Quantitative electroencephalographic subtyping of obsessive-compulsive disorder

doi:10.1016/0925-4927(93)90021-9

Psychiatry Research: Neuroimaging

Volume 50, Issue 1, April 1993, Pages 25-32

https://doi.org/10.1016/0925-4927(93)90021-9 Get rights and content

Abstract

Current neuropsychological, electrophysiological, and other imaging data strongly suggest the existence of a neurobiological basis for obsessive-compulsive disorder (OCD), which was long considered to be exclusively of psychogenic origin. The positive response of some OCD patients to neurosurgery, as well as the efficacy of agents that selectively block serotonin reuptake, lends further support to a biological involvement. However, a survey of the treatment literature reveals that only 45–62% of OCD patients improve with these specific medications. In a pilot study using a quantitative electroencephalographic (QEEG) method known as neurometrics, in which QEEG data from OCD patients were compared statistically with those from an age-appropriate normative population, we previously reported the existence of two subtypes of OCD patients within a clinically homogeneous group of patients who met DSM-III-R criteria for OCD. Following pharmacological treatment, a clear relationship was found between treatment response and neurometric cluster membership. In this study, we have expanded the OCD population, adding patients from a second site, and have replicated the existence of two clusters of patients in an enlarged, statistically more robust population. Cluster 1 was characterized by excess relative power in theta, especially in the frontal and frontotemporal regions; cluster 2 was characterized by increased relative power in alpha. Further, 80.0% of the members of cluster 1 were found to be nonresponders to drug treatment, while 82.4% of the members of cluster 2 were found to be treatment responders. These findings suggest the existence of at least two pathophysiological subgroups within the OCD population that share a common clinical expression, but show a differential response to treatment with serotonin reuptake inhibitors.

References (38)

T. Insel et al.
Tricyclic response in obsessive compulsive disorder
Progress in Neuro-Psychopharmacology
(1985)
R. Katz et al.
Clomipramine in obsessive-compulsive disorder
Biological Psychiatry
(1990)
S. Khanna
Obsessive-compulsive disorder: Is there a frontal lobe dysfunction?
Biological Psychiatry
(1988)
L. Baxter
Brain imaging as a tool in establishing a theory of brain pathology in obsessive compulsive disorder
Journal of Clinical Psychiatry
(1990)
L. Baxter et al.
Local cerebral glucose metabolic rates in obsessive-compulsive disorder
Archives of General Psychiatry
(1987)
D. Behar et al.
Computerized tomography and neuropsychological test measures in adolescents with obsessive-compulsive disorder
American Journal of Psychiatry
(1984)
E. Chiocca et al.
Neurosurgical therapy of obsessive-compulsive disorder
C. Conners et al.
Rating scales and checklists for child psychopharmacology
Psychopharmacology Bulletin
(1985)
J. DeVeaugh-Geiss et al.
Clinical predictors of treatment response in obsessive-compulsive disorder: Exploratory analyses from multicenter trials of clomipramine
Psychopharmacology Bulletin
(1990)
P. Flor-Henry et al.
Neuropsychological and power spectral EEG investigations of the obsessive-compulsive syndrome
Biological Psychiatry
(1979)

M. George et al.

Obsessive-compulsive symptoms in neurological disease: A review

Behavior Neurology

(1992)

W. Goodman et al.

Fluvoxamine in the treatment of obsessive-compulsive disorder

W. Goodman et al.

Specificity of serotonin reuptake inhibitors in the treatment of obsessive-compulsive disorder

Archives of General Psychiatry

(1990)

W. Goodman et al.

Efficacy of fluxoxamine in obsessive-compulsive disorder

Archives of General Psychiatry

(1989)

W. Goodman et al.

The Yale-Brown Obsessive-Compulsive Scale: II. Validity

Archives of General Psychiatry

(1989)

W. Goodman et al.

The Yale-Brown Obsessive-Compulsive Scale: I. Development, use, and reliability

Archives of General Psychiatry

(1989)

E. Hollander et al.

Biological aspects of obsessive-compulsive disorder

Psychiatric Annals

(1989)

E. Hollander et al.

Signs of central nervous system dysfunction in obsessive-compulsive disorder

Archives of General Psychiatry

(1990)

T. Insel et al.

Neurological and neuropsychological studies of patients with obsessive-compulsive disorder

Biological Psychiatry

(1983)

Cited by (129)

