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Spontaneous magnetoencephalographic activity in patients with obsessive-compulsive disorder
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a v a i l a b l e a t w w w. s c i e n c e d i r e c t . c o m
w w w. e l s e v i e r. c o m / l o c a t e / b r a i n r e s
Research Report
Spontaneous magnetoencephalographic activity in patients with obsessive-compulsive disorder Christian Maihöfner a,⁎,1 , Wolfgang Sperling b,1 , Martin Kaltenhäuser a , Stefan Bleich b , Martina de Zwaan c , Jens Wiltfang b , Norbert Thürauf b , Samuel Elstner b , Udo Reulbach b , Piotr Lewczuk b , Johannes Kornhuber b , Axel Ropohl b a
Department of Neurology, Friedrich-Alexander-University of Erlangen-Nuremberg, Schwabachanlage 6, 91054 Erlangen, Germany Department of Psychiatry and Psychotherapy, University of Erlangen-Nuremberg, Schwabachanlage 6, 91054 Erlangen, Germany c Department of Psychosomatics, University of Erlangen-Nuremberg, Schwabachanlage 6, 91054 Erlangen, Germany b
A R T I C LE I N FO
AB S T R A C T
Article history:
Non-invasive functional imaging techniques have begun to delineate the underlying
Accepted 25 October 2006
neurophysiological basis of obsessive-compulsive disorder (OCD). In the present study, we
Available online 6 December 2006
investigated slow (2–6 Hz) and fast (12.5–30 Hz) spontaneous magnetoencephalographic (MEG) activity in ten patients with obsessive-compulsive disorders compared to ten healthy
Keywords:
control subjects. Fast MEG activity was significantly elevated in OCD patients. The
Magnetoencephalography
corresponding dipole density maxima were concentrated on the left superior temporal
Obsessive-compulsive disorder
gyrus. Although no differences were detected in the absolute dipole numbers between
Dipole density plot
controls and OCD patients regarding slow MEG activity, only the latter showed a clustering
Frontotemporal dysfunction
of slow MEG activity over their left dorsolateral prefrontal cortex. We conclude that
Superior temporal gyrus
alterations of spontaneous MEG activity in prefrontal and temporal cortices may be linked to the pathogenesis of OCD. Therefore, we provide further functional neuroimaging evidence that the complex features of OCD have neural correlates, which may help in a future understanding of this disease. © 2006 Elsevier B.V. All rights reserved.
1.
Introduction
Obsessive-compulsive disorder (OCD) is the world's fourth most common mental disorder and has a lifetime prevalence of 2–3% (Weissman et al., 1994). OCD is characterized by recurrent, intrusive and distressing thoughts (obsessions) or repetitive behaviors (compulsions) (Stein, 2002). The underlying pathophysiology is still not fully understood. Recently, advances in neuroimaging techniques have led to a better understanding of brain–behavior relationships in OCD. Most
data derive from positron emission tomography (PET), functional magnetic resonance imaging (fMRI) and single photon emission tomography (SPECT) studies (Adler et al., 2000; Saxena and Rauch, 2000; Rauch et al., 2001; Kwon et al., 2003; Whiteside et al., 2004; Nakao et al., 2005). These studies demonstrated over- or underactivity of frontal cortices (mainly orbito-frontal and dorsolateral prefrontal cortices; OF and DLPFC) and parts of the basal ganglia when the resting state was compared with controls (Saxena and Rauch, 2000; Whiteside et al., 2004). Symptom provocations in OCD patients
⁎ Corresponding author. E-mail address: [email protected] (C. Maihöfner). 1 Contributed equally to this work. 0006-8993/$ – see front matter © 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.brainres.2006.10.048
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using experimental paradigms have also been found to generate activations in similar brain areas (Adler et al., 2000; Nakao et al., 2005). Finally, when pharmacotherapy or behavioral therapy was employed, activations in OF, DLPFC and basal ganglia were found to be reduced (Schwartz et al., 1996; Brody et al., 1999; Saxena and Rauch, 2000). Therefore, these studies indicate that OCD symptoms might be mediated by a hyperactivity in orbito-frontal and subcortical circuits, which may finally lead to an imbalance of tone between direct and indirect striato-pallidal pathways (Saxena and Rauch, 2000; Rauch et al., 2001). Basically, spontaneous brain activity may also be investigated by magnetoencephalography (MEG). MEG is an additional neuroimaging method that combines both high temporal and spatial resolution. It represents neuronal activity more directly than techniques using intermediates like changes in cerebral blood flow or glucose metabolism. Since magnetic fields are not distorted by the different conduction of the skull and other inhomogenities of the head, MEG is a potentially powerful localization tool of brain function. Measurements of spontaneous MEG activity have been performed to characterize abnormal brain activity in several neurological and psychiatric disorders. Focal slow wave MEG activity (2–6 Hz) was found to be associated with impaired neuronal function. Recently, we investigated spontaneous MEG activity in patients with depression and found an enrichment of slow wave activity over the left DLPFC (Maihofner et al., 2005). This agrees with PET studies demonstrating hypometabolism in this cortex in depressive patients. Furthermore, abnormal slow wave activity has been found around brain tumor borders, brain infarctions or during transient global amnesia (Kamada et al., 1997, 2001; Stippich et al., 2000). Therefore, slow MEG wave activity appears to be associated with decreased neuronal activity. Additionally, several studies found an abnormal increase of focal spontaneous beta wave activity (12.5–30 Hz) in the areas of or adjacent to brain lesions (Vieth et al., 1996). There is also evidence for an interhemispheric phase synchrony and amplitude correlation of spontaneous beta oscillations in human subjects (Nikouline et al., 2001). This was interpreted as spontaneous brain activity associated with the resting state. Finally, in a recent study, we were able to detect increased fast MEG activity in the auditory cortex during auditory hallucinations in schizophrenia (Ropohl et al., 2004). This pattern of activation was similar to increases of fMRI signals during auditory hallucinations (Dierks et al., 1999). Therefore, in the present study, we extended these previous findings and hypothesized that patients with OCD may have alterations of their spontaneous MEG activity pattern. We investigated both slow (2–6 Hz) and fast (12.5–30 Hz) spontaneous magnetoencephalographic (MEG) activity in ten patients with OCD compared to ten healthy control subjects.
