COMMENTARY

Toward a Neuroanatomy of Obsessive-CompulsiveDisorder RevisitedSteven A. Rasmussen, Jane L. Eisen, and Benjamin D. Greenberg

Since the publication of Insel’s commentary Towards aNeuroanatomy of Obsessive-Compulsive Disorder (1) 20 yearsago, the finding of increased regional metabolic activity in

orbitofrontal cortex and caudate in obsessive-compulsive disor-der (OCD) patients versus controls, in both resting and sympto-matic states, has been one of the most replicable findings inpsychiatric imaging. Using resting positron emission tomography,Schwartz et al. (2) were the first to report on a functionalconnectivity measure that led to the speculation that the orbitalstriatal thalamic loop was overly synchronized in OCD and thatsuccessful behavioral or pharmacologic treatment led to thedesynchronization of the network. Since that initial study,advances in Bayesian dynamic causal modeling have allowed usto gain an understanding of how slow resting state rhythms aresynchronized across brain regions and has led to a new era inexploring functional connectivity in psychiatric disease (3). Func-tional connectivity studies have brought home the importance ofcomplex network connections as well as the significance ofsynchrony versus desynchrony between structures as a potentialtarget for therapeutic intervention. In 2009 Harrison et al. (4) werethe first of several groups to report on resting-state functionalconnectivity in OCD. Their major findings confirmed previouspositron emission tomography and functional magnetic reso-nance imaging data that pointed to abnormalities in orbitalstriatal function in OCD and whose magnitude was correlatedwith OCD severity. In the current issue, Harrison et al. (4) havereplicated their initial findings with a much larger sample of 74patients and controls and report on the similarities and differ-ences in functional connectivity (5) that are correlated with OCDsymptom dimensions measured by the Dimensional Yale BrownObsessive Compulsive Scale (DYBOCS) (6). The findings validate ahost of other clinical, imaging, and genetic findings thatdemonstrate both the overlap and unique features of symptomdimensions in OCD. These data support OCD’s phenotypic andetiologic heterogeneity.

Although functional connectivity studies represent a funda-mental advance in how we understand distributed brain net-works in relation to both structure and function, it is important torecognize that our ability to make conclusions from this class ofdata are limited by many of the same methodologic problemsthat have complicated an earlier generation of metabolic activa-tion studies. Although there has been substantial progress inunderstanding the neurophysiologic basis of changes in meta-bolic rates and in particular that the BOLD signal may vary withthe power of higher amplitude neuronal frequencies (7), theevidence remains controversial. Furthermore, it remains unclearwhat the relative balance of inhibitory or excitatory neuronal

From the Alpert School of Medicine at Brown University and Butler

Hospital, 345 Blackstone Blvd, Providence, Rhode Island.

Address correspondence to Steven A. Rasmussen, M.D., Alpert

School of Medicine at Brown University and Butler Hospital, 345

Blackstone Blvd., Providence, Rhode Island 02906; E-mail:

Steven_Rasmussen@Brown.edu.

Received Dec 21, 2012; accepted Dec 21, 2012.

0006-3223/$36.00http://dx.doi.org/10.1016/j.biopsych.2012.12.010

contribution to the BOLD signal for any given structure is andtherefore what that means for how we might perturb thatstructure to affect a disease state. Given that functional mapsdo not directly correspond to anatomic tracing studies, it isalmost certain that at least some of the functional connectionsare polysynaptic. The complexity of the wiring of the connec-tome has been brought home by the elegant studies of Lichtmanand Denk (8), who has pointed out that the resolution of currentfunctional magnetic resonance imaging (a cubic 1-mm voxel) is 1trillion times larger than the scale needed to fully ascertain thewiring diagram. Regional metabolic differences in functionalconnectivity between patients and controls may or may notrepresent clues to etiology. For example, increased orbitofrontalstriatal connectivity may represent higher levels of trait relatedautonomic reactivity in the patients, an endophenotype thatwould be shared across patients with anxiety and depression andnot necessarily specific to OCD.

Another layer of complexity with resting-state studies is howto control for the many cognitive and autonomic processes thatare not under voluntary control during the resting state. Are wemeasuring a state or trait variable or a combination of the two?For example, how do we know that the increased functionalconnectivity is not simply a measure of obsessional patient’sinability to relax and control their thoughts while in the restingstate in the scanner? Our ability to ascribe meaning to functionalactivation and functional connectivity becomes progressivelymore in doubt as we move from the primary sensory and motorcortices to the prefrontal cortex in which the potential forpolysynaptic interactions increases considerably. Finally, theproblem of multiple comparisons and combinatorial explosionsof dynamic causal models continue to be of concern in spite ofgood to fair test-retest reliability (9). Given the limitationsoutlined above, it is remarkable that the imaging findings inOCD have been so consistent across studies, methodologies, andpatient groups.

Our understanding of the phenotypic heterogeneity of OCDhas also advanced over the past 2 decades. Data from a variety ofsources including factor analyses of cross-sectional and long-itudinal data sets, imaging, neuropsychologic tests of frontalfunction, and genetics have supported clinical observations thatOCD is separable into four or five symptom dimensions includingcontamination (washing), overresponsibility (checking), symme-try/ordering, taboo thoughts (sexual, aggressive, and religious),and hoarding (10). In the current paper, the authors demonstratesignificant differences in functional connectivity maps and theircorrelation to symptom dimensions. The authors’ use of theDYBOCS and a two-step image masking approach has accountedfor the fact that most patients have multiple symptoms fromdifferent dimensions with varying degrees of severity. Interest-ingly their findings are consistent with studies from multipledomains showing a general pattern of a common influenceacross dimensions yet with some features that are unique to thedimensions (10). Their data support that differences between thedimensions were most marked for hoarding. This finding isentirely consistent with other studies that have led the DSM-V

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Commentary BIOL PSYCHIATRY 2013;73:298–299 299

work group on anxiety disorders to conclude that hoardingshould become its own diagnostic category.

