Tag: Zinn

A systematic review of quantitative EEG findings in Long COVID, Fibromyalgia and Chronic Fatigue Syndrome

Abstract:

Long COVID (LC) is a multisymptom clinical syndrome with similarities to Fibromyalgia Syndrome (FMS) and Chronic Fatigue Syndrome/Myalgic Encephalomyelitis (CFS/ME). All these conditions are believed to be associated with centrally driven mechanisms such as central sensitisation.

There is a lack of consensus on quantitative EEG (qEEG) changes observed in these conditions. This review aims to synthesise and appraise the literature on resting-state qEEG in LC, FMS and CFS/ME, to help uncover possible mechanisms of central sensitisation in these similar clinical syndromes.

A systematic search of MEDLINE, Embase, CINHAL, PsycINFO and Web of Science databases for articles published between December 1994 and September 2023 was performed. Following screening for predetermined selection criteria and out of the initial 2510 studies identified, 17 articles were retrieved that met all the inclusion criteria, particularly of assessing qEEG changes in one of the three conditions compared to healthy controls. All studies scored moderate to high quality on the Newcastle-Ottawa scale.

There was a general trend for decreased low frequency EEG band activity (delta, theta, and alpha) and increased high-frequency EEG beta activity in FMS, whereas an opposite trend was found in CFS/ME. The limited LC studies included in this review focused mainly on cognitive impairments and showed mixed findings not consistent with patterns seen in FMS and CFS/ME.

Further research is required to explore whether there are phenotypes within LC that have EEG signatures similar to FMS or CFS/ME. This could inform identification of reliable diagnostic markers and possible targets for neuromodulation therapies.

Source: Bárbara Silva-Passadouro, Arnas Tamasauskas, Omar Khoja, Alexander J. Casson, Ioannis Delis, Christopher Brown, Manoj Sivan. A systematic review of quantitative EEG findings in Long COVID, Fibromyalgia and Chronic Fatigue Syndrome. medRxiv [Preprint] https://www.medrxiv.org/content/10.1101/2023.11.06.23298171v1.full-text (Full text)

Cortical autonomic network connectivity predicts symptoms in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS)

Abstract:

Myalgic encephalomyelitis and chronic fatigue syndrome (ME/CFS) represents a significant public health challenge given the presence of many unexplained patient symptoms. Research has shown that many features in ME/CFS may result from a dysfunctional autonomic nervous system (ANS). We explored the role of the cortical autonomic network (CAN) involved in higher-order control of ANS functioning in 34 patients with ME/CFS and 34 healthy controls under task-free conditions.

All participants underwent resting-state quantitative electroencephalographic (qEEG) scalp recordings during an eyes-closed condition. Source analysis was performed using exact low-resolution electromagnetic tomography (eLORETA), and lagged coherence was used to estimate intrinsic functional connectivity between each node across 7 frequency bands: delta (1-3 Hz), theta (4-7 Hz), alpha-1 (8-10 Hz), alpha-2 (10-12 Hz), beta-1 (13-18 Hz), beta-2 (19-21 Hz), and beta-3 (22-30 Hz). Symptom ratings were measured using the DePaul Symptom Questionnaire and the Short Form (SF-36) health survey. Graph theoretical analysis of weighted, undirected connections revealed significant group differences in baseline CAN organization.

Regression results showed that cognitive, affective, and somatomotor symptom cluster ratings were associated with alteration to CAN topology in patients, depending on the frequency band. These findings provide evidence for reduced higher-order homeostatic regulation and adaptability in ME/CFS. If confirmed, these findings address the CAN as a potential therapeutic target for managing patient symptoms.

Source: Zinn MA, Jason LA. Cortical autonomic network connectivity predicts symptoms in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). Int J Psychophysiol. 2021 Oct 15:S0167-8760(21)00900-4. doi: 10.1016/j.ijpsycho.2021.10.004. Epub ahead of print. PMID: 34662673. https://pubmed.ncbi.nlm.nih.gov/34662673/

Cortical Hypoactivation During Resting EEG Suggests Central Nervous System Pathology in Patients with Chronic Fatigue Syndrome

Abstract:

We investigated cognitive impairment to executive function in 50 patients with chronic fatigue syndrome (CFS) and 50 matched healthy controls (HC). Resting state EEG was collected from 19 scalp locations during a 3 minute, eyes-closed condition. Current densities were localized using exact low-resolution electromagnetic tomography (eLORETA). The Multidimensional Fatigue Inventory (MFI-20) and the Fatigue Severity Scale (FSS) were administered to all participants. Independent t-tests and linear regression analyses were used to evaluate group differences in current densities, followed by statistical non-parametric mapping (SnPM) correction procedures.

Significant differences were found in the delta (1-3 Hz) and beta-2 (19-21 Hz) frequency bands. Delta sources were found predominately in the frontal lobe, while beta-2 sources were found in the medial and superior parietal lobe. Left-lateralized, frontal delta sources were associated with a clinical reduction in motivation. The implications of abnormal cortical sources in patients with CFS are discussed.

