Search tips
Search criteria 


Logo of jpnSubmit a ManuscriptEmail AlertsAbout JPNJournal of Psychiatry and Neuroscience
J Psychiatry Neurosci. 2011 January; 36(1): 42–46.
PMCID: PMC3004974

White matter microstructure in patients with obsessive–compulsive disorder



Previous diffusion tensor imaging (DTI) studies in patients with obsessive–compulsive disorder (OCD) have reported inconsistent findings, and it is not known whether observed findings are related to abnormalities in axonal structure or myelination.


In this DTI study, we investigated fractional anisotropy, as well as axial and radial diffusivity, in 21 patients with OCD and 29 healthy controls.


We found decreased fractional anisotropy in the body of the corpus callosum in the OCD group, which was underpinned by increased radial diffusivity.


The cross-sectional design was the main limitation.


Our findings of increased radial diffusivity provide preliminary evidence for abnormal myelination in patients with OCD.


Most widely accepted models of obsessive–compulsive disorder (OCD) suggest that abnormalities of cortico–striatal circuits involving the orbitofrontal cortex, anterior cingulate cortex, thalamus and striatum play an important role in its pathophysiology.14 However, recent studies employing whole-brain analyses also indicate more distributed neuro-imaging alterations in patients with OCD, implicating parietal, insular and cerebellar regions.59 One potential explanation of these findings might be abnormality in white matter tracts, which can lead to abnormal connectivity between diverse brain regions.

Diffusion tensor imaging (DTI) is a magnetic resonance imaging (MRI) technique that is suitable for quantitatively investigating whole-brain white matter axonal integrity in vivo. It is based on the measurement of water molecule motion. Axonal structure restricts water diffusion such that it is greater in the axis parallel to the main axis of axons. Fractional anisotropy is a measure of the degree to which water diffusion is constrained in the brain and is widely used as a general index of axonal integrity.10,11 Component measures from which fractional anisotropy is derived, the so-called first (λ1), second (λ2) and third (λ3) principal eigenvalues, measure diffusion axial (parallel; λ1) and radial (perpendicular; λ = [λ2 + λ3]/2) to the primary axis of the axon. Previous studies showed that whereas axonal damage leads to marked decrease in λ1 (and modest or absent decrease in λ), demyelination increases λ without changing λ1.1215 Therefore, axial and radial diffusivity measures provide insights into the specific nature of white matter deficits; the former provides an index of axonal injury, whereas the latter is sensitive to changes in myelination.1215

To date, 8 studies have examined white matter pathology in patients with OCD using DTI.5,1622 However, the findings of these studies have been variable (Table 1), and no study has examined whether axonal injury or abnormal myelination explains the observed findings. In this study, our aim was to extend previous work and to examine alterations in fractional anisotropy as well as measures of axial and radial diffusivity in a sample of patients with OCD and healthy controls using a well-validated Tract-Based Spatial Statistics (TBSS) technique.24

Table 1
Previous diffusion tensor imaging studies in patients with obsessive–compulsive disorder



We recruited patients with OCD and matched healthy controls. Inclusion criteria for patients with OCD were

  • to be free of medications or to be stable on their medication dose for at least 1 month,
  • to have no other current Axis-I psychiatric diagnosis, and
  • to have a current intelligence quotient (IQ) greater than 80.

All participants with a history of neurologic disease, impaired thyroid function and steroid use were excluded. All patients were interviewed with the Structured Clinical Interview for DSM-IV Axis I Disorders, Patient version for diagnosis.25 The control group underwent the Structured Clinical Interview for DSM-IV Axis I Disorders, Nonpatient edition.26 General intelligence was assessed using the Wechsler Abbreviated Scale of Intelligence (WASI).27 The Yale–Brown Obsessive Compulsive Scale (Y–BOCS)23 was used to assess OCD symptoms within 1 week before scanning. Patients (and controls) were also assessed with Beck Depression Inventory28 and Beck Anxiety Inventory.29 All participants gave written informed consent to participate in the study. The study was approved by the Mental Health Research Institute Behavioural and Research Ethics Committee.

