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De Blasio FM, Love S, Barry RJ, Wassink K, Cave AE, Armour M, Steiner-Lim GZ. Frontocentral delta-beta amplitude coupling in endometriosis-related chronic pelvic pain. Clin Neurophysiol 2023; 149:146-156. [PMID: 36965467 DOI: 10.1016/j.clinph.2023.02.173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 02/08/2023] [Accepted: 02/13/2023] [Indexed: 03/08/2023]
Abstract
OBJECTIVE Endometriosis is associated with neuroplastic changes in cognitive control and pain processing networks. This was the first study to assess eyes-closed resting electroencephalogram (EEG) oscillatory amplitudes in women with endometriosis compared to healthy controls, and explore the relationship with chronic pelvic pain. METHODS Women with endometriosis-related chronic pelvic pain and individually age-matched pain-free controls (N = 20 per group) documented pelvic pain for 28 days before having continuous EEG recorded during a 2 min eyes closed resting state. Natural frequency components were extracted for each group using frequency principal components analysis. Corresponding components were assessed for group differences and correlated with pain scores. RESULTS Relative to controls, the endometriosis group had greater component amplitudes in delta (0.5 Hz) and beta (∼28 Hz), and reduced alpha (∼10 Hz). Delta and beta amplitudes were positively associated with pain severity, but only beta maintained this association after delta-beta amplitude coupling was controlled. CONCLUSIONS Enhanced resting delta and beta amplitudes were seen in women with endometriosis experiencing chronic pelvic pain. This delta-beta coupling varied with pelvic pain severity, perhaps reflecting altered cholinergic tone and/or stress reactivity. SIGNIFICANCE Endometriosis-related changes in central pain processing demonstrate a distinct neuronal oscillatory signature detectable at rest.
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Affiliation(s)
- Frances M De Blasio
- NICM Health Research Institute and Translational Health Research Institute (THRI), Western Sydney University, Penrith, NSW 2751, Australia; Brain & Behaviour Research Institute and School of Psychology, University of Wollongong, Wollongong, NSW 2522, Australia
| | - Sapphire Love
- Brain & Behaviour Research Institute and School of Psychology, University of Wollongong, Wollongong, NSW 2522, Australia
| | - Robert J Barry
- Brain & Behaviour Research Institute and School of Psychology, University of Wollongong, Wollongong, NSW 2522, Australia
| | - Katherine Wassink
- Brain & Behaviour Research Institute and School of Psychology, University of Wollongong, Wollongong, NSW 2522, Australia
| | - Adele E Cave
- NICM Health Research Institute and Translational Health Research Institute (THRI), Western Sydney University, Penrith, NSW 2751, Australia
| | - Mike Armour
- NICM Health Research Institute and Translational Health Research Institute (THRI), Western Sydney University, Penrith, NSW 2751, Australia
| | - Genevieve Z Steiner-Lim
- NICM Health Research Institute and Translational Health Research Institute (THRI), Western Sydney University, Penrith, NSW 2751, Australia.
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Vidaurre C, Nikulin VV, Herrojo Ruiz M. Identification of spatial patterns with maximum association between power of resting state neural oscillations and trait anxiety. Neural Comput Appl 2023; 35:5737-5749. [PMID: 36212215 PMCID: PMC9525925 DOI: 10.1007/s00521-022-07847-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Accepted: 09/14/2022] [Indexed: 12/01/2022]
Abstract
Anxiety affects approximately 5-10% of the adult population worldwide, placing a large burden on the health systems. Despite its omnipresence and impact on mental and physical health, most of the individuals affected by anxiety do not receive appropriate treatment. Current research in the field of psychiatry emphasizes the need to identify and validate biological markers relevant to this condition. Neurophysiological preclinical studies are a prominent approach to determine brain rhythms that can be reliable markers of key features of anxiety. However, while neuroimaging research consistently implicated prefrontal cortex and subcortical structures, such as amygdala and hippocampus, in anxiety, there is still a lack of consensus on the underlying neurophysiological processes contributing to this condition. Methods allowing non-invasive recording and assessment of cortical processing may provide an opportunity to help identify anxiety signatures that could be used as intervention targets. In this study, we apply Source-Power Comodulation (SPoC) to electroencephalography (EEG) recordings in a sample of participants with different levels of trait anxiety. SPoC was developed to find spatial filters and patterns whose power comodulates with an external variable in individual participants. The obtained patterns can be interpreted neurophysiologically. Here, we extend the use of SPoC to a multi-subject setting and test its validity using simulated data with a realistic head model. Next, we apply our SPoC framework to resting state EEG of 43 human participants for whom trait anxiety scores were available. SPoC inter-subject analysis of narrow frequency band data reveals neurophysiologically meaningful spatial patterns in the theta band (4-7 Hz) that are negatively correlated with anxiety. The outcome is specific to the theta band and not observed in the alpha (8-12 Hz) or beta (13-30 Hz) frequency range. The theta-band spatial pattern is primarily localised to the superior frontal gyrus. We discuss the relevance of our spatial pattern results for the search of biomarkers for anxiety and their application in neurofeedback studies.