2.
Results
Patients showed a significant increase of spontaneous MEG activity in the fast frequency range (12.5–30 Hz) over the left hemisphere for both Dtotal and Dmax (Dtotal: 3100 ± 334 versus 2061 ± 222; p < 0.05; Dmax: 78 ± 11 versus 29 ± 10; p < 0.05; Figs. 1A/B). This activity was concentrated over the left super-
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ior temporal gyrus (Fig. 2), while no focal dipole concentration was found for fast MEG activity of the left hemisphere in controls. Values of Dtotal and Dmax of patients were not correlated with scores on the Yale–Brown Obsessive-compulsive scale (Dtotal: r = −0.01; Dmax: r = 0.50; p > 0.05 each). Fast MEG activity of patients' left hemispheres was also significantly increased compared to the corresponding right hemispheres (Dtotal: 3100 ± 334 versus 2268 ± 275; p < 0.05; Dmax: 78 ± 11 versus 38 ± 5; p < 0.05; Figs. 1A/B). In contrast, there were no significant differences for Dtotal and Dmax in the fast frequency range over the right hemispheres of controls and OCD patients (Dtotal: 2268 ± 275 versus 1663 ± 374; p > 0.05; Dmax: 38 ± 5 versus 34 ± 4; p > 0.05; Figs. 1A/B). Spontaneous MEG activity in the slow frequency band (2–6 Hz) was not significantly different over the right hemispheres of patients and controls (Dtotal: 1998 ± 337 versus 2164 ± 236; p > 0.05; Dmax: 41 ± 7 versus 43 ± 7; p > 0.05; Figs. 1C/D). Furthermore; for both patients and controls, the MEG activity showed a widespread distribution and no focal maxima were found when a dipole density analysis was applied, consistent with previous results in healthy subjects (Ropohl et al., 2004; Maihofner et al., 2005). Finally, there was no difference for slow MEG activity over the left hemispheres of patients and controls (Dtotal: 2273 ± 299 versus 2237 ± 198; p > 0.05; Dmax: 46 ± 7 versus 52 ± 27; p > 0.05; Figs. 1C/D). However, in sharp contrast to the control group, where the detected magnetic activity was again widely distributed and no focal maxima were found, the slow MEG activity in OCD patients was found to be enriched over the left dorsolateral prefrontal cortex (Fig. 2B).
3.
Discussion
In the present study, we compared spontaneous MEG recordings of OCD patients with those of a healthy age- and sexmatched control group. Our results provide evidence for an increase of fast MEG activity over the left hemisphere in the OCD group. Magnetic source imaging located this increase to activity in the left superior temporal gyrus. Furthermore, we found an enrichment of slow MEG activity over the left DLPFC in OCD patients, a finding which was absent in controls. Converging evidence in the last decades has suggested a neuronal basis for the pathogenesis of obsessive-compulsive disorder. Neurophysiological findings in OCD have pointed to a dysfunction of frontal cortices (e.g. OF and DLPFC), anterior cingulate cortex, basal ganglia, and other subcortical and limbic structures (Saxena and Rauch, 2000; Rauch et al., 2001). Increased fast MEG activity in the left STG as found in the present study complements these previous studies and agrees with a recent morphometric magnetic resonance study in OCD patients (Choi et al., 2006). Choi and colleagues (2006) investigated gray matter volumes of the STG and found a significant reduction of this cortex in OCD patients compared to controls. This is also in line with studies investigating brain activation during symptom provocation in OCD. Using individually tailored provocative stimuli, Adler and colleagues demonstrated regular activations of temporal cortices in their fMRI study (Adler et al., 2000). Furthermore, studies looking for brain lesions in symptomatic OCD, e.g. following
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Fig. 1 – Spontaneous neuromagnetic activity in fast (A, B) and slow (C, D) frequency ranges in OCD patients and healthy control subjects. MEG activity was quantified by calculating the total dipole number (Dtotal; A, C) and the concentration of dipoles within the area of highest dipole density (density maximum; Dmax; B, D). Corresponding hemispheres are specified in the figure. Black bars indicate MEG activity of patients, gray bars of controls. Data are given as mean ± standard error of the mean. * Indicates p < 0.05. stroke, point to the temporal region being involved in the pathogenesis of OCD (Berthier et al., 1996). This also fits well with previous PET and SPECT studies (Lucey et al., 1995; Simpson and Baldwin, 1995; Cottraux et al., 1996; Hendler et al.,
Fig. 2 – Dipole density analysis of spontaneous focal fast (A) and slow (B) wave magnetic brain activity in one representative patient. Isocontour lines, representing magnetic activity, are projected onto respective cranial MRT slices of the patient. Focal magnetic maxima were located in the left superior temporal gyrus (A) and the left dorsolateral prefrontal cortex (B).