Imaging protocol

Magnetic resonance imaging was performed using a 3 T GE Signa LX whole-body scanner. Head motion was restricted using a Velcro strap over the forehead. We acquired diffusion imaging data in 28 diffusion gradient directions plus 5 b = 0 reference images using a sequence optimized to collect diffusion-weighted images (repetition time [TR] 6000 ms, echo time [TE] 90 ms, voxel size 1.875 × 1.875 × 2 mm). Data were transferred to a Linux 2.4.27 workstation for image processing and analyses.

Data analysis

We used the FMRIB Diffusion Toolbox, part of the FMRIB software library, to analyze DTI data.30 Diffusion-weighted volumes were corrected for Eddy current distortions and head motion. A diffusion tensor model was fit at each voxel, and fractional anisotropy λ1, λ2, λ3 maps were generated.31 We used fractional anisotropy axial (λ1) and radial (average of λ2 and λ3) diffusivity maps for further analyses.

Tract-based fractional anisotropy, axial and radial components of patient and control groups were calculated with TBSS.24 Fractional anisotropy data were aligned to a standard space (Montreal Neurological Institute 152) fractional anisotropy target by using a nonlinear registration method implemented in the FMRIB software library. A mean fractional anisotropy image was created from all participants, and then the mean image was thinned to create a mean fractional anisotropy skeleton that represented the centres of all tracts common to the participants. This image was thresholded to 0.2, then each participant’s aligned fractional anisotropy data were projected onto this skeleton.

Statistical analysis

We used a permutation-based parametric inference method with Randomize V2.1 software to analyze between-group differences.32 We performed corrections for multiple comparisons with an initial cluster-forming threshold of t = 2.0. We considered results to be significant at p < 0.05. For the clusters where we observed significant decreases of fractional anisotropy in patients with OCD, axial and radial diffusivity values were extracted from these clusters for each individual and further analyzed in SPSS 14.0 using Student t tests.


We included 21 patients with OCD and 29 healthy controls in our study. Ten patients were receiving stable doses of medication (selective serotonin reuptake inhibitor n = 6, chlorimi-pramine n = 3, venlafaxine n = 1). One of the patients had an incidental MRI finding without any clinical sign (possible ischemic lesion in the superior parietal area). The overall Y–BOCS scores of the patient group indicated a mild to moderate degree of symptom severity (mean 19.2, standard deviation [SD] 5.4).

There were no significant between-group differences for age, sex, years of education and IQ (Table 2). There were no significant differences for Y–BOCS between male and female patients with OCD. Patients tended to present with higher levels of subthreshold anxiety (t48 = 2.1, p = 0.05) and depression symptoms (t48 = 2.1, p = 0.06).

Table 2
Demographic and clinical characteristics of patients with obsessive–compulsive disorder (OCD) and healthy controls

Tract-Based Spatial Statistics analysis showed a significant between-group difference in only 1 region (Fig. 1). Patients with OCD had lower fractional anisotropy values in the body of the corpus callosum (CC). Excluding the single participant with incidental imaging findings did not change the results. Radial diffusivity in this region was increased in patients with OCD (t48 = 2.9, p = 0.006), but there were no between-group differences for axial diffusivity (t48 = −0.91, p = 0.36). Fractional anisotropy reduction in the midbody of the CC was not significantly different between male and female participants (t19 = 0.6, p = 0.55) and medicated and unmedicated patients (t19 = 0.6, p = 0.54). In voxel-wise correlation analyses, OCD, depression and anxiety symptoms were not associated with significant changes in white matter connectivity in any of the voxels, including the body of the CC.

Fig. 1
Diffusion tensor images showing (A) the mean fractional anisotropy skeleton representing the centres of all tracts common to the participants as determined by Tract-Based Spatial Statistics and (B–D) reduction of fractional anisotropy in patients ...


Several DTI studies have previously reported CC abnormalities in patients with OCD.17,20 However, to our knowledge, no studies to date have investigated the axonal versus myelin contributions to the identified abnormalities in white matter integrity. By examining axial and radial diffusivity in patients with OCD, we have demonstrated that impaired white matter integrity in the body of the CC in this patient group is driven by a myelin abnormality. This finding is consistent with preliminary genetic data suggesting that polymorphism of a gene that is an important regulator for the development of cells producing myelin is associated with OCD.33 Myelination in some brain regions such as the CC continues into adolescence and early adulthood, a period during which the onset of OCD is typically observed.34 As such, neurodevelopmental irregularities leading to abnormal myelination might have a role in the pathophysiology of OCD. However, this hypothesis needs support with longitudinal and postmortem studies.

