scholarly journals Anhedonia Relates to the Altered Global and Local Grey Matter Network Properties in Schizophrenia

2021 ◽  
Vol 10 (7) ◽  
pp. 1395
Author(s):  
Byung-Hoon Kim ◽  
Hesun Erin Kim ◽  
Jung Suk Lee ◽  
Jae-Jin Kim
Keyword(s):  
Negative Symptoms ◽  
Grey Matter ◽  
Regional Scale ◽  
Real Life ◽  
Small World ◽  
Global Scale ◽  
Single Subject ◽  
Social Anhedonia ◽  
Whole Brain ◽  
Small World Property

Anhedonia is one of the major negative symptoms in schizophrenia and defined as the loss of hedonic experience to various stimuli in real life. Although structural magnetic resonance imaging has provided a deeper understanding of anhedonia-related abnormalities in schizophrenia, network analysis of the grey matter focusing on this symptom is lacking. In this study, single-subject grey matter networks were constructed in 123 patients with schizophrenia and 160 healthy controls. The small-world property of the grey matter network and its correlations with the level of physical and social anhedonia were evaluated using graph theory analysis. In the global scale whole-brain analysis, the patients showed reduced small-world property of the grey matter network. The local-scale analysis further revealed reduced small-world property in the default mode network, salience/ventral attention network, and visual network. The regional-level analysis showed an altered relationship between the small-world properties and the social anhedonia scale scores in the cerebellar lobule in patients with schizophrenia. These results indicate that anhedonia in schizophrenia may be related to abnormalities in the grey matter network at both the global whole-brain scale and local–regional scale.

A NETWORK MODEL GENERATED FROM THE RECURSIVE GRAPH BASED ON POLYGON

2013 ◽  
Vol 24 (09) ◽  
pp. 1350062 ◽  
Author(s):  
YUANYUAN SUN ◽  
KAINING HOU ◽  
YUJIE ZHAO
Keyword(s):  
Real Life ◽  
Network Models ◽  
Small World ◽  
Mapping Method ◽  
Clustering Coefficient ◽  
Research Fields ◽  
Network Diameter ◽  
Degree Correlations ◽  
New Perspective ◽  
Small World Property

The study of network models is one of the most challenging research fields among the studies of complex networks, which have been the hot research topics in recent decades. In this paper, we construct a deterministic network by a mapping method based on a recursive graph, and analyze its topological characteristics, including degree distribution, clustering coefficient, network diameter, average path length and degree correlations. We obtain that this network has the small-world property and positive correlation. The network modeling as we present gives a new perspective on networks, and helps to understand better the evolutions of the real-life systems, making it possible to explore the complexity of complex systems.

scholarly journals White Matter Network Alterations in Alzheimer’s Disease Patients

2020 ◽  
Vol 10 (3) ◽  
pp. 919
Author(s):  
Ramesh Kumar Lama ◽  
Sang-Woong Lee
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
White Matter ◽  
Grey Matter ◽  
Small World ◽  
Brain Network ◽  
Topological Properties ◽  
Graph Theoretical Analysis ◽  
Small World Property ◽  
The Brain

Previous studies have revealed the occurrence of alterations of white matter (WM) and grey matter (GM) microstructures in Alzheimer’s disease (AD) and their prodromal state amnestic mild cognitive impairment (MCI). In general, these alterations can be studied comprehensively by modeling the brain as a complex network, which describes many important topological properties, such as the small-world property, modularity, and efficiency. In this study, we systematically investigated white matter abnormalities using unbiased whole brain network analysis. We compared regional and network related WM features between groups of 19 AD and 25 MCI patients and 22 healthy controls (HC) using tract-based spatial statistics (TBSS), network based statistics (NBS) and graph theoretical analysis. We did not find significant differences in fractional anisotropy (FA) between two groups on TBSS analysis. However, observable alterations were noticed at a network level. Brain network measures such as global efficiency and small world properties were low in AD patients compared to HCs.