Source: Zinn MA, Zinn ML, Valencia I, Jason LA, Montoya JG. Cortical Hypoactivation During Resting EEG Suggests Central Nervous System Pathology in Patients with Chronic Fatigue Syndrome. Biol Psychol. 2018 May 23. pii: S0301-0511(18)30407-1. doi: 10.1016/j.biopsycho.2018.05.016. [Epub ahead of print] https://www.ncbi.nlm.nih.gov/pubmed/29802861

Small-World Network Analysis of Cortical Connectivity in Chronic Fatigue Syndrome Using Quantitative EEG

Abstract:

The aim of this study was to explore the relationship between complex brain networks in people with Chronic Fatigue Syndrome (CFS) and neurocognitive impairment. Quantitative EEG (qEEG) recordings were taken from 14 people with CFS and 15 healthy controls (HCs) during an eye-closed resting condition.

Exact low resolution electromagnetic tomography (eLORETA) was used to estimate cortical sources and perform a functional connectivity analysis. The graph theory approach was used to characterize network representations for each participant and derive the “small-worldness” index, a measure of the overall homeostatic balance between local and long-distance connectedness.

Results showed that small-worldness for the delta band was significantly lower for patients with CFS compared to HCs. In addition, delta small-worldness was negatively associated with neurocognitive impairment scores on the DePaul Symptom Questionnaire (DSQ). Finally, delta small-worldness indicated a greater risk of complex brain network inefficiency for the CFS group.

These results suggest that CFS pathology may be functionally disruptive to small-world networks. In turn, small-world characteristics might serve as a neurophysiological indicator for confirming a biological basis of cognitive symptoms, treatment outcome, and neurophysiological status of people with CFS.

Source: Citation: Zinn, M. A., Zinn, M. L., & Jason, L. A. (2017). Small-world network analysis of cortical connectivity in Chronic Fatigue Syndrome using quantitative EEG. NeuroRegulation, 4(3–4), 125–137. http://dx.doi.org/10.15540/nr.4.3-4.125 http://www.neuroregulation.org/article/view/17838/11670 (Full article)

Intrinsic Functional Hypoconnectivity in Core Neurocognitive Networks Suggests Central Nervous System Pathology in Patients with Myalgic Encephalomyelitis: A Pilot Study

Abstract:

Exact low resolution electromagnetic tomography (eLORETA) was recorded from nineteen EEG channels in nine patients with myalgic encephalomyelitis (ME) and 9 healthy controls to assess current source density and functional connectivity, a physiological measure of similarity between pairs of distributed regions of interest, between groups. Current source density and functional connectivity were measured using eLORETA software.

We found significantly decreased eLORETA source analysis oscillations in the occipital, parietal, posterior cingulate, and posterior temporal lobes in Alpha and Alpha-2. For connectivity analysis, we assessed functional connectivity within Menon triple network model of neuropathology.

We found support for all three networks of the triple network model, namely the central executive network (CEN), salience network (SN), and the default mode network (DMN) indicating hypo-connectivity in the Delta, Alpha, and Alpha-2 frequency bands in patients with ME compared to controls.

In addition to the current source density resting state dysfunction in the occipital, parietal, posterior temporal and posterior cingulate, the disrupted connectivity of the CEN, SN, and DMN appears to be involved in cognitive impairment for patients with ME. This research suggests that disruptions in these regions and networks could be a neurobiological feature of the disorder, representing underlying neural dysfunction.

 

Source: Zinn ML, Zinn MA, Jason LA. Intrinsic Functional Hypoconnectivity in Core Neurocognitive Networks Suggests Central Nervous System Pathology in Patients with Myalgic Encephalomyelitis: A Pilot Study. Appl Psychophysiol Biofeedback. 2016 Sep;41(3):283-300. doi: 10.1007/s10484-016-9331-3. https://www.ncbi.nlm.nih.gov/pubmed/26869373

 

Myalgic Encephalomyelitis: Symptoms and Biomarkers

Abstract:

Myalgic Encephalomyelitis (ME) continues to cause significant morbidity worldwide with an estimated one million cases in the United States. Hurdles to establishing consensus to achieve accurate evaluation of patients with ME continue, fueled by poor agreement about case definitions, slow progress in development of standardized diagnostic approaches, and issues surrounding research priorities. Because there are other medical problems, such as early MS and Parkinson’s Disease, which have some similar clinical presentations, it is critical to accurately diagnose ME to make a differential diagnosis.

In this article, we explore and summarize advances in the physiological and neurological approaches to understanding, diagnosing, and treating ME. We identify key areas and approaches to elucidate the core and secondary symptom clusters in ME so as to provide some practical suggestions in evaluation of ME for clinicians and researchers.

This review, therefore, represents a synthesis of key discussions in the literature, and has important implications for a better understanding of ME, its biological markers, and diagnostic criteria. There is a clear need for more longitudinal studies in this area with larger data sets, which correct for multiple testing.

 

Source: Jason LA, Zinn ML, Zinn MA. Myalgic Encephalomyelitis: Symptoms and Biomarkers. Curr Neuropharmacol. 2015;13(5):701-34. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4761639/ (Full article)