Obsessive-compulsive disorder (OCD) is associated with increased electroencephalographic (EEG) delta and theta oscillatory power but reduced delta connectivity
2023, Journal of Psychiatric Research
Obsessive-Compulsive Disorder (OCD) is a mental health condition causing significant decline in the quality of life of sufferers and the limited knowledge on the pathophysiology hinders successful treatment. The aim of the current study was to examine electroencephalographic (EEG) findings of OCD to broaden our understanding of the disease. Resting-state eyes-closed EEG data was recorded from 25 individuals with OCD and 27 healthy controls (HC). The 1/f arrhythmic activity was removed prior to computing oscillatory powers of all frequency bands (delta, theta, alpha, beta, gamma). Cluster-based permutation was used for between-group statistical analyses, and comparisons were performed for the 1/f slope and intercept parameters. Functional connectivity (FC) was measured using coherence and debiased weighted phase lag index (d-wPLI), and statistically analyzed using the Network Based Statistic method. Compared to HC, the OCD group showed increased oscillatory power in the delta and theta bands in the fronto-temporal and parietal brain regions. However, there were no significant between-group findings in other bands or 1/f parameters. The coherence measure showed significantly reduced FC in the delta band in OCD compared to HC but the d-wPLI analysis showed no significant differences. OCD is associated with raised oscillatory power in slow frequency bands in the fronto-temporal brain regions, which agrees with the previous literature and therefore is a potential biomarker. Although delta coherence was found to be lower in OCD, due to inconsistencies found between measures and the previous literature, further research is required to ascertain definitive conclusions.
Quantitative electroencephalography (qEEG) clinical applications: a review and update
2023, Introduction to Quantitative EEG and Neurofeedback: Third Edition
In the more than a decade since writing the previous version of this chapter, the development of quantitative EEG (qEEG) as a tool has greatly expanded not only for use in health care but also as an industry encompassing commercial companies offering variations of qEEG measurement sets, as well as professional Boards to provide certification and training companies to provide the professional standards to meet the requirements for certification. This chapter will serve to outline some of the multitudes of clinical applications of qEEG and its continued use in various forms of neurotherapy. As before, case studies will be used to illustrate these applications.
qEEG measurements have expanded from simple measurement derivations across the traditional broad frequency EEG bands of Delta, Theta, Alpha, and Beta to calculations within the EEG spectra in very narrow bands as short as 4 Hz and the calculation of not only a multitude of univariate measures but also complex multivariate measures that can be combined into multivariate algorithms that can describe everything from specific measures of human performance to the variations of behaviors that we have come to define a clinical disorder or syndrome.
Fundamental to qEEG are the “quantitative” aspects of measuring the brain’s electrical signals for neural activity and employing statistical measures of probability to derive clinical meaningfulness from these measures.
Asperger’s syndrome intervention: combining neurofeedback, biofeedback, and metacognition
2023, Introduction to Quantitative EEG and Neurofeedback: Third Edition
Asperger's syndrome, which constitutes a distinct sub-set of symptoms subsumed under the spectrum of autistic disorders, is increasingly being recognized, not only by clinicians, but also by the general public, due to the portrayal of people with Asperger's in media productions. This chapter details the symptoms and the underlying neuroanatomical findings of Asperger's and then goes on to explain appropriate interventions that combine neurofeedback with biofeedback especially heart rate variability (HRV) training and coaching in metacognitive strategies.
Gamma oscillations predict paroxetine response of patients with Obsessive Compulsive Disorder
2021, Journal of Obsessive-Compulsive and Related Disorders
Obsessive compulsive disorder is a distressing psychiatric illness with considerable treatment resistance rates. Prediction of treatment response leads to an increase in patient compliance and a decrease in morbidity. To decrease the treatment resistance rates, valid and useful instruments have been searched. Quantitative electroencephalography (QEEG) based markers have been objective predictors of the treatment response in psychiatric disorders.
This retrospective pilot study aims to explore QEEG as a biomarker to predict early response to paroxetine in OCD patients.
Resting state QEEG and Yale-Brown Obsessive Compulsive Scale (Y-BOCS) were administered to 30 drug-free OCD patients without comorbidity. After maximum 12-week of treatment with paroxetine, patients with and without an early improvement were classified based on at least a 35% reduction in Y-BOCS scores. Pre-treatment QEEG data were compared between the two groups.
Pre-treatment gamma, gamma 1 and gamma 2 oscillations were significantly higher in OCD patients who did not show an early improvement.
These preliminary results indicate that gamma oscillations could be acknowledged as the electrophysiological predictors of early clinical outcomes of OCD patients during paroxetine treatment.
Prediction of treatment resistance in obsessive compulsive disorder patients based on EEG complexity as a biomarker
2020, Clinical Neurophysiology
Citation Excerpt :
The literature includes several studies that used EEG or quantitative EEG (qEEG) for predicting treatment resistance in OCD patients; however, the findings are inconsistent. For instance, 2 subgroups of OCD patients were described using qEEG data: those with increased prefrontal theta power, and those with increased alpha and beta power (Prichep et al., 1993). Interestingly Prichep et al. (1993) and Hansen et al. (2003) reported that the increased theta power subgroup did not respond to treatment, whereas the increased alpha and beta power subgroup did respond to pharmacological treatment.
This study aimed to identify an Electroencephalography (EEG) complexity biomarker that could predict treatment resistance in Obsessive compulsive disorder (OCD) patients. Additionally, the statistical differences between EEG complexity values in treatment-resistant and treatment-responsive patients were determined. Moreover, the existence of correlations between EEG complexity and Yale-Brown Obsessive Compulsive Scale (YBOCS) score were evaluated.
EEG data for 29 treatment-resistant and 28 treatment-responsive OCD patients were retrospectively evaluated. Approximate entropy (ApEn) method was used to extract the EEG complexity from both whole EEG data and filtered EEG data, according to 4 common frequency bands, namely delta, theta, alpha, and beta. The random forests method was used to classify ApEn complexity.
ApEn complexity extracted from beta band EEG segments discriminated treatment-responsive and treatment-resistant OCD patients with an accuracy of 89.66% (sensitivity: 89.44%; specificity: 90.64%). Beta band EEG complexity was lower in the treatment-resistant patients and the severity of OCD, as measured by YBOCS score, was inversely correlated with complexity values.
The results indicate that, EEG complexity could be considered a biomarker for predicting treatment response in OCD patients.
The prediction of treatment response in OCD patients might help clinicians devise and administer individualized treatment plans.
Electrophysiology of obsessive compulsive disorder: A systematic review of the electroencephalographic literature
2019, Journal of Anxiety Disorders
Citation Excerpt :
However, due to the presence of excessive individual variations in alpha activity, interpreting such results is a challenge. An elevation of resting frontotemporal alpha activity, compared to healthy controls was observed in several OCD studies (Bolwig et al., 2007; Desarkar et al., 2007a; Hansen et al., 2003; Ischebeck et al., 2014; Prichep et al., 1993). However, decreased overall alpha (Drake et al., 1996; Karadag et al., 2003), alpha-1 (8–10 Hz) (Bucci et al., 2004) and alpha-2 (10–13 Hz) (Locatelli et al., 1996; Pogarell et al., 2006) activity was noted by others.
Obsessive-compulsive disorder (OCD) is a chronic disease that causes significant decline in the quality of life of those affected. Due to our limited understanding of the underlying pathophysiology of OCD, successful treatment remains elusive. Although many have studied the pathophysiology of OCD through electroencephalography (EEG), limited attempts have been made to synthesize and interpret their findings. To bridge this gap, we conducted a comprehensive literature review using Medline/PubMed and considered the 65 most relevant studies published before June 2018. The findings are categorised into quantitative EEG, sleep related EEG and event related potentials (ERPs). Increased frontal asymmetry, frontal slowing and an enhancement in the ERP known as error related negativity (ERN) were consistent findings in OCD. However, sleep EEG and other ERP (P3 and N2) findings were inconsistent. Additionally, we analysed the usefulness of ERN as a potential candidate endophenotype. We hypothesize that dysfunctional frontal circuitry and overactive performance monitoring are the major underlying impairments in OCD. Additionally, we conceptualized that defective fronto-striato-thalamic circuitry causing poor cerebral functional connectivity gives rise to the OCD behavioural manifestations. Finally, we have discussed transcranial magnetic stimulation and EEG (TMS-EEG) applications in future research to further our knowledge of the underlying pathophysiology of OCD.