The CC body includes interhemispheric fibres connecting associative areas in parietal lobes in both sides of the brain. Despite not being part of traditional OCD networks, there is increasing evidence for parietal lobe abnormalities in patients with OCD, and OCD has been reported in patients with right parietal multiple sclerosis.5,7,35 The parietal lobe was also found to be the only region in which white matter connectivity was decreased in relatives of patients with OCD.5 Neurocognitive studies also suggest parietal dysfunction in patients with OCD.36 In this study, we did not find any white matter deficit of the parietal lobe itself, but this might reflect the fact that TBSS only assesses the most common fibre pathways across individuals, typically excluding fibres penetrating the cortical mantle; thus, our methodology may have limited sensitivity in regions near the grey/white matter boundary. It is also possible that we were unable to detect white matter abnormalities in broader regions inside and outside of the CC owing to the inclusion of patients with less severe obsessive–compulsive symptoms in the current study. Previous studies that have detected such abnormalities have typically included patients with more severe obsessive–compulsive symptoms.

Previous DTI studies of patients with OCD have reported variable findings. Some have found abnormalities in different regions (white matter tracts within the anterior cingulate, medial frontal and occipital cortices). Furthermore, the direction of the changes has been conflicting. For example, fractional anisotropy was reported to be both decreased and increased for the anterior cingulum bundle.5,18,21 Methodological differences can explain some of these findings: only 1 of these studies5 corrected their findings, and the sample sizes of most studies have been small (n < 15). Potential misalignment of the white matter tracts, medication effects and differences in the content and severity of obsessive–compulsive symptoms might be other issues that can explain inconsistent findings.


One of the limitations of our study is its cross-sectional nature. Also, the potential effect of antidepressant treatment is another issue. In our study, we found no differences between medicated and unmedicated patients, suggesting our results are not attributable to such effects. However, our method for examining the effect of medication was not optimal since currently unmedicated patients were not medication-naive. Another potential issue relates to the influence of history of comorbid depression, as indicated by recent structural neuro-imaging work in patients with OCD.37 In this study, only current comorbid depression was considered as an exclusion cri-terion. Therefore, follow-up studies investigating the effects of illness-related factors and treatment are necessary to better understand the nature of white matter abnormalities in patients with OCD.


Studies with larger sample sizes to examine potential differences with respect to OCD patient subtypes or major symptom dimensions will be a valuable extension of the current work. Other DTI methods like tractography could provide information about the integrity of individual white matter tracts.


Drs. Yücel and Harrison were supported by a National Health and Medical Research Council of Australia (NHMRC) Clinical Career Development Award (I.D. 509345 and 628509). Dr. Fornito was supported by a National Health and Medical Research Council CJ Martin Fellowship (ID: 454797). Dr. Cocchi was supported by the Swiss Foundation for Fellowships in Biology and Medicine (PASMP3_129357 / 1) and a Swiss National Science Foundation grant (PBLAB-3-119622).


Competing interests: None declared for Drs. Bora, Harrison, Fornito, Pujol, Velakoulis and Yücel. Dr. Fontenelle declares having received grant support from an Endeavour Postdoctoral Research Fellowship and the Conselho Nacional de Desenvolvimento Científico e Techológico (Bolsa de Produtividade e Pesquisa); having consulted, presented lectures and developed educational presentations for Lundbeck; and having received travel assistance from Lundbeck, Solvay and Servier. Dr. Pantelis declares having consulted for and receiving honoraria from Janssen Cilag, Eli Lilly, AstraZeneca, Mayne Pharma, Pfizer and Schering Plough; receiving grant support from the National Health and Medical Research Council of Australia, the Australian Research Council, Eli Lilly, Hospira (Mayne), Janssen Cilag, the Ramaciotti Foudation, AstraZeneca, the AE Rowden White Foundation, the Victorian Neurotrauma Initiative, the Australian Nuclear Science and Technology Organisation and the University of Melbourne; having received payment for speaking from Janssen Cilag, Eli Lilly, Bristol Myers Squibb, AstraZeneca and Pfizer; and having received travel assistance from Janssen Cilag, AstraZeneca and Eli Lilly.

