored revision of the Unified Parkinson’s Disease Rating Scale (MDS-UPDRS): Scale presentation and clinimetric testing results. Movement Disorders, 23, 2129–2170.

  • Grahn, J. A., Parkinson, J. A., & Owen, A. M. (2008). The role of the basal ganglia in learning and memory: neuropsychological studies. Behavioural Brain Research, 199, 53–60.

  • Heaton, R. K., Miller, S. W., Taylor, M. J., & Grant, I. (2004). Revised comprehensive norms for an expanded Halstead-Reitan battery: Demographically adjusted neuropsychological norms for African American and Caucasian adults (HRB). Lutz: Psychological Assessment Resources.

    Google Scholar 

  • Hefkemeijer, A., Altmann-Schneider, I., Oleksik, A. M., van de Wiel, L., Middelkoop, H. A. M., van Buchem, M. A.,…, & Rombouts, S. A. (2012). Increased functional connectivity and brain atrophy in elderly with subjective memory complaints. Brain Connectivity, 2, A1–A156.

  • Hoehn, M. M., & Yahr, M. D. (1967). Parkinsonism: onset, progression and mortality. Neurology, 17(5), 427–442.

    Article  CAS  PubMed  Google Scholar 

  • Hughes, A. J., Ben-Shlomo, Y., et al. (1992). What features improve the accuracy of clinical diagnosis in Parkinson’s disease: a clinicopathologic study. Neurology, 42(6), 1142–1146.

    Article  CAS  PubMed  Google Scholar 

  • Jenkinson, M., & Smith, S. (2001). A global optimisation method for robust affine registration of brain images. Medical Image Analysis, 5, 143–156.

    Article  CAS  PubMed  Google Scholar 

  • Jiji, S., Smitha, K. A., Gupta, A. K., Pillai, V. P. M., & Jayasree, R. S. (2013). Segmentation and volumetric analysis of the caudate nucleus in Alzheimer’s disease. European Journal of Radiology, 82, 1525–1530.

    Article  PubMed  Google Scholar 

  • Jurica, P. J., Leitten, C. L., & Mattis, S. (2001). DRS-2: Dementia Rating Scale-2. Psychological Assessment Resources Eds. Odessa: FI.

  • Kaplan, E., Goodglass, H., & Weintrab, S. (1983). The Boston naming test. Philadelphia: Lea & Febiger.

    Google Scholar 

  • Krabbe, K., Karlsborg, M., Hansen, A., Werdelin, L., Mehlsen, J., Larsson, H. B. W., & Paulson, O. B. (2005). Increased intracranial volume in Parkinson’s disease. Journal of the Neurological Sciences, 239, 45–52.

    Article  PubMed  Google Scholar 

  • Lawton, M. P., & Brody, E. M. (1969). Assessment of older people: self-maintaining and instrumental activities of daily living. The Gerontologist, 9, 179–186.

    Article  CAS  PubMed  Google Scholar 

  • Lee, J. H., Han, Y. H., Kang, B. M., Mun, C. W., Lee, S. J., & Balk, S. K. (2013). Quantitative assessment of subcortical atrophy and iron content in progressive supranuclear palsy and parkinsonian variant of multiple system atrophy. Journal of Neurology, 260, 2094–2101.

    Article  CAS  PubMed  Google Scholar 

  • Lezak, M. (2004). Neuropsychological assessment (4th ed.). Oxford: University Press.

    Google Scholar 

  • Lisanby, S. H., McDonald, W. M., Massey, E. W., Doraiswamy, P. M., Rozear, M., …, & Nemeroff, C. (1993). Diminished subcortical nuclei volumes in Parkinson’s disease by MR imaging. Journal of Neural Transmission. Supplementa, 40, 13–21.

  • Lubin, A., Rossi, S., Simon, G., Lanoe, C., Leroux, G., Poirel, N., …, & Houde, O. (2013). Numerical transcoding proficiency in 10-year-old schoolchildren is associated with gray matter inter-individual differences: a voxel-based morphometry study. Frontiers in Psychology, 4, 1–7.

  • Mann, D. M. A., & Yates, P. O. (2008). Pathological basis for neurotransmitter changes in Parkinson’s disease. Neuropathology and Applied Neurobiology, 9, 3–19.

