EEG synchronization characteristics of functional connectivity and complex network properties of memory maintenance in the delta and theta frequency bands

ObjectiveCognitive impairment occurs frequently in Parkinson’s disease (PD) and negatively impacts the patient’s quality of life. However, its pathophysiological mechanism remains unclear, hindering the development of new therapies. Changes in brain connectivity are related to cognitive impairment in patients with PD, with the dorsolateral prefrontal cortex (DLPFC) being considered the essential region related to PD cognitive impairment. Nevertheless, few studies have focused on the global connectivity responsible for communication with the DLPFC node, the posterior division of the middle frontal gyrus (PMFG) in patients with PD; this was the focus of this study.MethodsWe applied resting-state electroencephalography (EEG) and calculated a reliable functional connectivity measurement, the debiased weighted phase lag index (dWPLI), to examine inter-regional functional connectivity in 68 patients with PD who were classified into two groups according to their cognitive condition.ResultsWe observed that altered left and right PMFG-based functional connectivity associated with cognitive impairment in patients with PD in the theta frequency bands under the eyes closed condition (r = −0.426, p < 0.001 and r = −0.437, p < 0.001, respectively). Exploratory results based on the MoCA subdomains indicated that poorer visuospatial function was associated with higher right PMFG-based functional connectivity (r = −0.335, p = 0.005), and poorer attention function was associated with higher left and right PMFG-based functional connectivity (r = −0.380, p = 0.001 and r = −0.256, p = 0.035, respectively). Further analysis using logistic regression and receiver operating characteristic (ROC) curves found that this abnormal functional connectivity was an independent risk factor for cognitive impairment [odds ratio (OR): 2.949, 95% confidence interval (CI): 1.294–6.725, p = 0.01 for left PMFG; OR: 11.278, 95% CI: 2.578–49.335, p = 0.001 for right PMFG, per 0.1 U], and provided moderate classification power to discriminate between cognitive abilities in patients with PD [area under the ROC curve (AUC) = 0.770 for left PMFG; AUC = 0.809 for right PMFG].ConclusionThese preliminary findings indicate that abnormal PMFG-based functional connectivity patterns associated with cognitive impairment in the theta frequency bands under the eyes closed condition and altered functional connectivity patterns have the potential to act as reliable biomarkers for identifying cognitive impairment in patients with PD.

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Increased functional connectivity within alpha and theta frequency bands in dysphoria: A resting-state EEG study

Journal of Affective Disorders ◽

10.1016/j.jad.2020.12.015 ◽

2021 ◽

Vol 281 ◽

pp. 199-207

Author(s):

Carola Dell'Acqua ◽

Shadi Ghiasi ◽

Simone Messerotti Benvenuti ◽

Alberto Greco ◽

Claudio Gentili ◽

...

Keyword(s):

Functional Connectivity ◽

Resting State ◽

Frequency Bands ◽

Theta Frequency

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A Resting State fMRI Study on The Functional Connectivity, Neural Network Architecture and Neural Network Properties of PTSD

PsycEXTRA Dataset ◽

10.1037/e533652013-471 ◽

2012 ◽

Author(s):

Xiaodan Yan ◽

Charles Marmar

Keyword(s):

Neural Network ◽

Functional Connectivity ◽

Resting State ◽

Network Architecture ◽

Resting State Fmri ◽

Neural Network Architecture ◽

Fmri Study ◽

Network Properties

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Characterization and Coarsening of Autonomous System Networks

Advanced Methods for Complex Network Analysis - Advances in Wireless Technologies and Telecommunication ◽

10.4018/978-1-4666-9964-9.ch006 ◽

2016 ◽

pp. 148-179 ◽

Cited By ~ 5

Author(s):

Alberto Garcia-Robledo ◽

Arturo Diaz-Perez ◽

Guillermo Morales-Luna

Keyword(s):

Experimental Study ◽

Complex Network ◽

Autonomous System ◽

The Internet ◽

Linear Relationships ◽

Network Properties ◽

Network Metrics ◽

Graph Coarsening

This Chapter studies the correlations among well-known complex network metrics and presents techniques to coarse the topology of the Internet at the Autonomous System (AS) level. We present an experimental study on the linear relationships between a rich set of complex network metrics, to methodologically select a subset of non-redundant and potentially independent metrics that explain different aspects of the topology of the Internet. Then, the selected metrics are used to evaluate graph coarsening algorithms to reduce the topology of AS networks. The presented coarsening algorithms exploit the k-core decomposition of graphs to preserve relevant complex network properties.