1999). The STG is a brain area crucially involved in the processing of visuospatial information and mental coordination (Mayer et al., 2004). Furthermore, the STG has rich interconnections to the amygdala and the OF (Rempel-Clower and Barbas, 2000; Choi et al., 2006), which is overactive in OCD. Therefore, activity of the OF may influence STG activation or vice versa. We did not observe MEG activity in the OF. However, this is likely due to technical constraints as we used a dual 37channel neuromagnetometer and the sensor arrays were placed above the C3 and C4 position. Therefore, we were not “sensitive” for the whole brain in the present study. The use of the MEG technology also explains why we did not observe activation of the basal ganglia as these deep brain areas are usually not accessible by MEG. All patients described the presence of obsessive thoughts while keeping their eyes closed during the MEG recordings. Nevertheless, the increase of fast MEG activity was not correlated to the severity of OCD symptoms as assessed by the Yale–Brown OCD scale. This may hint at the fact that other neuropsychological features of OCD may be involved in this abnormal MEG activity. Many previous neuropsychological studies have reported cognitive dysfunction in OCD in areas such as executive and selective function, non-verbal memory and visuospatial skills (FlorHenry et al., 1979; Christensen et al., 1992; Savage et al., 1999).
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Although we did not assess visuospatial processing in our patients, abnormal MEG activity in the STG may be involved in such neuropsychological features, based on the function of this brain area (Purcell et al., 1998; Mayer et al., 2004). Alternatively, focal enrichment of MEG activity in the beta range has been reported in areas of structural damage (Vieth et al., 1996). Accordingly, our present findings of focal beta MEG activity in the STG agree with a decrease of the gray matter volume in this cortex in OCD patients (Choi et al., 2006). Finally, there is evidence for an interhemispheric phase synchrony and amplitude correlation of spontaneous beta oscillations in healthy human subjects (Nikouline et al., 2001). This was interpreted as spontaneous brain activity associated with the resting state. Therefore, another possible explanation for fast MEG activity in the STG may be an alteration of the resting state due to attentional processes in OCD. Although the results of the Yale–Brown OCD scale were after the MEG measurement not different from our baseline assessment, the MEG recording itself with eyes closed may have led to a higher degree of “introspection” in the patients, who are presumably more familiar with reflecting their thoughts and behavior. Future studies will help to clarify the relationship between MEG activity and neuropsychological profiles. Furthermore, we found enrichment of slow MEG activity over the left DLPFC. Recent quantitative EEG investigations in OCD patients showed a frontotemporal dysfunction with a significant increase of frontal slow wave activity compared to healthy subjects (Tot et al., 2002; Karadag et al., 2003). This effect was mainly found over the left hemisphere. Therefore, our results of spontaneous MEG measurements confirm EEG findings demonstrating an involvement of frontal cortices in OCD. In agreement with these studies, we found a concentration of slow frequencies in the left frontal lobe. Activation of the DLPFC has been consistently demonstrated during symptom provocation in OCD (Adler et al., 2000; Nakao et al., 2005). Furthermore, fMRI studies in OCD patients demonstrated decreased activation of the DLPFC in test paradigms used to probe planning processes, like the Tower of London task (Van den Heuvel et al., 2005). The DLPFC is involved in planning processes, executive aspects of selective attention and complex processes which operate on the working memory information, like monitoring, manipulation and higher level planning (Van den Heuvel et al., 2003). Planning as assessed by the Tower of London task is compromised in OCD patients (Van den Heuvel et al., 2005). These results fit well with our present finding of enriched slow wave activity over the DLPFC in OCD patients. Nevertheless, a regular comorbidity of OCD is depression (Stein, 2002). Our patients had signs of mild depression as assessed by the Hamilton Depression Rating Scale score. Previously, we were able to demonstrate that depressive patients show abnormally slow MEG activity over their left prefrontal cortex which was found to be significantly reduced following treatment with repetitive transcranial magnetic stimulation (Maihofner et al., 2005). Therefore, as an alternative to the aforementioned possibilities, depressive symptoms might also have influenced the results of spontaneous MEG measurements over frontal cortices in our study. In summary, using MEG, we here demonstrate that OCD patients show abnormally fast MEG activity over their left STG and an enrichment of slow MEG activity over the left DLPFC.
