Altered EEG lagged coherence during rest in obsessive-compulsive disorder

Exploring functional connectivity in large-scale brain networks in obsessive-compulsive disorder: a systematic review of EEG and fMRI studies

Obsessive-compulsive disorder (OCD) is a debilitating psychiatric condition that is difficult to treat due to our limited understanding of its pathophysiology. Functional connectivity in brain networks, as evaluated through neuroimaging studies, plays a pivotal role in understanding OCD. While both electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) have been extensively employed in OCD research, few have fully synthesized their findings. To bridge this gap, we reviewed 166 studies (10 EEG, 156 fMRI) published up to December 2023. In EEG studies, OCD exhibited lower connectivity in delta and alpha bands, with inconsistent findings in other frequency bands. Resting-state fMRI studies reported conflicting connectivity patterns within the default mode network (DMN) and sensorimotor cortico-striato-thalamo-cortical (CSTC) circuitry. Many studies observed decreased resting-state connectivity between the DMN and salience network (SN), implicating the 'triple network model' in OCD. Task-related hyperconnectivity within the DMN-SN and hypoconnectivity between the SN and frontoparietal network suggest OCD-related cognitive inflexibility, potentially due to triple network dysfunction. In conclusion, our review highlights diverse connectivity differences in OCD, revealing complex brain network interplay that contributes to symptom manifestation. However, the presence of conflicting findings underscores the necessity for targeted research to achieve a comprehensive understanding of the pathophysiology of OCD.

Long-range temporal correlations in resting state alpha oscillations in major depressive disorder and obsessive-compulsive disorder

Introduction

Mental disorders are a significant concern in contemporary society, with a pressing need to identify biological markers. Long-range temporal correlations (LRTC) of brain rhythms have been widespread in clinical cohort studies, especially in major depressive disorder (MDD). However, research on LRTC in obsessive-compulsive disorder (OCD) is severely limited. Given the high co-occurrence of OCD and MDD, we conducted a comparative LRTC investigation. We assumed that the LRTC patterns will allow us to compare measures of brain cortical balance of excitation and inhibition in OCD and MDD, which will be useful in the area of differential diagnosis.

Methods

In this study, we used the 64-channel resting state EEG of 29 MDD participants, 26 OCD participants, and a control group of 37 volunteers. Detrended fluctuation analyzes was used to assess LRTC.

Results

Our results indicate that all scaling exponents of the three subject groups exhibited persistent LRTC of EEG oscillations. There was a tendency for LRTC to be higher in disorders than in controls, but statistically significant differences were found between the OCD and control groups in the entire frontal and left parietal occipital areas, and between the MDD and OCD groups in the middle and right frontal areas.

Discussion

We believe that these results indicate abnormalities in the inhibitory and excitatory neurotransmitter systems, predominantly affecting areas related to executive functions.

Modification of cortical electrical activity in stroke survivors with abnormal subjective visual vertical: An eLORETA study

Objectives

Balance impairment is among the main complications of stroke. The gravity-based subjective vertical (SV) is considered an important reference for upright posture and navigation affected by stroke. The correlation between injury location and pathological perception of verticality remains controversial. This study aimed to evaluate the cortico-cortical network of vertical perception among patients with the right hemisphere stroke and abnormal visual-vertical perception compared with healthy individuals.

Materials and methods

This observational cross-sectional study included 40 patients with the right hemisphere stroke and 35 healthy participants. All patients had abnormal visual-vertical perception. The EEG connectivity analysis was conducted through the exact low-resolution brain electromagnetic tomography analysis (eLORETA).

Results

Stroke survivors manifested a power spectral density that reduced within the beta-2 frequency band in the left hemisphere and increased within the beta-3 frequency band in the right hemisphere compared with controls (p < 0.01). The lagged-phase synchronization was increased within alpha-1, beta-2, and beta-3 bands and decreased in stroke survivors compared with controls in the vestibular network involved in visual-vertical perception (p < 0.01).

