Disruption of Cortical Connectivity during Remifentanil Administration Is Associated with Cognitive Impairment but Not with Analgesia

2015 ◽  
Vol 122 (1) ◽  
pp. 140-149 ◽  
Author(s):  
Ahmad Khodayari-Rostamabad ◽  
Søren S. Olesen ◽  
Carina Graversen ◽  
Lasse P. Malver ◽  
Geana P. Kurita ◽  
...  
Keyword(s):  
Reaction Time ◽  
Functional Connectivity ◽  
Path Length ◽  
Experimental Pain ◽  
Clustering Coefficient ◽  
Cognitive Test ◽  
Characteristic Path Length ◽  
Network Properties ◽  
Continuous Reaction ◽  
Continuous Reaction Time

Abstract Background: The authors investigated the effect of remifentanil administration on resting electroencephalography functional connectivity and its relationship to cognitive function and analgesia in healthy volunteers. Methods: Twenty-one healthy male adult subjects were enrolled in this placebo-controlled double-blind cross-over study. For each subject, 2.5 min of multichannel electroencephalography recording, a cognitive test of sustained attention (continuous reaction time), and experimental pain scores to bone-pressure and heat stimuli were collected before and after infusion of remifentanil or placebo. A coherence matrix was calculated from the electroencephalogram, and three graph-theoretical measures (characteristic path-length, mean clustering coefficient, and relative small-worldness) were extracted to characterize the overall cortical network properties. Results: Compared to placebo, most graph-theoretical measures were significantly altered by remifentanil at the alpha and low beta range (8 to 18 Hz; all P < 0.001). Taken together, these alterations were characterized by an increase in the characteristic path-length (alpha 17% and low beta range 24%) and corresponding decrements in mean clustering coefficient (low beta range −25%) and relative small-worldness (alpha −17% and low beta range −42%). Changes in characteristic path-lengths after remifentanil infusion were correlated to the continuous reaction time index (r = −0.57; P = 0.009), while no significant correlations between graph-theoretical measures and experimental pain tests were seen. Conclusions: Remifentanil disrupts the functional connectivity network properties of the electroencephalogram. The findings give new insight into how opioids interfere with the normal brain functions and have the potential to be biomarkers for the sedative effects of opioids in different clinical settings.

scholarly journals Functional Connectivity of EEG in Encephalitis during Slow Biphasic Complexes

Electronics ◽  
2021 ◽  
Vol 10 (23) ◽  
pp. 2978
Author(s):  
Giovanni Chiarion ◽  
Luca Mesin
Keyword(s):  
Functional Connectivity ◽  
Path Length ◽  
Inflammatory Diseases ◽  
Clustering Coefficient ◽  
Eeg Rhythms ◽  
Characteristic Path Length ◽  
Slowing Down ◽  
Eeg Functional Connectivity ◽  
Network Patterns ◽  
The Brain

The electroencephalogram (EEG) of patients suffering from inflammatory diseases of the brain may show specific waveforms called slow biphasic complexes (SBC). Recent studies indicated a correlation between the severity of encephalitis and some features of SBCs, such as location, amplitude and frequency of appearance. Moreover, EEG rhythms were found to vary before the onset of an SBC, as if the brain was preparing to the discharge (actually with a slowing down of the EEG oscillation). Here, we investigate possible variations of EEG functional connectivity (FC) in EEGs from pediatric patients with different levels of severity of encephalitis. FC was measured by the maximal crosscorrelation of EEG rhythms in different bipolar channels. Then, the indexes of network patterns (namely strength, clustering coefficient, efficiency and characteristic path length) were estimated to characterize the global behavior when they are measured during SBCs or far from them. EEG traces showed statistical differences in the two conditions: clustering coefficient, efficiency and strength are higher close to an SBC, whereas the characteristic path length is lower. Moreover, for more severe conditions, an increase in clustering coefficient, efficiency and strength and a decrease in characteristic path length were observed in the delta–theta band. These outcomes support the hypothesis that SBCs result from the anomalous coordination of neurons in different brain areas affected by the inflammation process and indicate FC as an additional key for interpreting the EEG in encephalitis patients.