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These results are in line with a frontotemporal dysfunction in OCD. It would be of great interest to further characterize the relationships between MEG activity and individual neuropsychological profiles in future studies.
4.
Experimental procedures
4.1.
Patients and controls
Informed written consent was obtained from all subjects, and the study was approved by the local ethics committee. We included ten right-handed patients diagnosed with OCD (six males, four females; mean age =32.5 ± 6.3 years, disease duration 5–17 years). OCD was diagnosed by a psychiatric consultant (WS) according to the criteria of the DSM-IV classification system. Scores on the Yale–Brown Obsessive-compulsive scale (Goodman et al., 1989) were recorded 2 days before MEG measurements (baseline) and immediately after each MEG measurement (post MEG recording) to define the severity of the symptoms subsequent to the investigation. Baseline and post MEG scores showed no statistically significant differences (baseline score: 26.4 ± 1.2; post MEG score: 26.5 ± 1.4; p > 0.05, t-test for paired samples). Furthermore, OCD patients revealed a mean Hamilton Depression Rating Scale score of 13.5 ± 3.5 indicating mild depressive symptoms. All patients were drug-free 3 weeks before the beginning of the MEG measurements and were exclusively treated with unique psychotherapy (educational program). Before the inclusion phase, all patients were treated with selective serotonin reuptake inhibitors (SSRI) and psychotherapy. SSRIs were either sertraline, paroxetine or citalopram. Therefore, based on the pharmacokinetic properties, it was guaranteed that a time interval of 3 weeks was sufficient to eliminate respective drugs (Preskorn, 1997). Exclusion criteria were a history of focal neurological disorders, systemic illness, head trauma, treatment with electroconvulsive therapy, repetitive magnetic transcranial stimulation, nerve vagus stimulation, schizophrenia, drug abuse or dependence. MEG data were compared with those of 10 healthy age- and sex-matched subjects (six males, four females; mean age 27.4 ± 4.3 years). Matching criterion was age of the individual patient ± 5 years for the corresponding control subject. All patients and control subjects were right-handed as assessed during a medical interview.
4.1.1.
Magnetoencephalography
Cortical activity was recorded with the same dual 37-channel neuromagnetometer (Magnes II®; 4-D Neuroimaging, San Diego, CA) as used previously (Maihofner et al., 2003, 2004, 2005; Ropohl et al., 2004). Sensor arrays were placed with the center above C3 and C4, according to the international 10–20 EEG system. Spontaneous neuromagnetic brain activity was recorded in data sets of 600 s duration from both hemispheres simultaneously at a sampling rate of 520.8 Hz. Online highpass (1.0 Hz) and lowpass (100.0 Hz) filters were applied, and an ECG was recorded. For offline data analysis, an initial 50 Hz notch filter was applied and the magnetic field noise of the heart was removed by ECG triggered digital noise reduction. All raw data sets were carefully checked for artifacts from eye and body movements, and affected sections were excluded from further
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analysis. Digital bandpass filters were applied to analyze slow (2–6 Hz; theta/delta range) and fast (12.5–30 Hz; beta range) frequency bands separately. A principal component analysis was used to select a 10 s period minimum from the whole measurement where one component was predominant in the signal (Vieth et al., 1993; Kamada et al., 1997). This was achieved by analyzing overlapping time sections with a length that corresponded to the mean signal frequency. In those selected time sections, >90% of the signal variance could be attributed to the dominant component and a single source model was considered to be an adequate mathematical model. Single equivalent current dipoles were calculated every 2 ms over the selected data segments using a locally fitted spherical head model. Only dipoles showing statistical correlations between estimated and measured magnetic field distributions of p > 0.9 were accepted for data evaluation. The spatial distribution of dipoles was determined by a 3D convolution with a Gaussian shaped envelope, for which the variance was the localization uncertainty of individual dipole localizations yielding a dipole density plot (DDP) (Vieth et al., 1993; Kamada et al., 1997; Ropohl et al., 2004; Maihofner et al., 2005). Patients' headshapes were digitized using a commercially available sensor position indicator system (Polhemus®; Colchester, Vermont, New England) integrated into the standard Magnes II® system. Using a contour fit technique, MEG localizations were inserted onto an anatomical 3D T1-weighted image acquired with a 1.5 Tesla Magnetom (Magnetom Symphony, Siemens, Germany). Spontaneous neuromagnetic activity was quantified by calculating the total dipole number (Dtotal), and highest dipole density (density maximum; Dmax) from dipole distributions. To visualize the results of this analysis with respect to brain anatomy, the slice containing the density maximum Dmax was used and the dipole density of this slice shown by isocontour lines was superimposed on MRI. Line spacing was chosen to be 1% of Dtotal.
4.2.
Statistical analysis
The data are presented as mean ± standard error of the mean (SEM). Differences between patients and health controls were tested by the t-test for independent samples. Interhemispheric differences within groups were tested by the t-test for paired samples. All statistical tests were two-sided, and a significance level of α < 0.05 was used. Correlations were calculated with the Pearson correlation coefficient. Data were analyzed using SPSS™ 11 (SPSS Inc., Chicago, IL).