Conclusion

The results of this study demonstrated variations in the function and functional connectivity of cortical areas involved in the visual-vertical perception that are mainly located in the vestibular cortex.

Obsessive-compulsive disorder (OCD) is associated with increased electroencephalographic (EEG) delta and theta oscillatory power but reduced delta connectivity

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.

The time scales of irreversibility in spontaneous brain activity are altered in obsessive compulsive disorder

We study how obsessive-compulsive disorder (OCD) affects the complexity and time-reversal symmetry-breaking (irreversibility) of the brain resting-state activity as measured by magnetoencephalography (MEG). Comparing MEG recordings from OCD patients and age/sex matched control subjects, we find that irreversibility is more concentrated at faster time scales and more uniformly distributed across different channels of the same hemisphere in OCD patients than in control subjects. Furthermore, the interhemispheric asymmetry between homologous areas of OCD patients and controls is also markedly different. Some of these differences were reduced by 1-year of Kundalini Yoga meditation treatment. Taken together, these results suggest that OCD alters the dynamic attractor of the brain's resting state and hint at a possible novel neurophysiological characterization of this psychiatric disorder and how this therapy can possibly modulate brain function.

Disrupted resting-state functional connectivity of frontal network in opium use disorder

Opioid use disorder (OUD) as a chronic relapsing disorder is initially driven by dysfunction of brain reward networks and associated with several psychiatric disorders. Resting-state EEG was recorded in 24 healthy participants as well as 31 patients with OUD. Healthy participants do not meet OUD criteria. After pre-processing of the raw EEG, functional connectivity in the frontal network using eLORETA and all networks using graph analysis method were calculated. Patients with OUD had higher electrical neuronal activity compared to healthy participants in higher frequency bands. The statistical analysis revealed that patients with OUD had significantly decreased phase synchronization in β1 and β2 frequency bands compared with the healthy group in the frontal network. Regarding global network topology, we found a significant decrease in the characteristic path length and an increase in global efficiency, clustering coefficient, and transitivity in patients compared with the healthy group. These changes indicated that local specialization and global integration of the brain were disrupted in OUD and it suggests a tendency toward random network configuration of functional brain networks in patients with OUD. Disturbances in EEG-based brain network indices might reflect an altered cortical functional network in OUD. These findings might provide useful biomarkers to understand cortical brain pathology in opium use disorder.

Temporal and spatial variability of dynamic microstate brain network in early Parkinson's disease

Changes of brain network dynamics reveal variations in macroscopic neural activity patterns in behavioral and cognitive aspects. Quantification and application of changed dynamics in brain functional connectivity networks may contribute to a better understanding of brain diseases, and ultimately provide better prognostic indicators or auxiliary diagnostic tools. At present, most studies are focused on the properties of brain functional connectivity network constructed by sliding window method. However, few studies have explored evidence-based brain network construction algorithms that reflect disease specificity. In this work, we first proposed a novel approach to characterize the spatiotemporal variability of dynamic functional connectivity networks based on electroencephalography (EEG) microstate, and then developed a classification framework for integrating spatiotemporal variability of brain networks to improve early Parkinson's disease (PD) diagnostic performance. The experimental results indicated that compared with the brain network construction method based on conventional sliding window, the proposed method significantly improved the performance of early PD recognition, demonstrating that the dynamic spatiotemporal variability of microstate-based brain networks can reflect the pathological changes in the early PD brain. Furthermore, we observed that the spatiotemporal variability of early PD brain network has a specific distribution pattern in brain regions, which can be quantified as the degree of motor and cognitive impairment, respectively. Our work offers innovative methodological support for future research on brain network, and provides deeper insights into the spatiotemporal interaction patterns of brain activity and their variabilities in early PD.