The idea that there is a unique functional network for eachobsessive-compulsive symptom dimension is intriguing. Therehave been surprisingly few studies of resting- or task-dependentfunctional connectivity in simple phobia to date. Are symptomsdue to an anatomical (structural) abnormality or dynamicemergent property of the network? It is easy to see why phobiasin general are connected to fear circuitry but more difficult to seewhy a particular type of phobia might have its own anatomy asopposed to being something that is learned. It is unknown, butseems unlikely, that the current resolution in neuroimaging willbe able to detect a different hierarchical ensemble of activatedneurons in bee phobias versus height phobias, for example. Inphobias and other anxiety disorders, as well as harm-avoidantOCD, it seems likely that therapeutic targets will be found inwhich networks overlap as opposed to those in which they aredistinct. It is of particular interest that hoarders appear to havelittle overlap with the rest of OCD and that they are the mosttreatment refractory group. The current study suggests that weneed to be thinking about targeting a different set of circuitry forhoarders than for patients with OCD. Similarly, checkers have thebest longitudinal outcome, whereas patients with need forsymmetry/perfection have a worse long-term outcome. Perhapsthese differences in therapeutic response to selective serotoninreuptake inhibitors and behavior therapy have a basis in differentpatterns of functional connectivity.

It does not take much clinical experience working with OCDpatients to ascertain that there are fundamental differences aswell as overlap between patients with distinct obsessive-compulsive symptom dimensions. Although the DYBOCS hasbeen a significant advance in addressing how to measure overlapin symptom dimensions across individual patients, it fails tocapture the underlying core features of the disorder, harmavoidance, incompleteness, and pathologic doubt that are foundacross symptom dimensions. It is easy to see how making certainsomething is done correctly to avoid harm coming to self orsignificant others would be a highly conserved trait(s) in evolu-tion. It is also easy to see how harm avoidance, overreponsibility/pathologic doubt, and incompleteness/perfectionism all contri-bute to successful adaptation and why they may overlap in theOCD phenotype. There is some evidence that the currentsymptom dimensions defined by factor analyses are heteroge-neous. For example, patients with contamination may experiencedisgust, which has been associated with insular activation orharm avoidance that has been associated with medial frontalactivation. Similarly the need for symmetry dimension can beassociated with either harm avoidance or incompleteness. Careful

Toward a Neuroanatomy of Obsessive-Compulsive Disorder Revisite

phenotypic characterization is essential for determining validendophenotypes. For example, significant differences in stopsignal reaction time and reversal learning tasks have been widelyreported in OCD versus controls. A quarter of OCD patients havecomorbid obsessive compulsive personality disorder that isdefined in part by rigidity and difficulty switching sets, yet thisvariable has not been controlled for in the analyses. We lookforward to future studies that will test the specificity of thefindings for OCD versus other anxiety and OCD-related disordersas well as studies that test the homogeneity of current symptomdimensions. Finally, it is worth remembering that the funda-mental question is not whether there are differences in functionalconnectivity between dimensions but rather how can we use thisinformation to develop hypothesis-driven, circuit-based neuro-modulatory interventions.

Dr. Greenberg received meeting travel support in 2012 fromMedtronic, Inc., and Hoffman-La Roche Pharmaceuticals. Drs.Rasmussen and Eisen report no biomedical financial interests orpotential conflicts of interest.

1. Insel TR (1992): Towards a neuroanatomy of obsessive compulsivedisorder. Arch Gen Psychiatry 49:739–744.

2. Schwartz JM, Stoessel PW, Baxter LR, Martin KM, Phelps ME (1996):Systematic changes in cerebral glucose metabolic rate after successfulbehavior modification treatment of obsessive compulsive disorder.Arch Gen Psychiatry 53:109–113.

3. Fox MD, Raichle ME (2007): Spontaneous fluctuations in brain activityobserved with functional magnetic resonance imaging. Nat NeurosciRev 8:700–711.

4. Harrison BJ, Soriano-Mas C, Pujol J, Ortiz H, Lopez-Sola M, Hernandez-Ribas R, et al. (2009): Altered corticostriatal functional connectivity inobsessive compulsive disorder. Arch Gen Psychiatry 66:1189–1200.

5. Harrison BJ, Pujol J, Cardoner N, Deus J, Alonso P, Lopez-Sola M,et al. (2013): Brain corticostriatal systems and the major clinicalsymptom dimensions of obsessive-compulsive disorder. Biol Psychia-try 73:321–328.

6. Mataix-Cols D, Rosario-Campos MS, Leckman JF (2005): A multi-dimensional model of obsessive compulsive disorder. Am J Psychiatry162:228–238.

7. Leopold DA, Murayama Y, Logothetis NK (2003): Very slow activityfluctuations in monkey visual cortex: implications for functional brainimaging. Cereb Cortex 13:425–433.

8. Lichtman JW, Denk W (2011): The big and the small: challenges ofimaging the brain’s circuits. Science 334:618–623.

9. Daunizeau J, David O, Stephan KE (2011): Dynamic causal modeling: acritical review of the biophysical and statistical foundations. Neuro-image 58:312–322.

10. Van den Heuvel OA, Remijnse PL, Mataix-Cols D, Vrenken H,Groenewegen HJ, Uylings HB, et al. (2009): The major symptomdimensions of obsessive compulsive disorder are mediated bypartially distinct neural systems. Brain 132:853–868.

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