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Obsessive-compulsive dimension localized using low-resolution brain electromagnetic tomography (LORETA)
Neuroscience Letters 387 (2005) 72–74
Obsessive-compulsive dimension localized using low-resolution brain electromagnetic tomography (LORETA) Leslie Sherlin a,c,∗ , Marco Congedo b,c a
Harold Able School of Psychology, Capella University, Minneapolis, MN, USA b France Telecom R&D, Meylan, France c Nova Tech EEG Inc., Knoxville, TN, USA
Received 2 May 2005; received in revised form 8 June 2005; accepted 29 June 2005
Abstract Electroencephalographic mapping techniques have been used to show differences between normal subjects and those diagnosed with various mental disorders. To date, there is no other research using the techniques of low-resolution brain electromagnetic tomography (LORETA) with the obsessive-compulsive disorder (OCD) population. The current investigation compares current source density measures of persons with OCD symptoms to an age-matched control group. The main finding is excess current source density in the Beta frequencies in the cingulate gyrus. This Beta activity is primarily located in the middle cingulate gyrus as well as adjacent frontal parieto-occipital regions. Lower frequency Beta is prominent more anteriorly in the cingulate gyrus whereas higher frequency Beta is seen more posteriorly. These preliminary findings indicate the utility of LORETA as a clinical and diagnostic tool. © 2005 Elsevier Ireland Ltd. All rights reserved.
Electroencephalographic mapping techniques have been used to show differences between normal subjects and those diagnosed with various mental disorders. Studies have been conducted previously on depression [10], attention-deficit disorder [2] and other more disorders such as schizophrenia [8]. Quantitative electroencephalographic (QEEG) mapping techniques have traditionally been used [2] whereas others have also incorporated low-resolution electromagnetic tomography (LORETA) ([8,10]. Combined, these studies have illustrated the usefulness of such mapping techniques in the diagnosis and treatment of these disorders. QEEG and LORETA techniques are useful in treating disorders through increased accuracy in diagnoses, medication response prediction and potentially through EEG-based biofeedback [5]. Previous QEEG research on obsessive-compulsive disorder (OCD) has indicated an excess of Alpha and Beta activity in the central channels when analyzed using QEEG techniques [11]. However, to date, there is no current research using the ∗ Corresponding author at: Capella University, School of Psychology, 8503 E. Keats Avenue, Mesa, AZ 85208, USA. Tel.: +1 480 797 9304. E-mail address: [email protected] (L. Sherlin).
0304-3940/$ – see front matter © 2005 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.neulet.2005.06.069
techniques of LORETA with the OCD population. The current investigation compares current source density measures of persons with OCD symptoms to an age-matched control group. The data for this study was selected from an archived database of 108 adult clients who had presented for evaluation of various complaints. All clients had completed a Symptom Checklist—Revised (SCL-90-R) and had an electroencephalograph (EEG) recording scalp electrical potentials as part of the assessment. To be included in the clinical group the subject must have scored a t-value of 67 (95 percentile) or higher on the obsessive-compulsive dimension of the SCL90-R, with all other dimensions having a t-value below 63 (90 percentile). There are no specific studies that could be found to address the correlation of obsessive-compulsive dimension to obsessive-compulsive disorder. However, the individuals included in the clinical population scored at the 67 t-value are in the 95% of the normative sample for those symptoms included in the obsessive-compulsive dimension, which were the same as those required for the obsessive compulsive disorder diagnosis by the DSM-IV-TR [1]. There were eight subjects from the sample of 108 that fit these criteria. The
L. Sherlin, M. Congedo / Neuroscience Letters 387 (2005) 72–74
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Fig. 1. From top to bottom are the spatial distributions of t-statistics for Beta 1 (a), Beta 2 (b), Beta 3 (c), Beta 4 (d) and Beta 5 (e). Only significant statistics (p = 0.05 corrected) are shown. The distributions are shown by an axial (view from the top), sagittal (view from the left) and coronal (view from the back) slice passing thought the voxel with maximal t-value. Each image is sliced at its own maximum. In axial and coronal view left of picture is left of the brain. In sagittal view left of picture is front of the brain. The t-distribution is linearly color-coded with red being the maximum of each image and white being zero. Non-significant statistics are coded as zero. At the top of each image are printed the x, y and z Talairach coordinates of the voxel where the maximum was found.