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Resting-state brain network topological properties and the correlation with neuropsychological assessment in adolescent narcolepsy

SLEEP ◽

10.1093/sleep/zsaa018 ◽

2020 ◽

Vol 43 (8) ◽

Author(s):

Xiao Fulong ◽

Spruyt Karen ◽

Lu Chao ◽

Zhao Dianjiang ◽

Zhang Jun ◽

...

Keyword(s):

Functional Connectivity ◽

Neuropsychological Assessment ◽

Resting State ◽

Brain Connectivity ◽

Small World ◽

Theoretical Method ◽

Brain Network ◽

Topological Properties ◽

Depressive Feelings ◽

Network Properties

Abstract Study Objectives To evaluate functional connectivity and topological properties of brain networks, and to investigate the association between brain topological properties and neuropsychiatric behaviors in adolescent narcolepsy. Methods Resting-state functional magnetic resonance imaging (fMRI) and neuropsychological assessment were applied in 26 adolescent narcolepsy patients and 30 healthy controls. fMRI data were analyzed in three ways: group independent component analysis and a graph theoretical method were applied to evaluate topological properties within the whole brain. Lastly, network-based statistics was utilized for group comparisons in region-to-region connectivity. The relationship between topological properties and neuropsychiatric behaviors was analyzed with correlation analyses. Results In addition to sleepiness, depressive symptoms and impulsivity were detected in adolescent narcolepsy. In adolescent narcolepsy, functional connectivity was decreased between regions of the limbic system and the default mode network (DMN), and increased in the visual network. Adolescent narcolepsy patients exhibited disrupted small-world network properties. Regional alterations in the caudate nucleus (CAU) and posterior cingulate gyrus were associated with subjective sleepiness and regional alterations in the CAU and inferior occipital gyrus were associated with impulsiveness. Remodeling within the salience network and the DMN was associated with sleepiness, depressive feelings, and impulsive behaviors in narcolepsy. Conclusions Alterations in brain connectivity and regional topological properties in narcoleptic adolescents were associated with their sleepiness, depressive feelings, and impulsive behaviors.

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NOESIS: A Framework for Complex Network Data Analysis

Complexity ◽

10.1155/2019/1439415 ◽

2019 ◽

Vol 2019 ◽

pp. 1-14

Author(s):

Víctor Martínez ◽

Fernando Berzal ◽

Juan-Carlos Cubero

Keyword(s):

Data Mining ◽

Open Source ◽

Complex Network ◽

Open Source Software ◽

Network Data ◽

Analysis Techniques ◽

Software Analysis ◽

Open Source Framework ◽

Network Properties ◽

Real World Problems

Network data mining has attracted a lot of attention since a large number of real-world problems have to deal with complex network data. In this paper, we present NOESIS, an open-source framework for network-based data mining. NOESIS features a large number of techniques and methods for the analysis of structural network properties, network visualization, community detection, link scoring, and link prediction. The proposed framework has been designed following solid design principles and exploits parallel computing using structured parallel programming. NOESIS also provides a stand-alone graphical user interface allowing the use of advanced software analysis techniques to users without prior programming experience. This framework is available under a BSD open-source software license.

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Reduced Brain Electric Activity and Functional Connectivity in Bipolar Euthymia: An sLORETA Source Localization Study

Clinical EEG and Neuroscience ◽

10.1177/1550059419893472 ◽

2019 ◽

Vol 51 (3) ◽

pp. 155-166

Author(s):

Annamaria Painold ◽

Pascal L. Faber ◽

Eva Z. Reininghaus ◽

Sabrina Mörkl ◽

Anna K. Holl ◽

...