Contributors: Drs. Bora and Yücel designed the study. Dr. Yücel acquired the data. All authors analzyed the data and approved publication of the article. Drs. Bora and Fornito wrote the article, which Drs. Bora, Harrison, Fornito, Cocchi, Pujol, Fontenelle, Velakoulis, Pantelis and Yücel critically reviewed.


1. Graybiel AM, Rauch SL. Toward a neurobiology of obsessive-compulsive disorder. Neuron. 2000;28:343–7. [PubMed]
2. Menzies L, Chamberlain SR, Laird AR, et al. Integrating evidence from neuroimaging and neuropsychological studies of obsessive-compulsive disorder: the orbitofronto-striatal model revisited. Neurosci Biobehav Rev. 2008;32:525–49. [PMC free article] [PubMed]
3. Saxena S. Neuroimaging and the pathophysiology of obsessive compulsive disorder. In: Fu C, Senior C, Russell TA, editors. Neuroimaging in psychiatry. London (UK): Martin Dunitz; 2003. pp. 191–224.
4. Harrison BJ, Soriano-Mas C, Pujol J, et al. Altered corticostriatal functional connectivity in obsessive-compulsive disorder. Arch Gen Psychiatry. 2009;66:1189–200. [PubMed]
5. Menzies L, Williams GB, Chamberlain SR, et al. White matter abnormalities in patients with obsessive-compulsive disorder and their first-degree relatives. Am J Psychiatry. 2008;165:1308–15. [PubMed]
6. Nabeyama M, Nakagawa A, Yoshiura T, et al. Functional MRI study of brain activation alterations in patients with obsessive-compulsive disorder after symptom improvement. Psychiatry Res. 2008;163:236–47. [PubMed]
7. Page LA, Rubia K, Deeley Q, et al. A functional magnetic resonance imaging study of inhibitory control in obsessive-compulsive disorder. Psychiatry Res. 2009;174:202–9. [PubMed]
8. Pujol J, Soriano-Mas C, Alonso P, et al. Mapping structural brain alterations in obsessive-compulsive disorder. Arch Gen Psychiatry. 2004;61:720–30. [PubMed]
9. Yücel M, Harrison BJ, Wood SJ, et al. Functional and biochemical alterations of the medial frontal cortex in obsessive-compulsive disorder. Arch Gen Psychiatry. 2007;64:946–55. [PubMed]
10. Kubicki M, Westin CF, Maier SE, et al. Diffusion tensor imaging and its application to neuropsychiatric disorders. Harv Rev Psychiatry. 2002;10:324–36. [PMC free article] [PubMed]
11. Le Bihan D, Mangin JF, Poupon C, et al. Diffusion tensor imaging: concepts and applications. J Magn Reson Imaging. 2001;13:534–46. [PubMed]
12. Seal ML, Yücel M, Fornito A, et al. Abnormal white matter microstructure in schizophrenia: a voxelwise analysis of axial and radial diffusivity. Schizophr Res. 2008;101:106–10. [PubMed]
13. Wozniak JR, Lim O. Advances in white matter imaging: a review of in vivo magnetic resonance methodologies and their applicability to the study of development and aging. Neurosci Biobehav Rev. 2006;30:762–74. [PMC free article] [PubMed]
14. Song SK, Sun SW, Ju WK, et al. Diffusion tensor imaging detects and differentiates axon and myelin degeneration in mouse optic nerve after retinal ischemia. Neuroimage. 2003;20:1714–22. [PubMed]
15. Song SK, Yoshino J, Le TQ, et al. Demyelination increases radial diffusivity in corpus callosum of mouse brain. Neuroimage. 2005;26:132–40. [PubMed]
16. Cannistraro PA, Makris N, Howard JD, et al. A diffusion tensor imaging study of white matter in obsessive-compulsive disorder. Depress Anxiety. 2007;24:440–6. [PubMed]
17. Garibotto V, Scifo P, Gorini A, et al. Disorganization of anatomical connectivity in obsessive compulsive disorder: a multi-parameter diffusion tensor imaging study in a subpopulation of patients. Neurobiol Dis. 2010;37:468–76. [PubMed]