A recent suicide attempt and the heartbeat: Electrophysiological findings from a trans-diagnostic cohort of patients and healthy controls

Suicidal behavior is influenced by a multitude of factors, making prediction and prevention of suicide attempts (SA) a challenge. A useful tool to uncover underlying pathophysiology or propose new therapy approaches are biomarkers, especially within the context of point-of-care tests. Heart rate variability (HRV) is a well-established biomarker of mental health, and measures the activity of the sympathetic and parasympathetic nervous system (PNS). Previous studies reported a correlation between lower PNS activity and suicidality. However, most studies involved participants from a healthy population, patients without history of suicide attempts, or patients with a single diagnosis. 52 in-patients with a recent suicide attempt (<6 months), and 43 controls without history of SA or psychiatric diagnoses confirmed study participation. The included patients age ranged between 18 and 65 years, 65% had psychiatric comorbidities. Patients with dementia, cognitive impairments, acute psychosis, chronic non suicidal self-harming behavior, or current electroconvulsive therapy were excluded. A 15-min resting state electrocardiography was recorded with two bipolar electrodes attached to the right and left insides of the wrists. The multiple regression analyses showed lower parasympathetic, and higher sympathetic activity in patients compared to controls. Partial correlation found a positive trend result between self-reported suicidality and the very low frequency band. ROC curve analysis revealed an acceptable to excellent clinical accuracy of HRV parameters. Therefore, HRV parameters could be reliable discriminative biomarkers between in-patients with a recent SA and healthy controls. One limitation is the lack of a control group consisting of in-patients without life-time suicidal ideation or attempts.

Modeling Brain Functional Connectivity Patterns during an Isometric Arm Force Exertion Task at Different Levels of Perceived Exertion: A Graph Theoretical Approach

The perception of physical exertion is the cognitive sensation of work demands associated with voluntary muscular actions. Measurements of exerted force are crucial for avoiding the risk of overexertion and understanding human physical capability. For this purpose, various physiological measures have been used; however, the state-of-the-art in-force exertion evaluation lacks assessments of underlying neurophysiological signals. The current study applied a graph theoretical approach to investigate the topological changes in the functional brain network induced by predefined force exertion levels for twelve female participants during an isometric arm task and rated their perceived physical comfort levels. The functional connectivity under predefined force exertion levels was assessed using the coherence method for 84 anatomical brain regions of interest at the electroencephalogram (EEG) source level. Then, graph measures were calculated to quantify the network topology for two frequency bands. The results showed that high-level force exertions are associated with brain networks characterized by more significant clustering coefficients (6%), greater modularity (5%), higher global efficiency (9%), and less distance synchronization (25%) under alpha coherence. This study on the neurophysiological basis of physical exertions with various force levels suggests that brain regions communicate and cooperate higher when muscle force exertions increase to meet the demands of physically challenging tasks.

Decreased Resting State Inter- and Intra-Network Functional Connectivity Is Associated with Perceived Stress in a Sample of University Students: An eLORETA Study

INTRODUCTION

Although the study of the Triple Network (TN) model has gained attention in the exploration of stress-related processes, the neurophysiological mechanisms of TN in relation to perceived stress have been relatively understudied in nonclinical samples so far. The main objective of the present study was to investigate, in a sample of university students, the association of perceived stress with resting state electroencephalography (EEG) functional connectivity in the TN.

METHODS

Ninety university students (40 males and 50 females; mean age 22.30 ± 2.43 years; mean educational level 16.60 ± 1.62 years) were enrolled. EEG data were analyzed through the exact low-resolution electromagnetic tomography (eLORETA).

RESULTS

Higher levels of perceived stress were associated with decreased delta EEG connectivity within the central executive network (CEN) and between the CEN and the salience network (SN). Higher levels of perceived stress were also associated with decreased theta EEG connectivity between the CEN and the SN. The associations between perceived stress and EEG connectivity data were significant even when relevant confounding factors (i.e., sex, age, educational level, and psychopathological symptoms) were controlled for.