Abstract 17426: Pulmonary Vein Isolation ‘Rewires’ Electrical Communications to Enhance Small-world Network Topology During Atrial Fibrillation

Circulation ◽  
2015 ◽  
Vol 132 (suppl_3) ◽  
Author(s):  
Hiroshi Ashikaga ◽  
Jonathan Chrispin ◽  
Degang Wu ◽  
Joshua Garland
Keyword(s):  
Atrial Fibrillation ◽  
Communication Network ◽  
Mutual Information ◽  
Path Length ◽  
Random Network ◽  
Small World ◽  
Clustering Coefficient ◽  
Small World Network ◽  
Z Score ◽  
Network Properties

Recent evidence suggests that pulmonary vein isolation (PVI) may perturb the electrophysiological substrate for maintenance of atrial fibrillation (AF). Our previous work indicates that information theory metrics can quantify electrical communications during arrhythmia. We hypothesized that PVI ‘rewires’ the electrical communication network during AF such that the topology exhibits higher levels of small-world network properties, with higher clustering coefficient and lower path length, than would be expected by chance. Thirteen consecutive patients (n=6 with prior PVI and n=7 without) underwent AF ablation using a 64-electrode basket catheter in the left atrium. Multielectrode recording was performed during AF for 60 seconds, followed by PVI. Mutual information was calculated from the time series between each pair of electrodes using the Kraskov-Stögbauer-Grassberger estimator. The all-to-all mutual information matrix (64x64; Figure, upper panels) was thresholded by the median and standard deviations of mutual information to build a binary adjacency matrix for electrical communication networks. The properties of small-world network ( swn ; ‘small-world-ness’) were quantified by the ratio of the observed average clustering coefficient to that of a random network over the ratio of the observed average path length to that of a random network. swn was expressed in normal Z standard deviation units. As the binarizing threshold increased, the Z-score of swn decreased (Figure, lower panel). However, the Z-score at each threshold value was consistently higher with prior PVI than those without (p<0.05). In conclusion, electrical communication network during AF with prior PVI is associated with higher levels of small-world network properties than those without. This finding supports the concept that PVI perturbs the underlying substrate. In addition, swn of electrical communication network may be a promising metric to quantify substrate modification.

scholarly journals Altered Functional Connectivity after Epileptic Seizure Revealed by Scalp EEG

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Yi Liang ◽  
Chunli Chen ◽  
Fali Li ◽  
Dezhong Yao ◽  
Peng Xu ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Brain Activity ◽  
Epileptic Seizures ◽  
Local Area ◽  
Brain Network ◽  
Fuzzy Entropy ◽  
Clustering Coefficient ◽  
Characteristic Path Length ◽  
Functional Brain Network ◽  
Before And After

Epileptic seizures are considered to be a brain network dysfunction, and chronic recurrent seizures can cause severe brain damage. However, the functional brain network underlying recurrent epileptic seizures is still left unveiled. This study is aimed at exploring the differences in a related brain activity before and after chronic repetitive seizures by investigating the power spectral density (PSD), fuzzy entropy, and functional connectivity in epileptic patients. The PSD analysis revealed differences between the two states at local area, showing postseizure energy accumulation. Besides, the fuzzy entropies of preseizure in the frontal, central, and temporal regions are higher than that of postseizure. Additionally, attenuated long-range connectivity and enhanced local connectivity were also found. Moreover, significant correlations were found between network metrics (i.e., characteristic path length and clustering coefficient) and individual seizure number. The PSD, fuzzy entropy, and network analysis may indicate that the brain is gradually impaired along with the occurrence of epilepsy, and the accumulated effect of brain impairment is observed in individuals with consecutive epileptic bursts. The findings of this study may provide helpful insights into understanding the network mechanism underlying chronic recurrent epilepsy.

OPTIMAL INTERCONNECTION OF AD HOC INJECTION NETWORKS

2008 ◽  
Vol 09 (03) ◽  
pp. 277-297 ◽  
Author(s):  
GREGOIRE DANOY ◽  
ENRIQUE ALBA ◽  
PASCAL BOUVRY
Keyword(s):  
Ad Hoc Networks ◽  
Ad Hoc ◽  
Small World ◽  
Access Point ◽  
Clustering Coefficient ◽  
Mobility Patterns ◽  
Characteristic Path Length ◽  
Network Properties ◽  
Hoc Networks ◽  
Topology Control Problem

Multi-hop ad hoc networks allow establishing local groups of communicating devices in a self-organizing way. However, when considering realistic mobility patterns, such networks most often get divided in a set of disjoint partitions. This presence of partitions is an obstacle to communication within these networks. Ad hoc networks are generally composed of devices capable of communicating in a geographical neighborhood for free (e.g. using Wi-Fi or Bluetooth). In most cases a communication infrastructure is available. It can be a set of access point as well as a GSM/UMTS network. The use of such an infrastructure is billed, but it permits to interconnect distant nodes, through what we call “bypass links”. The objective of our work is to optimize the placement of these long-range links. To this end we rely on small-world network properties, which consist in a high clustering coefficient and a low characteristic path length. In this article we investigate the use of three genetic algorithms (generational, steady-state, and cooperative coevolutionary) to optimize three instances of this topology control problem and present initial evidence of their capacity to solve it.