requirement for inclusion in the control group was that the subject could not have a t-value of 63 (90 percentile) or higher on any dimension. Subjects that met this requirement were selected by age match to the clinical group. The clinical and control groups were age matched but the constraints of inclusion did not allow for sex match. The control group consisted of three females and five males and the clinical group included four females and four males. All subjects were between the ages of 17 and 29 years old. The mean age was 23.1 and 4.04 standard deviations. Brain electrical activity had been digitally recorded on a LEXICOR NeuroSearch-24 system from 19 scalp electrodes, according to the International 10-20 System of electrode placement. Electrode impedances were reduced to below 5 k. EEG was recorded continuously in the awakened state with eyes closed and open and during active task conditions. For this study, the eyes closed data was imported into the EureKa! software [3] for precise artifact rejection and for computing the cross-spectral analysis for each subject in nine bands. These bands were Delta (2–3.5 Hz), Theta (4–7.5 Hz), Alpha1 (8–10 Hz), Alpha2 (10–12 Hz), Beta1 (12–16 Hz), Beta2 (16–20 Hz), Beta3 (20–24 Hz), Beta4 (24–28 Hz) and Beta 5 (28–32 Hz). Each group’s cross-spectra was computed and the two groups compared using a t-sum procedure which is a multiple comparison procedure based on a combination of test–statistics [4]. LORETA difference maps for the nine frequencies were displayed using the LORETA Key software [9]. There is a main finding of excess current source density in the Beta frequencies in the cingulate gyrus. The Beta frequencies are primarily located in the middle cingulate gyrus as well as adjacent frontal parieto-occipital regions. However, when this Beta is examined in narrower defined frequency bands, each localizes in a slightly different location. Lower frequency Beta is prominent more anteriorly in the cingulate gyrus whereas higher frequency beta is seen more posteriorly (see Fig. 1). This study is aimed at finding the location of current source density differences between two groups that differed on the obsessive-compulsive dimension of the SCL-90-R.
Other dimensions are not considered except that they have a t-value of less than 63 (90 percentile). For this study, OCD is defined and measured by the SCL-90-R as “symptoms that are often identified with the standard clinical syndrome of the same name.” This measure focuses on thoughts, impulses and actions that are experienced as unremitting and irresistible and that are of an ego-alien or unwanted nature [6]. The finding is that individuals who subscribe to symptomatology of OCD have excess Beta activity in the cingulate gyrus when compared to a non-OCD control group. This is consistent with the [11] QEEG finding of excess central Beta, but is not corroborative of their finding of excess central Alpha. A probable explanation is that clinical symptoms may be present within the groups used in this study, which may not be measured by the SCL-90-R. As measured by this scale, the control group is a normal group and the OCD group had no other dimensions of clinical significance. Surgical treatment of refractory cases of OCD have sometimes involved small anterior cingulotomies [7]. In this study the primary results were in the middle cingulate gyrus. Based on the high signal-to-noise ratio of the EEG recordings, we do not believe that LORETA introduced large (>2 cm) localization errors for this data. Indeed, significant differences in Beta1 cover the anterior cingulate and the areas usually involved in anterior cingulotomy. Our findings suggest that in addition to these regions, overactivation of the middle cingulate gyrus also plays an important role in OCD symptoms. In general, the higher the Beta frequency range the more posterior the portion of the middle cingulate involved. Further studies should explore other scales measuring OCD symptoms to evaluate the specificity of these findings using the SCL-90-R. Despite the limitations, this preliminary study demonstrates the utility of LORETA as a clinical tool.
References [1] American Psychiatric Association, Diagnostic and Statistical Manual of Mental Disorders, 4th Ed.—Text Revision, American Psychiatric Association, Washington DC, 2000.