DISCUSSION

Taken together, our results suggest that higher levels of perceived stress are associated with a dysfunctional synchronization within the CEN and between the SN and the CEN. This functional pattern might in part reflect the negative impact of high levels of perceived stress on cognitive functioning.

Aberrant Whole-Brain Resting-State Functional Connectivity Architecture in Obsessive-Compulsive Disorder: An EEG Study

Obsessive-compulsive disorder (OCD) is a common neuropsychiatric disorder characterized by intrusive thoughts (obsessions) and repetitive behaviors (compulsions), and few studies have assessed the whole-brain functional connectivity architecture of OCD with electroencephalogram (EEG) during different resting states. Graph theory and network-based statistics (NBS) were employed to examine the neural synchronization and the whole-brain functional connectivity (FC) based on the phase-locking value (PLV) of OCD patients and healthy controls (HCs) during eyes-closed (EC) and eyes-open (EO) states. Compared with HCs, OCD patients exhibited not only decreased global synchronization in terms of phase synchrony but also aberrant global topological properties (decreased average shortest path lengths and normalized shortest path lengths together with increased global efficiencies and normalized clustering coefficients) together with inhibited intra-hemispheric and interhemispheric FCs during rest, which suggested an imbalance between functional integration and segregation of brain networks for OCD patients. Meanwhile, OCD patients had increased global efficiencies and normalized clustering coefficients, but decreased average clustering coefficients and normalized shortest path lengths together with significantly decreased FCs in the alpha band from EC to EO states, which suggested a dynamic switch between highly integrated (EC state) and highly specialized (EO state) modes of information processing. Moreover, the decreased FCs of OCD patients showed obvious hemispheric asymmetry within or between groups during EC and EO states, which might serve as a potential biomarker to classify OCD patients from HCs.

Intrinsic Synchronization Analysis of Brain Activity in Obsessive-compulsive Disorders

Obsessive-compulsive disorder (OCD) is one of the neuropsychiatric disorders qualified by intrusive and iterative annoying thoughts and mental attitudes that are activated by these thoughts. In recent studies, advanced signal processing techniques have been favored to diagnose OCD. This research suggests four different measurements; intrinsic phase-locked value, intrinsic coherence, intrinsic synchronization likelihood, and intrinsic visibility graph similarity that quantifies the synchronization level and complexity in electroencephalography (EEG) signals. This intrinsic synchronization is achieved by utilizing Multivariate Empirical Mode Decomposition (MEMD), a data-driven method that resolves nonlinear and nonstationary data into their intrinsic mode functions. Our intrinsic technique in this study demonstrates that MEMD-based synchronization analysis gives us much more detailed knowledge rather than utilizing the synchronization method alone. Furthermore, the nonlinear synchronization method presents more consistent results considering OCD heterogeneity. Statistical evaluation using sample [Formula: see text]-test and [Formula: see text]-test has shown the significance of such new methodology.

Random Forest Classification of Alcohol Use Disorder Using EEG Source Functional Connectivity, Neuropsychological Functioning, and Impulsivity Measures