Acknowledgment We gratefully thank Tassilo Mathiowetz for his technical support.
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Research Report
Spontaneous magnetoencephalographic activity in patients with obsessive-compulsive disorder Christian Maihöfner a,⁎,1 , Wolfgang Sperling b,1 , Martin Kaltenhäuser a , Stefan Bleich b , Martina de Zwaan c , Jens Wiltfang b , Norbert Thürauf b , Samuel Elstner b , Udo Reulbach b , Piotr Lewczuk b , Johannes Kornhuber b , Axel Ropohl b a
Department of Neurology, Friedrich-Alexander-University of Erlangen-Nuremberg, Schwabachanlage 6, 91054 Erlangen, Germany Department of Psychiatry and Psychotherapy, University of Erlangen-Nuremberg, Schwabachanlage 6, 91054 Erlangen, Germany c Department of Psychosomatics, University of Erlangen-Nuremberg, Schwabachanlage 6, 91054 Erlangen, Germany b
A R T I C LE I N FO
AB S T R A C T
Article history:
Non-invasive functional imaging techniques have begun to delineate the underlying
Accepted 25 October 2006
neurophysiological basis of obsessive-compulsive disorder (OCD). In the present study, we
Available online 6 December 2006
investigated slow (2–6 Hz) and fast (12.5–30 Hz) spontaneous magnetoencephalographic (MEG) activity in ten patients with obsessive-compulsive disorders compared to ten healthy
Keywords:
control subjects. Fast MEG activity was significantly elevated in OCD patients. The
Magnetoencephalography
corresponding dipole density maxima were concentrated on the left superior temporal
Obsessive-compulsive disorder
gyrus. Although no differences were detected in the absolute dipole numbers between
Dipole density plot
controls and OCD patients regarding slow MEG activity, only the latter showed a clustering
Frontotemporal dysfunction
of slow MEG activity over their left dorsolateral prefrontal cortex. We conclude that
Superior temporal gyrus
alterations of spontaneous MEG activity in prefrontal and temporal cortices may be linked to the pathogenesis of OCD. Therefore, we provide further functional neuroimaging evidence that the complex features of OCD have neural correlates, which may help in a future understanding of this disease. © 2006 Elsevier B.V. All rights reserved.
1.
Introduction
Obsessive-compulsive disorder (OCD) is the world's fourth most common mental disorder and has a lifetime prevalence of 2–3% (Weissman et al., 1994). OCD is characterized by recurrent, intrusive and distressing thoughts (obsessions) or repetitive behaviors (compulsions) (Stein, 2002). The underlying pathophysiology is still not fully understood. Recently, advances in neuroimaging techniques have led to a better understanding of brain–behavior relationships in OCD. Most
data derive from positron emission tomography (PET), functional magnetic resonance imaging (fMRI) and single photon emission tomography (SPECT) studies (Adler et al., 2000; Saxena and Rauch, 2000; Rauch et al., 2001; Kwon et al., 2003; Whiteside et al., 2004; Nakao et al., 2005). These studies demonstrated over- or underactivity of frontal cortices (mainly orbito-frontal and dorsolateral prefrontal cortices; OF and DLPFC) and parts of the basal ganglia when the resting state was compared with controls (Saxena and Rauch, 2000; Whiteside et al., 2004). Symptom provocations in OCD patients
⁎ Corresponding author. E-mail address: [email protected] (C. Maihöfner). 1 Contributed equally to this work. 0006-8993/$ – see front matter © 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.brainres.2006.10.048
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using experimental paradigms have also been found to generate activations in similar brain areas (Adler et al., 2000; Nakao et al., 2005). Finally, when pharmacotherapy or behavioral therapy was employed, activations in OF, DLPFC and basal ganglia were found to be reduced (Schwartz et al., 1996; Brody et al., 1999; Saxena and Rauch, 2000). Therefore, these studies indicate that OCD symptoms might be mediated by a hyperactivity in orbito-frontal and subcortical circuits, which may finally lead to an imbalance of tone between direct and indirect striato-pallidal pathways (Saxena and Rauch, 2000; Rauch et al., 2001). Basically, spontaneous brain activity may also be investigated by magnetoencephalography (MEG). MEG is an additional neuroimaging method that combines both high temporal and spatial resolution. It represents neuronal activity more directly than techniques using intermediates like changes in cerebral blood flow or glucose metabolism. Since magnetic fields are not distorted by the different conduction of the skull and other inhomogenities of the head, MEG is a potentially powerful localization tool of brain function. Measurements of spontaneous MEG activity have been performed to characterize abnormal brain activity in several neurological and psychiatric disorders. Focal slow wave MEG activity (2–6 Hz) was found to be associated with impaired neuronal function. Recently, we investigated spontaneous MEG activity in patients with depression and found an enrichment of slow wave activity over the left DLPFC (Maihofner et al., 2005). This agrees with PET studies demonstrating hypometabolism in this cortex in depressive patients. Furthermore, abnormal slow wave activity has been found around brain tumor borders, brain infarctions or during transient global amnesia (Kamada et al., 1997, 2001; Stippich et al., 2000). Therefore, slow MEG wave activity appears to be associated with decreased neuronal activity. Additionally, several studies found an abnormal increase of focal spontaneous beta wave activity (12.5–30 Hz) in the areas of or adjacent to brain lesions (Vieth et al., 1996). There is also evidence for an interhemispheric phase synchrony and amplitude correlation of spontaneous beta oscillations in human subjects (Nikouline et al., 2001). This was interpreted as spontaneous brain activity associated with the resting state. Finally, in a recent study, we were able to detect increased fast MEG activity in the auditory cortex during auditory hallucinations in schizophrenia (Ropohl et al., 2004). This pattern of activation was similar to increases of fMRI signals during auditory hallucinations (Dierks et al., 1999). Therefore, in the present study, we extended these previous findings and hypothesized that patients with OCD may have alterations of their spontaneous MEG activity pattern. We investigated both slow (2–6 Hz) and fast (12.5–30 Hz) spontaneous magnetoencephalographic (MEG) activity in ten patients with OCD compared to ten healthy control subjects.