View all citing articles on Scopus

View full text

Quantitative electroencephalographic subtyping of obsessive-compulsive disorder

Abstract

Progress in Neuro-Psychopharmacology

Biological Psychiatry

Biological Psychiatry

Brain imaging as a tool in establishing a theory of brain pathology in obsessive compulsive disorder

Journal of Clinical Psychiatry

Local cerebral glucose metabolic rates in obsessive-compulsive disorder

Archives of General Psychiatry

Computerized tomography and neuropsychological test measures in adolescents with obsessive-compulsive disorder

American Journal of Psychiatry

Neurosurgical therapy of obsessive-compulsive disorder

Rating scales and checklists for child psychopharmacology

Psychopharmacology Bulletin

Clinical predictors of treatment response in obsessive-compulsive disorder: Exploratory analyses from multicenter trials of clomipramine

Psychopharmacology Bulletin

Neuropsychological and power spectral EEG investigations of the obsessive-compulsive syndrome

Biological Psychiatry

Obsessive-compulsive symptoms in neurological disease: A review

Behavior Neurology

Fluvoxamine in the treatment of obsessive-compulsive disorder

Specificity of serotonin reuptake inhibitors in the treatment of obsessive-compulsive disorder

Archives of General Psychiatry

Efficacy of fluxoxamine in obsessive-compulsive disorder

Archives of General Psychiatry

The Yale-Brown Obsessive-Compulsive Scale: II. Validity

Archives of General Psychiatry

The Yale-Brown Obsessive-Compulsive Scale: I. Development, use, and reliability

Archives of General Psychiatry

Biological aspects of obsessive-compulsive disorder

Psychiatric Annals

Signs of central nervous system dysfunction in obsessive-compulsive disorder

Archives of General Psychiatry

Neurological and neuropsychological studies of patients with obsessive-compulsive disorder

Biological Psychiatry