    Article  Google Scholar 

  • Marie, R. M., Barre, L., Dupuy, B., Viader, F., Defer, G., & Baron, J. C. (1999). Relationship between striatal dopamine denervation and frontal executive tests in Parkinson’s disease. Neuroscience Letters, 260, 77–80.

    Article  CAS  PubMed  Google Scholar 

  • Martinot, M. L. P., Lemaitre, H., Artiges, E., Miranda, R., Goodman, R., Penttila, J., …, & IMAGEN Consortium. (2013). White-matter microstructure and gray-matter volumes in adolescents with subthreshold bipolar symptoms. Molecular Psychiatry, Advance online publication. doi:10.1038/mp.2013.44

  • Meng, X. L., Rosenthal, R., & Rubin, D. B. (1992). Comparing correlated correlation coefficients. Quantitative Methods in Psychology, 111, 172–175.

    Google Scholar 

  • Middleton, F. A., & Strick, P. L. (2000). Basal ganglia output and cognition: evidence from anatomical, behavioral, and clinical study. Brain and Cognition, 42, 183–200.

    Article  CAS  PubMed  Google Scholar 

  • Moller, C., Vrenken, H., Jiskoot, L., Versteeg, A., Barkhof, F., Scheltens, P., & van der Flier, W. (2013). Different patterns of gray matter atrophy in early- and late- onset Alzheimer’s disease. Neurobiology of Aging, 34, 2014–2022.

    Article  PubMed  Google Scholar 

  • O’Neill, J., Schuff, N., Marks, W. J., Feiwell, R., Aminoff, M. J., & Weiner, M. W. (2002). Quantitative 1H magnetic resonance spectroscopy and MRI of Parkinson’s disease. Movement Disorders, 17(5), 917–927.

    Article  PubMed  Google Scholar 

  • Owen, A. M., James, M., Leigh, P. N., Summers, B. A., Marsden, C. D., Quinn, N. P., …, & and Robbins, T. W. (1992). Frontostriatal cognitive deficits at different stages in Parkinson’s disease. Brain, 115, 1727–1751.

  • Owen, A. M., Doyon, J., Dagher, A., Sadikot, A., & Evans, A. C. (1998). Abnormal basal ganglia outflow in Parkinson’s disease identified with PET. Implications for higher cortical functions. Brain, 121, 949–965.

    Article  PubMed  Google Scholar 

  • Postuma, R. B., & Dagher, A. (2006). Basal ganglia functional connectivity based on a meta-analysis of 126 positron emission tomography and functional magentic resonance imaging publications. Cerebral Cortex, 16, 1508–1521.

    Article  PubMed  Google Scholar 

  • Reitan, R. M. (1969). Manual for administration of neuropsychological test batteries for adults and children. Indianapolis: Neuropsychology Laboratory.

    Google Scholar 

  • Rinne, J. O., Rummukainen, J., Paljarvi, L., & Rinne, U. K. (1989). Dementia in Parkinson’s disease is related to neuronal loss in the medial substantia nigra. Annals of Neurology, 26, 47–50.

    Article  CAS  PubMed  Google Scholar 

  • Serra-Blasco, M., Portella, M. J., Gomez-Anson, B., de Diego-Adelino, J., Vives-Gilabert, Y. Puigdemont, D., …, & Perez, V. (2013). Effects of illness duration and treatment resistance on grey matter abnormalities in major depression. British Journal of Psychiatry, 202, 434–440.

  • Singh, S., Modi, S., Bagga, D., Kaur, P., Shankar, L. R., & Khushu, S. (2012). Voxel-based morphometric analysis in hypothyroidism using diffeomorphic anatomic registration via an exponentiated lie algebra algorithm approach. Journal of Neuroendocrinology, 25, 229–234.

    Article  Google Scholar 

  • Smith, S. M. (2002). Fast robust automated brain extraction. Human Brain Mapping, 17, 143–155.

    Article  PubMed  Google Scholar 

  • Taal, H. R., St Pourcain, B., Thiering, E., Das, S., Mook-Kanamori, D. O., Warrington, N. M., Kaakinen, M., …, & Jaddoe, V. W. V. (2012). Common variants at 12q15 and 12q24 are associated with infant head circumference. Nature Genetics, 55, 532–540.

  • Taylor, A. E., Saint-Cyr, J. A., & Lang, A. E. (1986). Frontal lobe dysfunction in Parkinson’s disease. The cortical focus of neostriatal outflow. Brain, 109, 845–883.