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L. Sherlin, M. Congedo / Neuroscience Letters 387 (2005) 72–74
[2] R.J. Chabot, G. Serfontein, Quantitative electroencephalographic profiles of children with attention deficit disorder, Biol. Psychiatry 40 (10) (1996) 951–963. [3] M. Congedo, EureKa! (Version 3.0) [Computer Software], NovaTech EEG, Inc., Knoxville, TN, 2002. [4] M. Congedo, L. Finos, F. Turkheimer, A multiple hypothesis test procedure based on the sum of test–statistics, Tenth Annual Meeting of the Organization for Human Brain Mapping, June 13–17, Budapest, Hungary, 2004 (Abstract, on CD). [5] M. Congedo, J.F. Lubar, D. Joffe, Low-resolution electromagnetic tomography neurofeedback, IEEE Trans. Neural Syst. Rehabil. Eng. 12 (4) (2004) 387–397. [6] L.R. Derogatis, Symptom Checklist-90-R (SCL-90-R) Administration, Scoring, and Procedures Manual, third ed., National Computer Systems, Minneapolis, 1994. [7] C.H. Kim, J.W. Chang, M.S. Koo, J.W. Kim, H.S. Suh, I.H. Park, H.S. Lee, Anterior cingulotomy for refractory obsessive-compulsive disorder, Acta Psychiatr. Scand. 107 (4) (2003) 283–290.
[8] R.D. Pascual-Marqui, Review of methods for solving the EEG inverse problem, Int. J. Bioelectromagn. 1 (1) (1999) 75–86. [9] R.D. Pascual-Marqui, D. Lehmann, T. Koenig, K. Kochi, M.C. Merlo, D. Hell, M. Koukkou, Low resolution brain electromagnetic tomography (LORETA) functional imaging in acute, neurolepticnaive, first-episode, productive schizophrenia, Psychiatry Res. 90 (3) (1999) 169–179. [10] D.A. Pizzagalli, J.B. Nitschke, T.R. Oakes, A.M. Hendrick, K.A. Horras, C.L. Larson, H.C. Abercrombie, S.M. Schaefer, J.V. Koger, R.M. Benca, R.D. Pascual-Marqui, R.J. Davidson, Brain electrical tomography in depression: the importance of symptom severity, anxiety, and melancholic features, Biol. Psychiatry 52 (2) (2002) 73– 85. [11] L.S. Prichep, F. Mas, E. Hollander, M. Liebowitz, E.R. John, M. Almas, C.M. DeCaria, R.H. Levine, Quantitative electroencephalographic subtyping of obsessive-compulsive disorder, Psychiatry Res. 50 (1) (1993) 25–32.
Obsessive-compulsive dimension localized using low-resolution brain electromagnetic tomography (LORETA) Leslie Sherlin a,c,∗ , Marco Congedo b,c a
Harold Able School of Psychology, Capella University, Minneapolis, MN, USA b France Telecom R&D, Meylan, France c Nova Tech EEG Inc., Knoxville, TN, USA
Received 2 May 2005; received in revised form 8 June 2005; accepted 29 June 2005
Abstract Electroencephalographic mapping techniques have been used to show differences between normal subjects and those diagnosed with various mental disorders. To date, there is no other research using the techniques of low-resolution brain electromagnetic tomography (LORETA) with the obsessive-compulsive disorder (OCD) population. The current investigation compares current source density measures of persons with OCD symptoms to an age-matched control group. The main finding is excess current source density in the Beta frequencies in the cingulate gyrus. This Beta activity is primarily located in the middle cingulate gyrus as well as adjacent frontal parieto-occipital regions. Lower frequency Beta is prominent more anteriorly in the cingulate gyrus whereas higher frequency Beta is seen more posteriorly. These preliminary findings indicate the utility of LORETA as a clinical and diagnostic tool. © 2005 Elsevier Ireland Ltd. All rights reserved.
Electroencephalographic mapping techniques have been used to show differences between normal subjects and those diagnosed with various mental disorders. Studies have been conducted previously on depression [10], attention-deficit disorder [2] and other more disorders such as schizophrenia [8]. Quantitative electroencephalographic (QEEG) mapping techniques have traditionally been used [2] whereas others have also incorporated low-resolution electromagnetic tomography (LORETA) ([8,10]. Combined, these studies have illustrated the usefulness of such mapping techniques in the diagnosis and treatment of these disorders. QEEG and LORETA techniques are useful in treating disorders through increased accuracy in diagnoses, medication response prediction and potentially through EEG-based biofeedback [5]. Previous QEEG research on obsessive-compulsive disorder (OCD) has indicated an excess of Alpha and Beta activity in the central channels when analyzed using QEEG techniques [11]. However, to date, there is no current research using the ∗ Corresponding author at: Capella University, School of Psychology, 8503 E. Keats Avenue, Mesa, AZ 85208, USA. Tel.: +1 480 797 9304. E-mail address: [email protected] (L. Sherlin).