Conceptual disorganization and redistribution of resting state cortical hubs in untreated first episode psychosis: A 7T MRI study

2020 ◽  
Author(s):  
Avyarthana Dey ◽  
Kara Dempster ◽  
Michael Mackinley ◽  
Peter Jeon ◽  
Tushar Das ◽  
...  
Keyword(s):  
Negative Symptoms ◽  
Superior Temporal Gyrus ◽  
Brain Regions ◽  
First Episode Psychosis ◽  
Cortical Reorganization ◽  
First Episode ◽  
Formal Thought Disorder ◽  
Whole Brain ◽  
Episode Psychosis ◽  
Positive And Negative Symptoms

Background:Network level dysconnectivity has been studied in positive and negative symptoms of schizophrenia. Conceptual disorganization (CD) is a symptom subtype which predicts impaired real-world functioning in psychosis. Systematic reviews have reported aberrant connectivity in formal thought disorder, a construct related to CD. However, no studies have investigated whole-brain functional correlates of CD in psychosis. We sought to investigate brain regions explaining the severity of CD in patients with first-episode psychosis (FEPs) compared with healthy controls (HCs).Methods:We computed whole-brain binarized degree centrality maps of 31 FEPs, 25 HCs and characterized the patterns of network connectivity in the two groups. In FEPs, we related these findings to the severity of CD. We also studied the effect of positive and negative symptoms on altered network connectivity.Results:Compared to HCs, reduced hubness of a right superior temporal gyrus (rSTG) cluster was observed in the FEPs. In patients exhibiting high CD, increased hubness of a medial superior parietal (mSPL) cluster was observed, compared to patients exhibiting low CD. These two regions were strongly correlated with CD scores but not with other symptom scores.Discussion:Our observations are congruent with previous findings of reduced but not increased hubness. We observed increased hubness of mSPL suggesting that cortical reorganization occurs to provide alternate routes for information transfer.Conclusion:These findings provide insight into the underlying neural processes mediating the presentation of symptoms in untreated FEP. A longitudinal tracking of the symptom course will be useful to assess the mechanisms underlying these compensatory changes.

Are local losses of biodiversity causing degraded ecosystem function?

2017 ◽  
Author(s):  
Mark Vellend
Keyword(s):  
Ecosystem Function ◽  
Species Interactions ◽  
Regional Scale ◽  
Temporal Trends ◽  
Biodiversity Loss ◽  
Large Degree ◽  
Global Scale ◽  
Degraded Ecosystem ◽  
Biodiversity Change ◽  
Local Extirpation

This chapter highlights the scale dependence of biodiversity change over time and its consequences for arguments about the instrumental value of biodiversity. While biodiversity is in decline on a global scale, the temporal trends on regional and local scales include cases of biodiversity increase, no change, and decline. Environmental change, anthropogenic or otherwise, causes both local extirpation and colonization of species, and thus turnover in species composition, but not necessarily declines in biodiversity. In some situations, such as plants at the regional scale, human-mediated colonizations have greatly outnumbered extinctions, thus causing a marked increase in species richness. Since the potential influence of biodiversity on ecosystem function and services is mediated to a large degree by local or neighborhood species interactions, these results challenge the generality of the argument that biodiversity loss is putting at risk the ecosystem service benefits people receive from nature.

scholarly journals The Associations between COMT and MAO-B Genetic Variants with Negative Symptoms in Patients with Schizophrenia

2021 ◽  
Vol 43 (2) ◽  
pp. 618-636
Author(s):  
Zoran Madzarac ◽  
Lucija Tudor ◽  
Marina Sagud ◽  
Gordana Nedic Erjavec ◽  
Alma Mihaljevic Peles ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Negative Symptoms ◽  
Type B ◽  
Social Anhedonia ◽  
Mao B ◽  
Comt Activity ◽  
Striatal Dopamine Release ◽  
Heavy Burden ◽  
Specific Increase ◽  
Male Patients