Continuous Reaction Time in Patients with Hepatic Encephalopathy

1981 ◽  
Vol 16 (3) ◽  
pp. 441-447 ◽  
Author(s):  
P. Elsass ◽  
S.-E. Christensen ◽  
L. Ranek ◽  
A. Theilgaard ◽  
N. Tygstrup
Keyword(s):  
Hepatic Encephalopathy ◽  
Reaction Time ◽  
Continuous Reaction ◽  
Continuous Reaction Time

scholarly journals A Comparative Study of Structural and Metabolic Brain Networks in Patients With Mild Cognitive Impairment

2021 ◽  
Vol 13 ◽  
Author(s):  
Cuibai Wei ◽  
Shuting Gong ◽  
Qi Zou ◽  
Wei Zhang ◽  
Xuechun Kang ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Path Length ◽  
Brain Networks ◽  
Brain Regions ◽  
Clustering Coefficient ◽  
Characteristic Path Length ◽  
Glucose Intake ◽  
Item Scores ◽  
Structural Brain

Background: Changes in the metabolic and structural brain networks in mild cognitive impairment (MCI) have been widely researched. However, few studies have compared the differences in the topological properties of the metabolic and structural brain networks in patients with MCI.Methods: We analyzedmagnetic resonance imaging (MRI) and fluoro-deoxyglucose positron emission tomography (FDG-PET) data of 137 patients with MCI and 80 healthy controls (HCs). The HC group data comes from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. The permutation test was used to compare the network parameters (characteristic path length, clustering coefficient, local efficiency, and global efficiency) between the two groups. Partial Pearson’s correlation analysis was used to calculate the correlations of the changes in gray matter volume and glucose intake in the key brain regions in MCI with the Alzheimer’s Disease Assessment Scale-Cognitive (ADAS-cog) sub-item scores.Results: Significant changes in the brain network parameters (longer characteristic path length, larger clustering coefficient, and lower local efficiency and global efficiency) were greater in the structural network than in the metabolic network (longer characteristic path length) in MCI patients than in HCs. We obtained the key brain regions (left globus pallidus, right calcarine fissure and its surrounding cortex, left lingual gyrus) by scanning the hubs. The volume of gray matter atrophy in the left globus pallidus was significantly positively correlated with comprehension of spoken language (p = 0.024) and word-finding difficulty in spontaneous speech item scores (p = 0.007) in the ADAS-cog. Glucose intake in the three key brain regions was significantly negatively correlated with remembering test instructions items in ADAS-cog (p = 0.020, p = 0.014, and p = 0.008, respectively).Conclusion: Structural brain networks showed more changes than metabolic brain networks in patients with MCI. Some brain regions with significant changes in betweenness centrality in both structural and metabolic networks were associated with MCI.

scholarly journals Disrupted functional connectivity in PD with probable RBD and its cognitive correlates

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Javier Oltra ◽  
Anna Campabadal ◽  
Barbara Segura ◽  
Carme Uribe ◽  
Maria Jose Marti ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Verbal Memory ◽  
Path Length ◽  
Behavior Disorder ◽  
Brain Network ◽  
Characteristic Path Length ◽  
Whole Brain ◽  
Sleep Behavior ◽  
Cognitive Correlates ◽  
Theoretical Approaches

AbstractRecent studies associated rapid eye movement sleep behavior disorder (RBD) in Parkinson’s disease (PD) with severe cognitive impairment and brain atrophy. However, whole-brain functional connectivity has never been explored in this group of PD patients. In this study, whole-brain network-based statistics and graph-theoretical approaches were used to characterize resting-state interregional functional connectivity in PD with probable RBD (PD-pRBD) and its relationship with cognition. Our sample consisted of 30 healthy controls, 32 PD without probable RBD (PD-non pRBD), and 27 PD-pRBD. The PD-pRBD group showed reduced functional connectivity compared with controls mainly involving cingulate areas with temporal, frontal, insular, and thalamic regions (p < 0.001). Also, the PD-pRBD group showed reduced functional connectivity between right ventral posterior cingulate and left medial precuneus compared with PD-non pRBD (p < 0.05). We found increased normalized characteristic path length in PD-pRBD compared with PD-non pRBD. In the PD-pRBD group, mean connectivity strength from reduced connections correlated with visuoperceptual task and normalized characteristic path length correlated with processing speed and verbal memory tasks. This work demonstrates the existence of disrupted functional connectivity in PD-pRBD, together with abnormal network integrity, that supports its consideration as a severe PD subtype.