18. Ha TH, Kang DH, Park JS, et al. White matter alterations in male patients with obsessive–compulsive disorder. Neuroreport. 2009;20:735–9. [PubMed]
19. Nakamae T, Narumoto J, Shibata K, et al. Alteration of fractional anisotropy and apparent diffusion coefficient in obsessive–compulsive disorder: a diffusion tensor imaging study. Prog Neuropsychopharmacol Biol Psychiatry. 2008;32:1221–6. [PubMed]
20. Saito Y, Nobuhara K, Okugawa G, et al. Corpus callosum in patients with obsessive-compulsive disorder: diffusion-tensor imaging study. Radiology. 2008;246:536–42. [PubMed]
21. Szeszko PR, Ardekani B, Ashtari M, et al. White matter abnormalities in obsessive-compulsive disorder: a diffusion tensor imaging study. Arch Gen Psychiatry. 2005;62:782–90. [PubMed]
22. Yoo SY, Jang JH, Shin YW, et al. White matter abnormalities in drug-naïve patients with obsessive–compulsive disorder: a diffusion tensor study before and after citalopram treatment. Acta Psychiatr Scand. 2007;116:211–9. [PubMed]
23. Goodman WK, Price LH, Rasmussen SA, et al. The Yale-Brown Obsessive Compulsive Scale (YBOCS): Part I. Development, use, and reliability. Arch Gen Psychiatry. 1989;46:1006–11. [PubMed]
24. Smith SM, Jenkinson M, Johansen-Berg H, et al. Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data. Neuroimage. 2006;31:1487–505. [PubMed]
25. First MB, Spitzer RL, Gibbon M, et al. Structured Clinical Interview for DSM-IV-TR Axis I Disorders, Research Version, Patient Edition (SCID-I/P) New York (NY): Biometrics Research, New York State Psychiatric Institute; 2002.
26. First MB, Spitzer RL, Gibbon M, et al. Structured Clinical Interview for DSM-IV-TR Axis I Disorders, Research Version, Non-patient Edition (SCID-I/NP) New York (NY): Biometrics Research, New York State Psychiatric Institute; 2002.
27. Wechsler D. Weschler Abbreviated Scale of Intelligence. New York (NY): Psychological Corporation; 1999.
28. Beck AT, Ward CH, Mendelson M, et al. An inventory for measuring depression. Arch Gen Psychiatry. 1961;4:53–63.
29. Beck AT, Epstein N, Brown G, et al. An inventory for measuring clinical anxiety: psychometric properties. J Consult Clin Psychol. 1988;56:893–7. [PubMed]
30. Smith SM, Jenkinson M, Woolrich MW, et al. Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage. 2004;23(Suppl 1):S208–19. [PubMed]
31. Behrens TEJ, Woolrich MW, Jenkinson M, et al. Characterisation and propogation of uncertainty in diffusion weighted MR imaging. Magn Reson Med. 2003;50:1077–88. [PubMed]
32. Nichols TE, Holmes AP. Nonparametric permutation tests for functional neuroimaging: a primer with examples. Hum Brain Mapp. 2002;15:1–25. [PubMed]
33. Stewart SE, Platko J, Fagerness J, et al. A genetic family-based association study of OLIG2 in obsessive-compulsive disorder. Arch Gen Psychiatry. 2007;64:209–14. [PubMed]
34. Pujol J, Vendrell P, Junqué C, et al. When does human brain development end? Evidence of corpus callosum growth up to adulthood. Ann Neurol. 1993;34:71–5. [PubMed]
35. Douzenis A, Michalopoulou PG, Voumvourakis C, et al. Obsessive-compulsive disorder associated with parietal white matter multiple sclerosis plaques. World J Biol Psychiatry. 2009;10:956–60. [PubMed]
36. Chamberlain SR, Fineberg NA, Blackwell AD, et al. A neuro-psychological comparison of obsessive-compulsive disorder and trichotillomania. Neuropsychologia. 2007;45:654–62. [PubMed]
37. Cardoner N, Soriano-Mas C, Pujol J, et al. Brain structural correlates of depressive comorbidity in obsessive compulsive disorder. Neuroimage. 2007;38:413–21. [PubMed]

Articles from Journal of Psychiatry & Neuroscience : JPN are provided here courtesy of Canadian Medical Association