Negative symptoms of schizophrenia, including anhedonia, represent a heavy burden on patients and their relatives. These symptoms are associated with cortical hypodopamynergia and impaired striatal dopamine release in response to reward stimuli. Catechol-O-methyltransferase (COMT) and monoamine oxidase type B (MAO-B) degrade dopamine and affect its neurotransmission. The study determined the association between COMT rs4680 and rs4818, MAO-B rs1799836 and rs6651806 polymorphisms, the severity of negative symptoms, and physical and social anhedonia in schizophrenia. Sex-dependent associations were detected in a research sample of 302 patients with schizophrenia. In female patients with schizophrenia, the presence of the G allele or GG genotype of COMT rs4680 and rs4818, as well as GG haplotype rs4818-rs4680, which were all related to higher COMT activity, was associated with an increase in several dimensions of negative symptoms and anhedonia. In male patients with schizophrenia, carriers of the MAO-B rs1799836 A allele, presumably associated with higher MAO-B activity, had a higher severity of alogia, while carriers of the A allele of the MAO-B rs6651806 had a higher severity of negative symptoms. These findings suggest that higher dopamine degradation, associated with COMT and MAO-B genetic variants, is associated with a sex-specific increase in the severity of negative symptoms in schizophrenia patients.

scholarly journals Can recurrence networks show small-world property?

2016 ◽  
Vol 380 (35) ◽  
pp. 2718-2723 ◽  
Author(s):  
Rinku Jacob ◽  
K.P. Harikrishnan ◽  
R. Misra ◽  
G. Ambika
Keyword(s):  
Small World ◽  
Small World Property

Grey matter alterations in obesity: A meta‐analysis of whole‐brain studies

2018 ◽  
Vol 20 (3) ◽  
pp. 464-471 ◽  
Author(s):  
Martin J. Herrmann ◽  
Ann‐Katrin Tesar ◽  
Jennifer Beier ◽  
Max Berg ◽  
Bodo Warrings
Keyword(s):  
Grey Matter ◽  
Meta Analysis ◽  
Whole Brain

scholarly journals Quantitative method for resilience assessment framework of airport network during COVID-19

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0260940
Author(s):  
Jiuxia Guo ◽  
Yang Li ◽  
Zongxin Yang ◽  
Xinping Zhu
Keyword(s):  
Complex Network ◽  
Small World ◽  
Global Scale ◽  
Assessment Framework ◽  
Small World Networks ◽  
Scale Free ◽  
Global Pandemic ◽  
Network Metrics ◽  
Resilience Assessment

The resilience and vulnerability of airport networks are significant challenges during the COVID-19 global pandemic. Previous studies considered node failure of networks under natural disasters and extreme weather. Herein, we propose a complex network methodology combined with data-driven to assess the resilience of airport networks toward global-scale disturbance using the Chinese airport network (CAN) and the European airport network (EAN) as a case study. The assessment framework includes vulnerability and resilience analyses from the network- and node-level perspectives. Subsequently, we apply the framework to analyze the airport networks in China and Europe. Specifically, real air traffic data for 232 airports in China and 82 airports in Europe are selected to form the CAN and EAN, respectively. The complex network analysis reveals that the CAN and the EAN are scale-free small-world networks, that are resilient to random attacks. However, the connectivity and vulnerability of the CAN are inferior to those of the EAN. In addition, we select the passenger throughput from the top-50 airports in China and Europe to perform a comparative analysis. By comparing the resilience evaluation of individual airports, we discovered that the factors of resilience assessment of an airport network for global disturbance considers the network metrics and the effect of government policy in actual operations. Additionally, this study also proves that a country’s emergency response-ability towards the COVID-19 has a significantly affectes the recovery of its airport network.

scholarly journals Application of global models and satellite data for smaller-scale groundwater recharge studies

2016 ◽  
Author(s):  
Rogier Westerhoff ◽  
Paul White ◽  
Zara Rawlinson
Keyword(s):  
New Zealand ◽  
Satellite Data ◽  
Input Data ◽  
Large Scale ◽  
Regional Scale ◽  
Global Scale ◽  
Global Models ◽  
Scale Models ◽  
Boundary Issues ◽  
Rainfall Recharge