: Individuals with alcohol use disorder (AUD) manifest a variety of impairments that can be attributed to alterations in specific brain networks. The current study aims to identify features of EEG-based functional connectivity, neuropsychological performance, and impulsivity that can classify individuals with AUD (N = 30) from unaffected controls (CTL, N = 30) using random forest classification. The features included were: (i) EEG source functional connectivity (FC) of the default mode network (DMN) derived using eLORETA algorithm, (ii) neuropsychological scores from the Tower of London test (TOLT) and the visual span test (VST), and (iii) impulsivity factors from the Barratt impulsiveness scale (BIS). The random forest model achieved a classification accuracy of 80% and identified 29 FC connections (among 66 connections per frequency band), 3 neuropsychological variables from VST (total number of correctly performed trials in forward and backward sequences and average time for correct trials in forward sequence) and all four impulsivity scores (motor, non-planning, attentional, and total) as significantly contributing to classifying individuals as either AUD or CTL. Although there was a significant age difference between the groups, most of the top variables that contributed to the classification were not significantly correlated with age. The AUD group showed a predominant pattern of hyperconnectivity among 25 of 29 significant connections, indicating aberrant network functioning during resting state suggestive of neural hyperexcitability and impulsivity. Further, parahippocampal hyperconnectivity with other DMN regions was identified as a major hub region dysregulated in AUD (13 connections overall), possibly due to neural damage from chronic drinking, which may give rise to cognitive impairments, including memory deficits and blackouts. Furthermore, hypoconnectivity observed in four connections (prefrontal nodes connecting posterior right-hemispheric regions) may indicate a weaker or fractured prefrontal connectivity with other regions, which may be related to impaired higher cognitive functions. The AUD group also showed poorer memory performance on the VST task and increased impulsivity in all factors compared to controls. Features from all three domains had significant associations with one another. These results indicate that dysregulated neural connectivity across the DMN regions, especially relating to hyperconnected parahippocampal hub as well as hypoconnected prefrontal hub, may potentially represent neurophysiological biomarkers of AUD, while poor visual memory performance and heightened impulsivity may serve as cognitive-behavioral indices of AUD.

Resting functional connectivity and mild cognitive impairment in Parkinson’s disease. An electroencephalogram study

Objective: Parkinson’s disease (PD) is characterized by cognitive deficits. There is not clarity about electroencephalogram (EEG) connectivity related to the cognitive profile of patients. Our objective was to evaluate connectivity over resting EEG in nondemented PD. Methods: PD subjects with and without mild cognitive impairment (MCI) were assessed using coherence from resting EEG for local, intra and interhemispheric connectivity. Results: PD subjects without MCI (PD-nMCI) had lower intra and interhemispheric coherence in alpha2 compared with controls. PD with MCI (PD-MCI) showed higher intra and posterior interhemispheric coherence in alpha2 and beta1, respectively, in comparison to PD-nMCI. PD-MCI presented lower frontal coherence in beta frequencies compared with PD-nMCI. Conclusion: EEG coherence measures indicate distinct cortical activity in PD with and without MCI.

EEG Frequency Bands in Psychiatric Disorders: A Review of Resting State Studies

A significant proportion of the electroencephalography (EEG) literature focuses on differences in historically pre-defined frequency bands in the power spectrum that are typically referred to as alpha, beta, gamma, theta and delta waves. Here, we review 184 EEG studies that report differences in frequency bands in the resting state condition (eyes open and closed) across a spectrum of psychiatric disorders including depression, attention deficit-hyperactivity disorder (ADHD), autism, addiction, bipolar disorder, anxiety, panic disorder, post-traumatic stress disorder (PTSD), obsessive compulsive disorder (OCD) and schizophrenia to determine patterns across disorders. Aggregating across all reported results we demonstrate that characteristic patterns of power change within specific frequency bands are not necessarily unique to any one disorder but show substantial overlap across disorders as well as variability within disorders. In particular, we show that the most dominant pattern of change, across several disorder types including ADHD, schizophrenia and OCD, is power increases across lower frequencies (delta and theta) and decreases across higher frequencies (alpha, beta and gamma). However, a considerable number of disorders, such as PTSD, addiction and autism show no dominant trend for spectral change in any direction. We report consistency and validation scores across the disorders and conditions showing that the dominant result across all disorders is typically only 2.2 times as likely to occur in the literature as alternate results, and typically with less than 250 study participants when summed across all studies reporting this result. Furthermore, the magnitudes of the results were infrequently reported and were typically small at between 20% and 30% and correlated weakly with symptom severity scores. Finally, we discuss the many methodological challenges and limitations relating to such frequency band analysis across the literature. These results caution any interpretation of results from studies that consider only one disorder in isolation, and for the overall potential of this approach for delivering valuable insights in the field of mental health.