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Affiliation(s)
- Carmen Vidaurre
- Neuroengineering Group, TECNALIA, Basque Research and Technology Alliance (BRTA), Donostia-San Sebastian, Spain ,IKERBASQUE, Basque Foundation for Science, Bilbao, Spain ,Department of Statistics, Computer Science and Mathematics, Public University of Navarre, Pamplona, Spain
| | - Vadim V. Nikulin
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany ,Institute for Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russian Federation
| | - Maria Herrojo Ruiz
- Institute for Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russian Federation ,Psychology Department, Goldsmiths University of London, London, UK
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Anaya B, Vallorani AM, Pérez‐Edgar K. Individual dynamics of delta-beta coupling: using a multilevel framework to examine inter- and intraindividual differences in relation to social anxiety and behavioral inhibition. J Child Psychol Psychiatry 2021; 62:771-779. [PMID: 32936944 PMCID: PMC7960561 DOI: 10.1111/jcpp.13319] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Revised: 07/22/2020] [Accepted: 07/31/2020] [Indexed: 01/16/2023]
Abstract
BACKGROUND Variation in EEG-derived delta-beta coupling has recently emerged as a potential neural marker of emotion regulation, providing a novel and noninvasive method for assessing a risk factor for anxiety. However, our understanding of delta-beta coupling has been limited to group-level comparisons, which provide limited information about an individual's neural dynamics. METHODS The present study used multilevel modeling to map second-by-second coupling patterns between delta and beta power. Specifically, we examined how inter- and intraindividual delta-beta coupling patterns changed as a function of social anxiety symptoms and temperamental behavioral inhibition (BI). RESULTS We found that stronger inter- and intraindividual delta-beta coupling were both associated with social anxiety. In contrast, the high-BI group showed weaker coupling relative to the non-BI group, a pattern that did not emerge when analyzing continuous scores of BI. CONCLUSIONS In characterizing inter- and intraindividual coupling across the sample, we illustrate the utility of examining neural processes across levels of analysis in relation to psychopathology to create multilevel assessments of functioning and risk.
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Affiliation(s)
- Berenice Anaya
- Department of Psychology The Pennsylvania State University University Park PA USA
| | - Alicia M. Vallorani
- Department of Psychology The Pennsylvania State University University Park PA USA
| | - Koraly Pérez‐Edgar
- Department of Psychology The Pennsylvania State University University Park PA USA
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Multilayer MEG functional connectivity as a potential marker for suicidal thoughts in major depressive disorder. NEUROIMAGE-CLINICAL 2020; 28:102378. [PMID: 32836087 PMCID: PMC7451429 DOI: 10.1016/j.nicl.2020.102378] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/02/2019] [Revised: 06/18/2020] [Accepted: 08/06/2020] [Indexed: 11/23/2022]
Abstract
Major depressive disorder (MDD) is highly heterogeneous in its clinical presentation. The present exploratory study used magnetoencephalography (MEG) to investigate electrophysiological intrinsic connectivity differences between healthy volunteers and unmedicated participants with treatment-resistant MDD. The study examined canonical frequency bands from delta through gamma. In addition to group comparisons, correlational studies were conducted to determine whether connectivity was related to five symptom factors: depressed mood, tension, negative cognition, suicidal thoughts, and amotivation. The MDD and healthy volunteer groups did not differ significantly at baseline when corrected across all frequencies and clusters, although evidence of generalized slowing in MDD was observed. Notably, however, electrophysiological connectivity was strongly related to suicidal thoughts, particularly as coupling of low frequency power fluctuations (delta and theta) with alpha and beta power. This analysis revealed hub areas underlying this symptom cluster, including left hippocampus, left anterior insula, and bilateral dorsolateral prefrontal cortex. No other symptom cluster demonstrated a relationship with neurophysiological connectivity, suggesting a specificity to these results as markers of suicidal ideation.