Abstract. Large-scale models and satellite data are increasingly used to characterise groundwater and its recharge at the global scale. Although these models have the potential to fill in data gaps and solve trans-boundary issues, they are often neglected in smaller-scale studies, since data are often coarse or uncertain. Large-scale models and satellite data could play a more important role in smaller-scale (i.e., national or regional) studies, if they could be adjusted to fit that scale. In New Zealand, large-scale models and satellite data are not used for groundwater recharge estimation at the national scale, since regional councils (i.e., the water managers) have varying water policy and models are calibrated at the local scale. Also, some regions have many localised ground observations (but poor record coverage), whereas others are data-sparse. Therefore, estimation of recharge is inconsistent at the national scale. This paper presents an approach to apply large-scale, global, models and satellite data to estimate rainfall recharge at the national to regional scale across New Zealand. We present a model, NGRM, that is largely inspired by the global-scale WaterGAP recharge model, but is improved and adjusted using national data. The NGRM model uses MODIS-derived ET and vegetation satellite data, and the available nation-wide datasets on rainfall, elevation, soil and geology. A valuable addition to the recharge estimation is the model uncertainty estimate, based on variance, covariance and sensitivity of all input data components in the model environment. This research shows that, with minor model adjustments and use of improved input data, large-scale models and satellite data can be used to derive rainfall recharge estimates, including their uncertainty, at the smaller scale, i.e., national and regional scale of New Zealand. The estimated New Zealand recharge of the NGRM model compare well to most local and regional lysimeter data and recharge models. The NGRM is therefore assumed to be capable to fill in gaps in data-sparse areas and to create more consistency between datasets from different regions, i.e., to solve trans-boundary issues. This research also shows that smaller-scale recharge studies in New Zealand should include larger boundaries than only a (sub-)aquifer, and preferably the whole catchment. This research points out the need for improved collaboration on the international to national to regional levels to further merge large-scale (global) models to smaller (i.e., national or regional) scales. Future research topics should, collaboratively, focus on: improvement of rainfall-runoff and snowmelt methods; inclusion of river recharge; further improvement of input data (rainfall, evapotranspiration, soil and geology); and the impact of recharge uncertainty in mountainous and irrigated areas.

scholarly journals Impacts of spatial resolution and representation of flow connectivity on large-scale simulation of floods

2017 ◽  
Author(s):  
Cherry May R. Mateo ◽  
Dai Yamazaki ◽  
Hyungjun Kim ◽  
Adisorn Champathong ◽  
Jai Vaze ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Large Scale ◽  
Flood Hazard ◽  
Regional Scale ◽  
Global Scale ◽  
Test Case ◽  
Efficiency Coefficient ◽  
Computational Power ◽  
Extreme Flood ◽  
Simulation Results

Abstract. Global-scale River Models (GRMs) are core tools for providing consistent estimates of global flood hazard, especially in data-scarce regions. Due to former limitations in computational power and input datasets, most GRMs have been developed to use simplified representation of flow physics and run at coarse spatial resolutions. With increasing computational power and improved datasets, the application of GRMs to finer resolutions is becoming a reality. To support development in this direction, the suitability of GRMs for application to finer resolutions needs to be assessed. This study investigates the impacts of spatial resolution and flow connectivity representation on the predictive capability of a GRM, CaMa-Flood, in simulating the 2011 extreme flood in Thailand. Analyses show that when single downstream connectivity (SDC) is assumed, simulation results deteriorate with finer spatial resolution; Nash–Sutcliffe Efficiency coefficient decreased by more than 35 % between simulation results at 10 km resolution and 1 km resolution. When multiple downstream connectivity (MDC) is represented, simulation results slightly improve with finer spatial resolution. The SDC simulations result in excessive backflows on very flat floodplains due to the restrictive flow directions in finer resolutions. MDC channels attenuated these effects by maintaining flow connectivity and flow capacity between floodplains in varying spatial resolutions. While a regional-scale flood was chosen as a test case, these findings are universal and can be extended to global-scale simulations. These results demonstrate that a GRM can be used for higher resolution simulations of large-scale floods, provided that MDC in rivers and floodplains is adequately represented in the model structure.

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