Keyword(s):

Functional Connectivity ◽

Large Scale ◽

Time Course ◽

Temporal Cortex ◽

Electric Activity ◽

Brain Regions ◽

Frequency Bands ◽

Head Surface ◽

Density Values ◽

Surface Eeg

Bipolar disorder (BD) is a chronic illness with a relapsing and remitting time course. Relapses are manic or depressive in nature and intermitted by euthymic states. During euthymic states, patients lack the criteria for a manic or depressive diagnosis, but still suffer from impaired cognitive functioning as indicated by difficulties in executive and language-related processing. The present study investigated whether these deficits are reflected by altered intracortical activity in or functional connectivity between brain regions involved in these processes such as the prefrontal and the temporal cortices. Vigilance-controlled resting state EEG of 13 euthymic BD patients and 13 healthy age- and sex-matched controls was analyzed. Head-surface EEG was recomputed into intracortical current density values in 8 frequency bands using standardized low-resolution electromagnetic tomography. Intracortical current densities were averaged in 19 evenly distributed regions of interest (ROIs). Lagged coherences were computed between each pair of ROIs. Source activity and coherence measures between patients and controls were compared (paired t tests). Reductions in temporal cortex activity and in large-scale functional connectivity in patients compared to controls were observed. Activity reductions affected all 8 EEG frequency bands. Functional connectivity reductions affected the delta, theta, alpha-2, beta-2, and gamma band and involved but were not limited to prefrontal and temporal ROIs. The findings show reduced activation of the temporal cortex and reduced coordination between many brain regions in BD euthymia. These activation and connectivity changes may disturb the continuous frontotemporal information flow required for executive and language-related processing, which is impaired in euthymic BD patients.

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Opioid withdrawal results in an increased local and remote functional connectivity at EEG alpha and beta frequency bands

Neuroscience Research ◽

10.1016/j.neures.2007.01.011 ◽

2007 ◽

Vol 58 (1) ◽

pp. 40-49 ◽

Cited By ~ 22

Author(s):

Andrew A. Fingelkurts ◽

Alexander A. Fingelkurts ◽

Reetta Kivisaari ◽

Taina Autti ◽

Sergei Borisov ◽

...

Keyword(s):

Functional Connectivity ◽

Opioid Withdrawal ◽

Frequency Bands ◽

Eeg Alpha ◽

Beta Frequency

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Altered Coactive Micropattern Connectivity in the Default-Mode Network during the Sleep-Wake Cycle

Neural Plasticity ◽

10.1155/2020/8876131 ◽

2020 ◽

Vol 2020 ◽

pp. 1-13

Author(s):

Yan Cui ◽

Qiao Chen ◽

Yang Xia ◽

Zeru Wang ◽

Yujia Guo ◽

...

Keyword(s):

Information Processing ◽

Functional Connectivity ◽

Default Mode Network ◽

Current Knowledge ◽

Current Work ◽

Default Mode ◽

States Of Consciousness ◽

Waking State ◽

Network Properties ◽

Efficient Information

The default-mode network (DMN) is believed to be associated with levels of consciousness, but how the functional connectivity (FC) of the DMN changes across different states of consciousness is still unclear. In the current work, we addressed this issue by exploring the coactive micropattern (CAMP) networks of the DMN according to the CAMPs of rat DMN activity during the sleep-wake cycle and tracking their topological alterations among different states of consciousness. Three CAMP networks were observed in DMN activity, and they displayed greater FC and higher efficiency than the original DMN structure in all states of consciousness, implying more efficient information processing in the CAMP networks. Furthermore, no significant differences in FC or network properties were found among the three CAMP networks in the waking state. However, the three networks were distinct in their characteristics in two sleep states, indicating that different CAMP networks played specific roles in distinct sleep states. In addition, we found that the changes in the FC and network properties of the CAMP networks were similar to those in the original DMN structure, suggesting intrinsic effects of various states of consciousness on DMN dynamics. Our findings revealed three underlying CAMP networks within the DMN dynamics and deepened the current knowledge concerning FC alterations in the DMN during conscious changes in the sleep-wake cycle.

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