Patient reported outcomes and neuropsychological testing in patients with chronic non-cancer pain in long-term opioid therapy: a pilot study

2019 ◽  
Vol 19 (3) ◽  
pp. 533-543 ◽  
Author(s):  
Pernille D. K. Diasso ◽  
Per Sjøgren ◽  
Jette Højsted ◽  
Susanne D. Nielsen ◽  
Katharina M. Main ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Reaction Time ◽  
Pilot Study ◽  
Cancer Pain ◽  
Opioid Consumption ◽  
Opioid Treatment ◽  
Continuous Reaction ◽  
Continuous Reaction Time

Abstract Background and aims Opioid consumption has increased dramatically in patients with chronic non-cancer pain (CNCP), but long-term consequences are still unclear. The aim of this study is to investigate the effects of long-term opioid treatment on pain, cognition, mood, sleep and quality of life in CNCP patients. Methods In this cross-sectional pilot study, two groups of patients with CNCP treated in a multidisciplinary pain center were selected: (1) opioid group: ≥30 mg morphine equivalent/day for >4 weeks, and (2) control group: no opioid consumption for >4 weeks. Socio-demographic data, alcohol consumption, smoking habits and body mass index (BMI) were registered and pain (brief pain inventory), mood (Hospital Anxiety and Depression Scale), sleep (Pittsburgh Sleep Quality Index) and quality of life (RAND 36-Item Health Survey) were assessed. Continuous Reaction Time and the Digit Span Test were used to evaluate cognitive function. Data was analyzed with a Fisher’s exact test and Wilcoxon two-sample test. Results Forty-two patients with CNCP were included (21 in each group). No differences regarding socio-demographics, smoking/alcohol habits and duration, type, or intensity of pain were found. More patients in the opioid group had significantly higher BMI (62% above BMI 25 vs. 33.3%, p = 0.042). Consequently, the subsequent data analyses were controlled for BMI. The two groups did not differ in pain, cognition, anxiety, depression, sleep or quality of life but both showed lower values than the normal standards. Further, the opioid group presented a tendency to lower ratings regarding pain and social function and performed below the normal cut off in the continuous reaction time. Conclusions No significant differences between the two groups were found regarding any of the above-mentioned variables. Interestingly, the patients assessed, regardless of taking opioids or not, could be classified with moderate pain intensity, anxiety and low quality of sleep and life compared to norm standards. Implications The findings of this pilot study suggested that long-term opioid treatment may influence pain and quality of life among CNCP patients. A larger cohort is needed to verify these findings.

scholarly journals Modeling acquaintance networks based on balance theory

2014 ◽  
Vol 24 (3) ◽  
pp. 683-696 ◽  
Author(s):  
Vida Vukašinović ◽  
Jurij Šilc ◽  
Risth Škrekovski
Keyword(s):  
Path Length ◽  
Animal Species ◽  
Small Diameter ◽  
Clustering Coefficient ◽  
The Other ◽  
Balance Theory ◽  
Mature Phase ◽  
The Social ◽  
Network Properties ◽  
E Mail

Abstract An acquaintance network is a social structure made up of a set of actors and the ties between them. These ties change dynamically as a consequence of incessant interactions between the actors. In this paper we introduce a social network model called the Interaction-Based (IB) model that involves well-known sociological principles. The connections between the actors and the strength of the connections are influenced by the continuous positive and negative interactions between the actors and, vice versa, the future interactions are more likely to happen between the actors that are connected with stronger ties. The model is also inspired by the social behavior of animal species, particularly that of ants in their colony. A model evaluation showed that the IB model turned out to be sparse. The model has a small diameter and an average path length that grows in proportion to the logarithm of the number of vertices. The clustering coefficient is relatively high, and its value stabilizes in larger networks. The degree distributions are slightly right-skewed. In the mature phase of the IB model, i.e., when the number of edges does not change significantly, most of the network properties do not change significantly either. The IB model was found to be the best of all the compared models in simulating the e-mail URV (University Rovira i Virgili of Tarragona) network because the properties of the IB model more closely matched those of the e-mail URV network than the other models

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