Normal Electrical Activity of the Brain in Obsessive-Compulsive Patients After Anodal Stimulation of the Left Dorsolateral Prefrontal Cortex

Introduction:

Transcranial Direct Current Stimulation (tDCS) has been used as a non-invasive method to increase the plasticity of brain. Growing evidence has shown several brain disorders such as depression, anxiety disorders, and chronic pain syndrome are improved following tDCS. In patients with Obsessive-Compulsive Disorder (OCD), increased brain rhythm activity particularly in the frontal lobe has been reported in several studies using Eectroencephalogram (EEG). To our knowledge, no research has been done on the effects of electrical stimulation on brain signals of patients with OCD. We measured the electrical activity of the brain using EEG in patients with OCD before and after tDCS and compared it to normal participants.

Methods:

Eight patients with OCD (3 males) and 8 matched healthy controls were recruited. A 64-channel EEG was used to record a 5-min resting state before and after application of tDCS in both groups. The intervention of tDCS was applied for 15 minutes with 2 mA amplitude where anode was placed on the left Dorsolateral Prefrontal Cortex (DLPFC) and cathode on the right DLPFC.

Results:

In line with previous studies, the results showed that the power of Delta frequency band in OCD patients are significantly higher than the normal group. Following anodal tDCS, hyperactivity in Delta and Theta bands declined in most channels, particularly in DLPFC (F3, F4) and became similar to normal signals pattern. The reduction in Delta band was significantly more than the other bands.

Conclusion:

Anodal tDCS over the left DLPFC significantly decreased the power of frequency bands of Delta and Theta in Patients with OCD. The pattern of EEG activity after tDCS became particularly similar to normal, so tDCS may have potential clinical application in these patients.

Evidence for a Resting State Network Abnormality in Adults Who Stutter

Neural network-based investigations of stuttering have begun to provide a possible integrative account for the large number of brain-based anomalies associated with stuttering. Here we used resting-state EEG to investigate functional brain networks in adults who stutter (AWS). Participants were 19 AWS and 52 age-, and gender-matched normally fluent speakers. EEGs were recorded and connectivity matrices were generated by LORETA in the theta (4-8 Hz), alpha (8-12 Hz), beta1 (12-20 Hz), and beta2 (20-30 Hz) bands. Small-world propensity (SWP), shortest path, and clustering coefficients were computed for weighted graphs. Minimum spanning tree analysis was also performed and measures were compared by non-parametric permutation test. The results show that small-world topology was evident in the functional networks of all participants. Three graph indices (diameter, clustering coefficient, and shortest path) exhibited significant differences between groups in the theta band and one [maximum betweenness centrality (BC)] measure was significantly different between groups in the beta2 band. AWS show higher BC than control in right temporal and inferior frontal areas and lower BC in the right primary motor cortex. Abnormal functional networks during rest state suggest an anomaly of DMN activity in AWS. Furthermore, functional segregation/integration deficits in the theta network are evident in AWS. These deficits reinforce the hypothesis that there is a neural basis for abnormal executive function in AWS. Increased beta2 BC in the right speech-motor related areas confirms previous evidence that right audio-speech areas are over-activated in AWS. Decreased beta2 BC in the right primary motor cortex is discussed in relation to abnormal neural mechanisms associated with time perception in AWS.