2.
Results
Patients showed a significant increase of spontaneous MEG activity in the fast frequency range (12.5–30 Hz) over the left hemisphere for both Dtotal and Dmax (Dtotal: 3100 ± 334 versus 2061 ± 222; p < 0.05; Dmax: 78 ± 11 versus 29 ± 10; p < 0.05; Figs. 1A/B). This activity was concentrated over the left super-
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ior temporal gyrus (Fig. 2), while no focal dipole concentration was found for fast MEG activity of the left hemisphere in controls. Values of Dtotal and Dmax of patients were not correlated with scores on the Yale–Brown Obsessive-compulsive scale (Dtotal: r = −0.01; Dmax: r = 0.50; p > 0.05 each). Fast MEG activity of patients' left hemispheres was also significantly increased compared to the corresponding right hemispheres (Dtotal: 3100 ± 334 versus 2268 ± 275; p < 0.05; Dmax: 78 ± 11 versus 38 ± 5; p < 0.05; Figs. 1A/B). In contrast, there were no significant differences for Dtotal and Dmax in the fast frequency range over the right hemispheres of controls and OCD patients (Dtotal: 2268 ± 275 versus 1663 ± 374; p > 0.05; Dmax: 38 ± 5 versus 34 ± 4; p > 0.05; Figs. 1A/B). Spontaneous MEG activity in the slow frequency band (2–6 Hz) was not significantly different over the right hemispheres of patients and controls (Dtotal: 1998 ± 337 versus 2164 ± 236; p > 0.05; Dmax: 41 ± 7 versus 43 ± 7; p > 0.05; Figs. 1C/D). Furthermore; for both patients and controls, the MEG activity showed a widespread distribution and no focal maxima were found when a dipole density analysis was applied, consistent with previous results in healthy subjects (Ropohl et al., 2004; Maihofner et al., 2005). Finally, there was no difference for slow MEG activity over the left hemispheres of patients and controls (Dtotal: 2273 ± 299 versus 2237 ± 198; p > 0.05; Dmax: 46 ± 7 versus 52 ± 27; p > 0.05; Figs. 1C/D). However, in sharp contrast to the control group, where the detected magnetic activity was again widely distributed and no focal maxima were found, the slow MEG activity in OCD patients was found to be enriched over the left dorsolateral prefrontal cortex (Fig. 2B).
3.
Discussion
In the present study, we compared spontaneous MEG recordings of OCD patients with those of a healthy age- and sexmatched control group. Our results provide evidence for an increase of fast MEG activity over the left hemisphere in the OCD group. Magnetic source imaging located this increase to activity in the left superior temporal gyrus. Furthermore, we found an enrichment of slow MEG activity over the left DLPFC in OCD patients, a finding which was absent in controls. Converging evidence in the last decades has suggested a neuronal basis for the pathogenesis of obsessive-compulsive disorder. Neurophysiological findings in OCD have pointed to a dysfunction of frontal cortices (e.g. OF and DLPFC), anterior cingulate cortex, basal ganglia, and other subcortical and limbic structures (Saxena and Rauch, 2000; Rauch et al., 2001). Increased fast MEG activity in the left STG as found in the present study complements these previous studies and agrees with a recent morphometric magnetic resonance study in OCD patients (Choi et al., 2006). Choi and colleagues (2006) investigated gray matter volumes of the STG and found a significant reduction of this cortex in OCD patients compared to controls. This is also in line with studies investigating brain activation during symptom provocation in OCD. Using individually tailored provocative stimuli, Adler and colleagues demonstrated regular activations of temporal cortices in their fMRI study (Adler et al., 2000). Furthermore, studies looking for brain lesions in symptomatic OCD, e.g. following
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Fig. 1 – Spontaneous neuromagnetic activity in fast (A, B) and slow (C, D) frequency ranges in OCD patients and healthy control subjects. MEG activity was quantified by calculating the total dipole number (Dtotal; A, C) and the concentration of dipoles within the area of highest dipole density (density maximum; Dmax; B, D). Corresponding hemispheres are specified in the figure. Black bars indicate MEG activity of patients, gray bars of controls. Data are given as mean ± standard error of the mean. * Indicates p < 0.05. stroke, point to the temporal region being involved in the pathogenesis of OCD (Berthier et al., 1996). This also fits well with previous PET and SPECT studies (Lucey et al., 1995; Simpson and Baldwin, 1995; Cottraux et al., 1996; Hendler et al.,
Fig. 2 – Dipole density analysis of spontaneous focal fast (A) and slow (B) wave magnetic brain activity in one representative patient. Isocontour lines, representing magnetic activity, are projected onto respective cranial MRT slices of the patient. Focal magnetic maxima were located in the left superior temporal gyrus (A) and the left dorsolateral prefrontal cortex (B).