    Article  PubMed  Google Scholar 

  • Tessa, C., Lucetti, C., Gianelli, M., Dicotti, S., Poletti, M., …, & Toschi, N. (2014) Progression of brain atrophy in the early stages of Parkinson’s disease: A longitudinal tensor-based morphometry study in de novo patients without cognitive impairment. Human Brain Mapping, Epub ahead of print, doi:10.1002/hbm.22449

  • Wechsler, D. (1997). Wechsler adult intelligence scale-Third Edition. San Antonio: Pearson.

    Google Scholar 

  • Wechsler, D. (1999). Wechsler abbreviated scale of intelligence. San Antonio, TX: Harcourt Assessment

  • Winston, G. P., Stretton, J., Sidhu, M. K., Symms, M. R., Thompson, P. J., & Duncan, J. S. (2013). Structural correlates of impaired working memory in hippocampal sclerosis. Epilepsia, 54, 1143–1153.

    Article  PubMed Central  PubMed  Google Scholar 

  • Yushkevich, P. A., Piven, J., Hazlett, H. C., Smith, R. G., Ho, S., Gee, J. C., & Gerig, G. (2006). User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability. NeuroImage, 31, 1116–1128.

    Article  PubMed  Google Scholar 

  • Zgaljardic, D. J., Borod, J. C., Foldi, N. S., & Mattis, P. (2003). A review of the cognitive and behavioral sequelae of Parkinson’s disease: relationship to frontostriatal circuitry. Cognitive and Behavioral Neurology, 16, 193–210.

    Article  PubMed  Google Scholar 

  • Zijdenbos, A. P., Dawant, B. M., Margolin, R. A., & Palmer, A. C. (1994). Morphometric analysis of white matter lesions in MR images: method and validation. IEEE Transactions on Medical Imaging, 13, 716–724.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgments

This work was completed in partial fulfillment of Ms. Schwab’s Master of Science degree in the Department of Clinical and Health Psychology, University of Florida, Gainesville, Florida. Supported by National Institute for Neurological Disorders and Stroke (NINDS) K23NS60660 (C.P.), NINDS RO1NS082386 (C.P.), NINDS R01NR014181 (C.P.), and in part by the National Institutes of Health/National Center for Advancing Translational Sciences (NIH/NCATS) Clinical and Translational Science Award to the University of Florida UL1TR000064. We are most thankful to the participants who provided us with the data making this study possible, Sylvia Orosco, John Collazo, and Stephen Towler for their time assisting with the original study concept and institutional review board requirements, and Jade Ward, B.S., for her expertise with participant recruitment and study coordination. We acknowledge William Perlstein, Ph.D., Associate Professor, Clinical and Health Psychology, University of Florida, for his statistical advice.

Conflict of interest

Nadine Schwab, Jared Tanner, Peter T. Nguyen, Ilona M. Schmalfuss, Dawn Bowers, Michael Okun, and Catherine C. Price declare that they have no conflict of interest.

Consent

All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2000. Informed consent was obtained from all patients for being included in the study.

Author information

Authors and Affiliations

  1. Department of Clinical and Health Psychology, University of Florida, 1225 Center Drive, Gainesville, FL, 32611, USA

    Nadine A. Schwab, Jared J. Tanner, Peter T. Nguyen, Dawn Bowers & Catherine C. Price

  2. Department of Radiology, North Florida/South Georgia Veteran Administration, University of Florida, 1601 SW Archer Rd., Gainesville, FL, 32608, USA

    Ilona M. Schmalfuss

  3. Department of Neurology, Center for Movement Disorders and Neurorestoration, University of Florida, 3450 Hull Rd., Gainesville, FL, 32607, USA

    Dawn Bowers & Michael Okun

  4. Clinical and Health Psychology, University of Florida, 101 S. Newell Drive, PO Box 100165, Gainesville, FL, 32610, USA

    Catherine C. Price

Authors
  1. Nadine A. Schwab
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jared J. Tanner
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Peter T. Nguyen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ilona M. Schmalfuss
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Dawn Bowers
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Michael Okun
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Catherine C. Price
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Catherine C. Price.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Schwab, N.A., Tanner, J.J., Nguyen, P.T. et al. Proof of principle: Transformation approach alters caudate nucleus volume and structure-function associations. Brain Imaging and Behavior 9, 744–753 (2015). https://doi.org/10.1007/s11682-014-9332-x

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11682-014-9332-x

Keywords

Search

Navigation