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Al-Ezzi A, Kamel N, Faye I, Gunaseli E. Review of EEG, ERP, and Brain Connectivity Estimators as Predictive Biomarkers of Social Anxiety Disorder. Front Psychol 2020; 11:730. [PMID: 32508695 PMCID: PMC7248208 DOI: 10.3389/fpsyg.2020.00730] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2019] [Accepted: 03/25/2020] [Indexed: 12/13/2022] Open
Abstract
Social anxiety disorder (SAD) is characterized by a fear of negative evaluation, negative self-belief and extreme avoidance of social situations. These recurrent symptoms are thought to maintain the severity and substantial impairment in social and cognitive thoughts. SAD is associated with a disruption in neuronal networks implicated in emotional regulation, perceptual stimulus functions, and emotion processing, suggesting a network system to delineate the electrocortical endophenotypes of SAD. This paper seeks to provide a comprehensive review of the most frequently studied electroencephalographic (EEG) spectral coupling, event-related potential (ERP), visual-event potential (VEP), and other connectivity estimators in social anxiety during rest, anticipation, stimulus processing, and recovery states. A search on Web of Science provided 97 studies that document electrocortical biomarkers and relevant constructs pertaining to individuals with SAD. This study aims to identify SAD neuronal biomarkers and provide insight into the differences in these biomarkers based on EEG, ERPs, VEP, and brain connectivity networks in SAD patients and healthy controls (HC). Furthermore, we proposed recommendations to improve methods of delineating the electrocortical endophenotypes of SAD, e.g., a fusion of EEG with other modalities such as functional magnetic resonance imaging (fMRI) and magnetoencephalograms (MEG), to realize better effectiveness than EEG alone, in order to ultimately evolve the treatment selection process, and to review the possibility of using electrocortical measures in the early diagnosis and endophenotype examination of SAD.
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Affiliation(s)
- Abdulhakim Al-Ezzi
- Centre for Intelligent Signal and Imaging Research, Department of Electrical and Electronic Engineering, Universiti Teknologi PETRONAS, Seri Iskandar, Malaysia
| | - Nidal Kamel
- Centre for Intelligent Signal and Imaging Research, Department of Electrical and Electronic Engineering, Universiti Teknologi PETRONAS, Seri Iskandar, Malaysia
| | - Ibrahima Faye
- Centre for Intelligent Signal and Imaging Research, Department of Electrical and Electronic Engineering, Universiti Teknologi PETRONAS, Seri Iskandar, Malaysia
| | - Esther Gunaseli
- Psychiatry Discipline Sub Unit, Universiti Kuala Lumpur, Ipoh, Malaysia
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Nugent AC, Ballard ED, Gilbert JR, Tewarie PK, Brookes MJ, Zarate CA. The Effect of Ketamine on Electrophysiological Connectivity in Major Depressive Disorder. Front Psychiatry 2020; 11:519. [PMID: 32655423 PMCID: PMC7325927 DOI: 10.3389/fpsyt.2020.00519] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Accepted: 05/21/2020] [Indexed: 01/06/2023] Open
Abstract
Major depressive disorder (MDD) is highly prevalent and frequently disabling. Only about 30% of patients respond to a first-line antidepressant treatment, and around 30% of patients are classified as "treatment-resistant" after failing to respond to multiple adequate trials. While most antidepressants target monoaminergic targets, ketamine is an N-methyl-D-aspartate (NMDA) antagonist that has shown rapid antidepressant effects when delivered intravenously or intranasally. While there is evidence that ketamine exerts its effects via enhanced α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) throughput, its mechanism for relieving depressive symptoms is largely unknown. This study acquired resting-state magnetoencephalography (MEG) recordings after both ketamine and placebo infusions and investigated functional connectivity using a multilayer amplitude-amplitude correlation technique spanning the canonical frequency bands. Twenty-four healthy volunteers (HVs) and 27 unmedicated participants with MDD took part in a double-blind, placebo-controlled, crossover trial of 0.5 mg/kg IV ketamine. Order of infusion was randomized, and participants crossed over to receive the second infusion after two weeks. The results indicated widespread ketamine-induced reductions in connectivity in the alpha and beta bands that did not correlate with magnitude of antidepressant response. In contrast, the magnitude of ketamine's antidepressant effects in MDD participants was associated with cross-frequency connectivity for delta-alpha and delta-gamma bands, with HVs and ketamine non-responders showing connectivity decreases post-ketamine and ketamine responders demonstrating small increases in connectivity. These results may indicate functional subtypes of MDD and also suggest that neural responses to ketamine are fundamentally different between responders and non-responders.
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Affiliation(s)
- Allison C Nugent
- MEG Core Facility, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States.,Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States
| | - Elizabeth D Ballard
- Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States
| | - Jessica R Gilbert
- Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States
| | - Prejaas K Tewarie
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, United Kingdom
| | - Matthew J Brookes
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, United Kingdom
| | - Carlos A Zarate
- Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States
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