Altered resting-state functional connectivity in patients with obsessive-compulsive disorder: A magnetoencephalography study

Aberrant cortical-striatal-thalamic-cortical circuits have been implicated in the pathophysiology of obsessive-compulsive disorder (OCD). However, the neurobiological basis of OCD remains unclear. We compared patterns of functional connectivity in patients with OCD and in healthy controls using resting-state magnetoencephalography (MEG). Participants comprised 24 patients with OCD (21 men, 3 women) and 22 age- and sex-matched healthy controls (19 men, 3 women). Resting-state measurements were obtained over a 6-min period using a 152-channel whole-head MEG system. We examined group differences in oscillatory activity and distribution of functional cortical hubs based on the nodal centrality of phase-locking value (PLV) maps. Differences in resting-state functional connectivity were examined through PLV analysis in selected regions of interest based on these two findings. Patients with OCD demonstrated significantly lower delta band activity in the cortical regions of the limbic lobe, insula, orbitofrontal, and temporal regions, and theta band activity in the parietal lobe regions than healthy controls. Patients with OCD exhibited fewer functional hubs in the insula and orbitofrontal cortex and additional hubs in the cingulate and temporo-parietal regions. The OCD group exhibited significantly lower phase synchronization among the insula, orbitofrontal cortex, and cortical regions of the limbic lobe in all band frequencies, except in the delta band. Altered functional networks in the resting state may be associated with the pathophysiology of OCD. These MEG findings indicate that OCD is associated with decreased functional connectivity in terms of phase synchrony, particularly in the insula, orbitofrontal cortex, and cortical regions of the limbic lobe.

Abnormal small-world brain functional networks in obsessive-compulsive disorder patients with poor insight

BACKGROUND

There are limited data on neurobiological correlates of poor insight in obsessive-compulsive disorder (OCD). This study explored whether specific changes occur in small-world network (SWN) properties in the brain functional network of OCD patients with poor insight.

METHOD

Resting-state electroencephalograms (EEGs) were recorded for 12 medication-free OCD patients with poor insight, 50 medication-free OCD patients with good insight, and 36 healthy controls.

RESULTS

Both of the OCD groups exhibited topological alterations in the brain functional network characterized by abnormal small-world parameters at the beta band. However, the alterations at the theta band only existed in the OCD patients with poor insight.

LIMITATIONS

A relatively small sample size. Subjects were naïve to medications and those with Axis I comorbidity were excluded, perhaps limiting generalizability.

CONCLUSIONS

Disrupted functional integrity at the beta bands of the brain functional network may be related to OCD, while disrupted functional integrity at the theta band may be associated with poor insight in OCD patients, thus this study might provide novel insight into our understanding of the pathophysiology of OCD.

Electroencephalography Source Functional Connectivity Reveals Abnormal High-Frequency Communication Among Large-Scale Functional Networks in Depression

BACKGROUND

Functional magnetic resonance imaging studies of resting-state functional connectivity have shown that major depressive disorder (MDD) is characterized by increased connectivity within the default mode network (DMN) and between the DMN and the frontoparietal network (FPN). However, much remains unknown about abnormalities in higher frequency (>1 Hz) synchronization. Findings of abnormal synchronization in specific frequencies would contribute to a better understanding of the potential neurophysiological origins of disrupted functional connectivity in MDD.

METHODS

We used the high temporal resolution of electroencephalography to compare the spectral properties of resting-state functional connectivity in individuals with MDD (n = 65) with healthy control subjects (n = 79) and examined the extent to which connectivity disturbances were evident in a third sample of individuals in remission from depression (n = 30). Exact low resolution electromagnetic tomography was used to compute intracortical activity from regions within the DMN and FPN, and functional connectivity was computed using lagged phase synchronization.

RESULTS

Compared to control subjects, the MDD group showed greater within-DMN beta 2 band (18.5-21 Hz) connectivity and greater beta 1 band (12.5-18 Hz) connectivity between the DMN and FPN. This hyperconnectivity was not observed in the remitted MDD group. However, greater beta 1 band DMN-FPN connectivity was associated with more frequent depressive episodes since first depression onset, even after controlling for current symptom severity.

CONCLUSIONS

These findings extend our understanding of the neurophysiological basis of abnormal resting-state functional connectivity in MDD and indicate that elevations in high-frequency DMN-FPN connectivity may be a neural marker linked to a more recurrent illness course.