1999). The STG is a brain area crucially involved in the processing of visuospatial information and mental coordination (Mayer et al., 2004). Furthermore, the STG has rich interconnections to the amygdala and the OF (Rempel-Clower and Barbas, 2000; Choi et al., 2006), which is overactive in OCD. Therefore, activity of the OF may influence STG activation or vice versa. We did not observe MEG activity in the OF. However, this is likely due to technical constraints as we used a dual 37channel neuromagnetometer and the sensor arrays were placed above the C3 and C4 position. Therefore, we were not “sensitive” for the whole brain in the present study. The use of the MEG technology also explains why we did not observe activation of the basal ganglia as these deep brain areas are usually not accessible by MEG. All patients described the presence of obsessive thoughts while keeping their eyes closed during the MEG recordings. Nevertheless, the increase of fast MEG activity was not correlated to the severity of OCD symptoms as assessed by the Yale–Brown OCD scale. This may hint at the fact that other neuropsychological features of OCD may be involved in this abnormal MEG activity. Many previous neuropsychological studies have reported cognitive dysfunction in OCD in areas such as executive and selective function, non-verbal memory and visuospatial skills (FlorHenry et al., 1979; Christensen et al., 1992; Savage et al., 1999).
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Although we did not assess visuospatial processing in our patients, abnormal MEG activity in the STG may be involved in such neuropsychological features, based on the function of this brain area (Purcell et al., 1998; Mayer et al., 2004). Alternatively, focal enrichment of MEG activity in the beta range has been reported in areas of structural damage (Vieth et al., 1996). Accordingly, our present findings of focal beta MEG activity in the STG agree with a decrease of the gray matter volume in this cortex in OCD patients (Choi et al., 2006). Finally, there is evidence for an interhemispheric phase synchrony and amplitude correlation of spontaneous beta oscillations in healthy human subjects (Nikouline et al., 2001). This was interpreted as spontaneous brain activity associated with the resting state. Therefore, another possible explanation for fast MEG activity in the STG may be an alteration of the resting state due to attentional processes in OCD. Although the results of the Yale–Brown OCD scale were after the MEG measurement not different from our baseline assessment, the MEG recording itself with eyes closed may have led to a higher degree of “introspection” in the patients, who are presumably more familiar with reflecting their thoughts and behavior. Future studies will help to clarify the relationship between MEG activity and neuropsychological profiles. Furthermore, we found enrichment of slow MEG activity over the left DLPFC. Recent quantitative EEG investigations in OCD patients showed a frontotemporal dysfunction with a significant increase of frontal slow wave activity compared to healthy subjects (Tot et al., 2002; Karadag et al., 2003). This effect was mainly found over the left hemisphere. Therefore, our results of spontaneous MEG measurements confirm EEG findings demonstrating an involvement of frontal cortices in OCD. In agreement with these studies, we found a concentration of slow frequencies in the left frontal lobe. Activation of the DLPFC has been consistently demonstrated during symptom provocation in OCD (Adler et al., 2000; Nakao et al., 2005). Furthermore, fMRI studies in OCD patients demonstrated decreased activation of the DLPFC in test paradigms used to probe planning processes, like the Tower of London task (Van den Heuvel et al., 2005). The DLPFC is involved in planning processes, executive aspects of selective attention and complex processes which operate on the working memory information, like monitoring, manipulation and higher level planning (Van den Heuvel et al., 2003). Planning as assessed by the Tower of London task is compromised in OCD patients (Van den Heuvel et al., 2005). These results fit well with our present finding of enriched slow wave activity over the DLPFC in OCD patients. Nevertheless, a regular comorbidity of OCD is depression (Stein, 2002). Our patients had signs of mild depression as assessed by the Hamilton Depression Rating Scale score. Previously, we were able to demonstrate that depressive patients show abnormally slow MEG activity over their left prefrontal cortex which was found to be significantly reduced following treatment with repetitive transcranial magnetic stimulation (Maihofner et al., 2005). Therefore, as an alternative to the aforementioned possibilities, depressive symptoms might also have influenced the results of spontaneous MEG measurements over frontal cortices in our study. In summary, using MEG, we here demonstrate that OCD patients show abnormally fast MEG activity over their left STG and an enrichment of slow MEG activity over the left DLPFC.
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These results are in line with a frontotemporal dysfunction in OCD. It would be of great interest to further characterize the relationships between MEG activity and individual neuropsychological profiles in future studies.