0304-3940/$ – see front matter © 2005 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.neulet.2005.06.069
techniques of LORETA with the OCD population. The current investigation compares current source density measures of persons with OCD symptoms to an age-matched control group. The data for this study was selected from an archived database of 108 adult clients who had presented for evaluation of various complaints. All clients had completed a Symptom Checklist—Revised (SCL-90-R) and had an electroencephalograph (EEG) recording scalp electrical potentials as part of the assessment. To be included in the clinical group the subject must have scored a t-value of 67 (95 percentile) or higher on the obsessive-compulsive dimension of the SCL90-R, with all other dimensions having a t-value below 63 (90 percentile). There are no specific studies that could be found to address the correlation of obsessive-compulsive dimension to obsessive-compulsive disorder. However, the individuals included in the clinical population scored at the 67 t-value are in the 95% of the normative sample for those symptoms included in the obsessive-compulsive dimension, which were the same as those required for the obsessive compulsive disorder diagnosis by the DSM-IV-TR [1]. There were eight subjects from the sample of 108 that fit these criteria. The
L. Sherlin, M. Congedo / Neuroscience Letters 387 (2005) 72–74
73
Fig. 1. From top to bottom are the spatial distributions of t-statistics for Beta 1 (a), Beta 2 (b), Beta 3 (c), Beta 4 (d) and Beta 5 (e). Only significant statistics (p = 0.05 corrected) are shown. The distributions are shown by an axial (view from the top), sagittal (view from the left) and coronal (view from the back) slice passing thought the voxel with maximal t-value. Each image is sliced at its own maximum. In axial and coronal view left of picture is left of the brain. In sagittal view left of picture is front of the brain. The t-distribution is linearly color-coded with red being the maximum of each image and white being zero. Non-significant statistics are coded as zero. At the top of each image are printed the x, y and z Talairach coordinates of the voxel where the maximum was found.
requirement for inclusion in the control group was that the subject could not have a t-value of 63 (90 percentile) or higher on any dimension. Subjects that met this requirement were selected by age match to the clinical group. The clinical and control groups were age matched but the constraints of inclusion did not allow for sex match. The control group consisted of three females and five males and the clinical group included four females and four males. All subjects were between the ages of 17 and 29 years old. The mean age was 23.1 and 4.04 standard deviations. Brain electrical activity had been digitally recorded on a LEXICOR NeuroSearch-24 system from 19 scalp electrodes, according to the International 10-20 System of electrode placement. Electrode impedances were reduced to below 5 k. EEG was recorded continuously in the awakened state with eyes closed and open and during active task conditions. For this study, the eyes closed data was imported into the EureKa! software [3] for precise artifact rejection and for computing the cross-spectral analysis for each subject in nine bands. These bands were Delta (2–3.5 Hz), Theta (4–7.5 Hz), Alpha1 (8–10 Hz), Alpha2 (10–12 Hz), Beta1 (12–16 Hz), Beta2 (16–20 Hz), Beta3 (20–24 Hz), Beta4 (24–28 Hz) and Beta 5 (28–32 Hz). Each group’s cross-spectra was computed and the two groups compared using a t-sum procedure which is a multiple comparison procedure based on a combination of test–statistics [4]. LORETA difference maps for the nine frequencies were displayed using the LORETA Key software [9]. There is a main finding of excess current source density in the Beta frequencies in the cingulate gyrus. The Beta frequencies are primarily located in the middle cingulate gyrus as well as adjacent frontal parieto-occipital regions. However, when this Beta is examined in narrower defined frequency bands, each localizes in a slightly different location. Lower frequency Beta is prominent more anteriorly in the cingulate gyrus whereas higher frequency beta is seen more posteriorly (see Fig. 1). This study is aimed at finding the location of current source density differences between two groups that differed on the obsessive-compulsive dimension of the SCL-90-R.
