Effect of a psychoneurotherapy on brain electromagnetic tomography in individuals with major depressive disorder

Abstract

Recent advances in power spectral analysis of electroencephalography (EEG) signals and brain–computer interface (BCI) technology may significantly contribute to the development of psychoneurotherapies. The goal of this study was to measure the effect of a psychoneurotherapy on brain source generators of abnormal EEG activity in individuals with major depressive disorder (MDD). Thirty participants with unipolar MDD were recruited in the community. The proposed psychoneurotherapy was developed based on the relationship between the localization of abnormal EEG activity and depressive symptomatology. Brain electromagnetic abnormalities in MDD were identified with low resolution brain electromagnetic tomography (LORETA) and a normative EEG database. Localization of brain changes after treatment was assessed through the standardized version of LORETA (sLORETA). Before treatment, excessive high-beta (18–30 Hz) activity was noted in several brain regions located in the fronto-temporal regions. After treatment, only participants who successfully normalized EEG activity in cortico-limbic/paralimbic regions could be considered in clinical remission. In these regions, significant correlations were found between the percentage of change of depressive symptoms and the percentage of reduction in high-beta activity. These results suggest that the normalization of high-beta activity in cortico-limbic/paralimbic regions can be associated with a significant reduction of depressive symptoms.

Introduction

Recent advances in computerized power spectral analysis (PSA) of electroencephalography (EEG) signals (Hughes and John, 1999, Coburn et al., 2006) and brain–computer interface (BCI) technology (Birbaumer et al., 2006, Scott, 2006, Fetz, 2007) may significantly contribute to the development of brain-based psychotherapies (as we may call psychoneurotherapies) in the context of an evidence-based and personalized medicine. With magnetoencephalography, EEG has the best temporal resolution of all functional neuroimaging techniques (Coburn et al., 2006). Further, EEG is the most practical and accessible neuroimaging technique because it is relatively simple and inexpensive. Given this and the compact nature of the equipment, EEG can readily be accommodated by clinics, hospitals and private offices. In regard to data analysis, visual inspection of the time-domain conventional EEG has been regarded as too nonspecific to investigate selective mental disorders. However, computerized PSA has made it possible to link quantitative descriptions of brain electrical activity with specific mental disorders (Hughes and John, 1999, Coburn et al., 2006). In combination with clinical assessment, computerized PSA is used as an adjunct in differential diagnostic and subtyping of depressive disorders (John et al., 1988, Lieber and Prichep, 1988, Pizzagalli et al., 2002). It is also utilized to predict the most effective pharmacological treatment for a given patient (Suffin and Emory, 1995, Hunter et al., 2007).

Computerized PSA has greatly benefited from the development of three-dimensional brain source localization methods such as low resolution brain electromagnetic tomography (LORETA) (Pascual-Marqui et al., 1994) and standardized LORETA (sLORETA) (Pascual-Marqui, 2002). In LORETA, intracranial generators of brain activity detected on the scalp are mathematically estimated by constraining the inverse solution to an anatomical template of the brain. Using this method, Pizzagalli et al. (2002) found in individuals with major depressive disorder (MDD) abnormally elevated high-beta activity (21–30 Hz) in the right prefrontal cortex (BA 9/10/11), combined with abnormally low high-beta activity in the precuneus/posterior cingulate regions. Importantly, EEG is the only neuroimaging technique that allows statistical comparison of individual recordings with age-matched or age regression life-span normative databases (John et al., 1988, Thatcher et al., 2003, Thatcher et al., 2005, Gordon et al., 2005, Prichep, 2005). These databases permit the detection of deficient or excessive EEG power and EEG coherence within each patient evaluated without having to create a local control group. With respect to this question, the FDA-approved University of Maryland life-span EEG normative database (Thatcher et al., 2003) permits a comparison of the estimated intracerebral current density distribution with LORETA (Thatcher et al., 2005). It has been previously proposed that LORETA (Saletu et al., 2005) and this normative database (Thatcher et al., 2005) may be useful for the diagnoses and treatment of psychiatric disorders.

There is mounting evidence that emotional dysregulation in MDD is related to a dysfunction of the neural circuitry supporting emotional self-regulation (Drevets, 2000, Mayberg, 2003, Seminowicz et al., 2004, Beauregard et al., 2006). Self-regulation of brain activity through operant control and on-line computerized feedback has been demonstrated a few decades ago with EEG (Fetz, 1969, Rosenfeld et al., 1969, Nowlis and Kamiya, 1970). Previous work conducted by our research team suggests that self-regulation of EEG activity via a BCI was able to functionally normalize the brain systems mediating selective attention and response inhibition in children with attention-deficit hyperactivity disorder (Lévesque and Beauregard, 2006). Recent functional magnetic resonance imaging (fMRI) studies have shown that by receiving continuous feedback about regional blood–oxygen-level dependent (BOLD) signals through a BCI, healthy individuals can learn to increase the magnitude of the BOLD signal responses within and across fMRI sessions (Weiskopf et al., 2003). Regarding this issue, it has been demonstrated that chronic pain patients can decrease their perception of pain by self-regulating BOLD activity in the anterior cingulate cortex (deCharms et al., 2005). As for MDD, the results of a small number of studies indicate that a BCI intervention based on EEG data may be successfully used to reduce depressive symptoms (Rosenfeld, 2000, Hammond, 2005). However, these studies have been done with only a few participants and without measuring whole-brain activity before vs. after treatment. Furthermore, the electrode sites and frequency band to train were determined a priori, based strictly on the literature.

The main goal of this exploratory study was to measure, using a before–after trial design, the effect of a psychoneurotherapy (PNT) on brain source generators of abnormal EEG activity in individuals with MDD. This PNT was developed based on the linkage between the localization of abnormal brain activity and symptoms in the current MDD sample. This brain-based psychotherapy uses a BCI allowing real-time self-regulation of brain activity mediating emotional and cognitive symptoms of depression. To our knowledge, this is the first study measuring the neurobiological and psychological effects of a PNT in MDD. The central aim of this PNT was to help depressed participants to self-regulate the abnormal brain activity via a BCI while learning to decrease their negative thoughts and emotional feelings. We predicted that the post-treatment evaluation (compared with the pre-treatment evaluation) would reveal a significant normalization of EEG abnormalities associated with a substantial decrease of depressive symptoms.