4.
Experimental procedures
4.1.
Patients and controls
Informed written consent was obtained from all subjects, and the study was approved by the local ethics committee. We included ten right-handed patients diagnosed with OCD (six males, four females; mean age =32.5 ± 6.3 years, disease duration 5–17 years). OCD was diagnosed by a psychiatric consultant (WS) according to the criteria of the DSM-IV classification system. Scores on the Yale–Brown Obsessive-compulsive scale (Goodman et al., 1989) were recorded 2 days before MEG measurements (baseline) and immediately after each MEG measurement (post MEG recording) to define the severity of the symptoms subsequent to the investigation. Baseline and post MEG scores showed no statistically significant differences (baseline score: 26.4 ± 1.2; post MEG score: 26.5 ± 1.4; p > 0.05, t-test for paired samples). Furthermore, OCD patients revealed a mean Hamilton Depression Rating Scale score of 13.5 ± 3.5 indicating mild depressive symptoms. All patients were drug-free 3 weeks before the beginning of the MEG measurements and were exclusively treated with unique psychotherapy (educational program). Before the inclusion phase, all patients were treated with selective serotonin reuptake inhibitors (SSRI) and psychotherapy. SSRIs were either sertraline, paroxetine or citalopram. Therefore, based on the pharmacokinetic properties, it was guaranteed that a time interval of 3 weeks was sufficient to eliminate respective drugs (Preskorn, 1997). Exclusion criteria were a history of focal neurological disorders, systemic illness, head trauma, treatment with electroconvulsive therapy, repetitive magnetic transcranial stimulation, nerve vagus stimulation, schizophrenia, drug abuse or dependence. MEG data were compared with those of 10 healthy age- and sex-matched subjects (six males, four females; mean age 27.4 ± 4.3 years). Matching criterion was age of the individual patient ± 5 years for the corresponding control subject. All patients and control subjects were right-handed as assessed during a medical interview.
4.1.1.
Magnetoencephalography
Cortical activity was recorded with the same dual 37-channel neuromagnetometer (Magnes II®; 4-D Neuroimaging, San Diego, CA) as used previously (Maihofner et al., 2003, 2004, 2005; Ropohl et al., 2004). Sensor arrays were placed with the center above C3 and C4, according to the international 10–20 EEG system. Spontaneous neuromagnetic brain activity was recorded in data sets of 600 s duration from both hemispheres simultaneously at a sampling rate of 520.8 Hz. Online highpass (1.0 Hz) and lowpass (100.0 Hz) filters were applied, and an ECG was recorded. For offline data analysis, an initial 50 Hz notch filter was applied and the magnetic field noise of the heart was removed by ECG triggered digital noise reduction. All raw data sets were carefully checked for artifacts from eye and body movements, and affected sections were excluded from further
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analysis. Digital bandpass filters were applied to analyze slow (2–6 Hz; theta/delta range) and fast (12.5–30 Hz; beta range) frequency bands separately. A principal component analysis was used to select a 10 s period minimum from the whole measurement where one component was predominant in the signal (Vieth et al., 1993; Kamada et al., 1997). This was achieved by analyzing overlapping time sections with a length that corresponded to the mean signal frequency. In those selected time sections, >90% of the signal variance could be attributed to the dominant component and a single source model was considered to be an adequate mathematical model. Single equivalent current dipoles were calculated every 2 ms over the selected data segments using a locally fitted spherical head model. Only dipoles showing statistical correlations between estimated and measured magnetic field distributions of p > 0.9 were accepted for data evaluation. The spatial distribution of dipoles was determined by a 3D convolution with a Gaussian shaped envelope, for which the variance was the localization uncertainty of individual dipole localizations yielding a dipole density plot (DDP) (Vieth et al., 1993; Kamada et al., 1997; Ropohl et al., 2004; Maihofner et al., 2005). Patients' headshapes were digitized using a commercially available sensor position indicator system (Polhemus®; Colchester, Vermont, New England) integrated into the standard Magnes II® system. Using a contour fit technique, MEG localizations were inserted onto an anatomical 3D T1-weighted image acquired with a 1.5 Tesla Magnetom (Magnetom Symphony, Siemens, Germany). Spontaneous neuromagnetic activity was quantified by calculating the total dipole number (Dtotal), and highest dipole density (density maximum; Dmax) from dipole distributions. To visualize the results of this analysis with respect to brain anatomy, the slice containing the density maximum Dmax was used and the dipole density of this slice shown by isocontour lines was superimposed on MRI. Line spacing was chosen to be 1% of Dtotal.
4.2.
Statistical analysis
The data are presented as mean ± standard error of the mean (SEM). Differences between patients and health controls were tested by the t-test for independent samples. Interhemispheric differences within groups were tested by the t-test for paired samples. All statistical tests were two-sided, and a significance level of α < 0.05 was used. Correlations were calculated with the Pearson correlation coefficient. Data were analyzed using SPSS™ 11 (SPSS Inc., Chicago, IL).
Acknowledgment We gratefully thank Tassilo Mathiowetz for his technical support.
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