Other dimensions are not considered except that they have a t-value of less than 63 (90 percentile). For this study, OCD is defined and measured by the SCL-90-R as “symptoms that are often identified with the standard clinical syndrome of the same name.” This measure focuses on thoughts, impulses and actions that are experienced as unremitting and irresistible and that are of an ego-alien or unwanted nature [6]. The finding is that individuals who subscribe to symptomatology of OCD have excess Beta activity in the cingulate gyrus when compared to a non-OCD control group. This is consistent with the [11] QEEG finding of excess central Beta, but is not corroborative of their finding of excess central Alpha. A probable explanation is that clinical symptoms may be present within the groups used in this study, which may not be measured by the SCL-90-R. As measured by this scale, the control group is a normal group and the OCD group had no other dimensions of clinical significance. Surgical treatment of refractory cases of OCD have sometimes involved small anterior cingulotomies [7]. In this study the primary results were in the middle cingulate gyrus. Based on the high signal-to-noise ratio of the EEG recordings, we do not believe that LORETA introduced large (>2 cm) localization errors for this data. Indeed, significant differences in Beta1 cover the anterior cingulate and the areas usually involved in anterior cingulotomy. Our findings suggest that in addition to these regions, overactivation of the middle cingulate gyrus also plays an important role in OCD symptoms. In general, the higher the Beta frequency range the more posterior the portion of the middle cingulate involved. Further studies should explore other scales measuring OCD symptoms to evaluate the specificity of these findings using the SCL-90-R. Despite the limitations, this preliminary study demonstrates the utility of LORETA as a clinical tool.
References [1] American Psychiatric Association, Diagnostic and Statistical Manual of Mental Disorders, 4th Ed.—Text Revision, American Psychiatric Association, Washington DC, 2000.
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L. Sherlin, M. Congedo / Neuroscience Letters 387 (2005) 72–74
[2] R.J. Chabot, G. Serfontein, Quantitative electroencephalographic profiles of children with attention deficit disorder, Biol. Psychiatry 40 (10) (1996) 951–963. [3] M. Congedo, EureKa! (Version 3.0) [Computer Software], NovaTech EEG, Inc., Knoxville, TN, 2002. [4] M. Congedo, L. Finos, F. Turkheimer, A multiple hypothesis test procedure based on the sum of test–statistics, Tenth Annual Meeting of the Organization for Human Brain Mapping, June 13–17, Budapest, Hungary, 2004 (Abstract, on CD). [5] M. Congedo, J.F. Lubar, D. Joffe, Low-resolution electromagnetic tomography neurofeedback, IEEE Trans. Neural Syst. Rehabil. Eng. 12 (4) (2004) 387–397. [6] L.R. Derogatis, Symptom Checklist-90-R (SCL-90-R) Administration, Scoring, and Procedures Manual, third ed., National Computer Systems, Minneapolis, 1994. [7] C.H. Kim, J.W. Chang, M.S. Koo, J.W. Kim, H.S. Suh, I.H. Park, H.S. Lee, Anterior cingulotomy for refractory obsessive-compulsive disorder, Acta Psychiatr. Scand. 107 (4) (2003) 283–290.
[8] R.D. Pascual-Marqui, Review of methods for solving the EEG inverse problem, Int. J. Bioelectromagn. 1 (1) (1999) 75–86. [9] R.D. Pascual-Marqui, D. Lehmann, T. Koenig, K. Kochi, M.C. Merlo, D. Hell, M. Koukkou, Low resolution brain electromagnetic tomography (LORETA) functional imaging in acute, neurolepticnaive, first-episode, productive schizophrenia, Psychiatry Res. 90 (3) (1999) 169–179. [10] D.A. Pizzagalli, J.B. Nitschke, T.R. Oakes, A.M. Hendrick, K.A. Horras, C.L. Larson, H.C. Abercrombie, S.M. Schaefer, J.V. Koger, R.M. Benca, R.D. Pascual-Marqui, R.J. Davidson, Brain electrical tomography in depression: the importance of symptom severity, anxiety, and melancholic features, Biol. Psychiatry 52 (2) (2002) 73– 85. [11] L.S. Prichep, F. Mas, E. Hollander, M. Liebowitz, E.R. John, M. Almas, C.M. DeCaria, R.H. Levine, Quantitative electroencephalographic subtyping of obsessive-compulsive disorder, Psychiatry Res. 50 (1) (1993) 25–32.