scholarly journals Abnormal topological organization of the white matter network in Mandarin speakers with congenital amusia

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Yanxin Zhao ◽  
Xizhuo Chen ◽  
Suyu Zhong ◽  
Zaixu Cui ◽  
Gaolang Gong ◽  
...  
Keyword(s):  
White Matter ◽  
Shortest Path ◽  
Path Length ◽  
Clustering Coefficient ◽  
Lexical Tone ◽  
Functional Connections ◽  
Congenital Amusia ◽  
Brain White Matter ◽  
Holistic Understanding ◽  
Global Connectivity

Abstract Congenital amusia is a neurogenetic disorder that mainly affects the processing of musical pitch. Brain imaging evidence indicates that it is associated with abnormal structural and functional connections in the fronto-temporal region. However, a holistic understanding of the anatomical topology underlying amusia is still lacking. Here, we used probabilistic diffusion tensor imaging tractography and graph theory to examine whole brain white matter structural connectivity in 31 Mandarin-speaking amusics and 24 age- and IQ-matched controls. Amusics showed significantly reduced global connectivity, as indicated by the abnormally decreased clustering coefficient (Cp) and increased normalized shortest path length (λ) compared to the controls. Moreover, amusics exhibited enhanced nodal strength in the right inferior parietal lobule relative to controls. The co-existence of the lexical tone deficits was associated with even more deteriorated global network efficiency in amusics, as suggested by the significant correlation between the increments in normalized shortest path length (λ) and the insensitivity in lexical tone perception. Our study is the first to reveal reduced global connectivity efficiency in amusics as well as an increase in the global connectivity cost due to the co-existed lexical tone deficits. Taken together these results provide a holistic perspective on the anatomical substrates underlying congenital amusia.

scholarly journals Enhancement of indirect functional connections with shortest path length in the adult autistic brain

2019 ◽  
Vol 40 (18) ◽  
pp. 5354-5369 ◽  
Author(s):  
Xiaonan Guo ◽  
Tiago Simas ◽  
Meng‐Chuan Lai ◽  
Michael V. Lombardo ◽  
Bhismadev Chakrabarti ◽  
...  
Keyword(s):  
Shortest Path ◽  
Path Length ◽  
Functional Connections

scholarly journals Disrupted Topological Organization in White Matter Networks in Unilateral Sudden Sensorineural Hearing Loss

2021 ◽  
Vol 15 ◽  
Author(s):  
Yan Zou ◽  
Hui Ma ◽  
Bo Liu ◽  
Dan Li ◽  
Dingxi Liu ◽  
...  
Keyword(s):  
Hearing Loss ◽  
White Matter ◽  
Sensorineural Hearing Loss ◽  
Path Length ◽  
Sudden Sensorineural Hearing Loss ◽  
Sensorineural Hearing ◽  
Clustering Coefficient ◽  
Healthy Controls ◽  
Characteristic Path Length ◽  
Topological Organization

Sudden sensorineural hearing loss (SSNHL) is a sudden-onset hearing impairment that rapidly develops within 72 h and is mostly unilateral. Only a few patients can be identified with a defined cause by routine clinical examinations. Recently, some studies have shown that unilateral SSNHL is associated with alterations in the central nervous system. However, little is known about the topological organization of white matter (WM) networks in unilateral SSNHL patients in the acute phase. In this study, 145 patients with SSNHL and 91 age-, gender-, and education-matched healthy controls were evaluated using diffusion tensor imaging (DTI) and graph theoretical approaches. The topological properties of WM networks, including global and nodal parameters, were investigated. At the global level, SSNHL patients displayed decreased clustering coefficient, local efficiency, global efficiency, normalized clustering coefficient, normalized characteristic path length, and small-worldness and increased characteristic path length (p < 0.05) compared with healthy controls. At the nodal level, altered nodal centralities in brain regions involved the auditory network, visual network, attention network, default mode network (DMN), sensorimotor network, and subcortical network (p < 0.05, Bonferroni corrected). These findings indicate a shift of the WM network topology in SSNHL patients toward randomization, which is characterized by decreased global network integration and segregation and is reflected by decreased global connectivity and altered nodal centralities. This study could help us understand the potential pathophysiology of unilateral SSNHL.

scholarly journals Disrupted Network Topology Contributed to Spatial Navigation Impairment in Patients With Mild Cognitive Impairment

2021 ◽  
Vol 13 ◽  
Author(s):  
Weiping Li ◽  
Hui Zhao ◽  
Zhao Qing ◽  
Zuzana Nedelska ◽  
Sichu Wu ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Shortest Path ◽  
Network Topology ◽  
Path Length ◽  
Spatial Navigation ◽  
Structural Connectivity ◽  
Clustering Coefficient ◽  
Topological Features ◽  
The Right

Impairment in spatial navigation (SN) and structural network topology is not limited to patients with Alzheimer’s disease (AD) dementia and can be detected earlier in patients with mild cognitive impairment (MCI). We recruited 32 MCI patients (65.91 ± 11.33 years old) and 28 normal cognition patients (NC; 69.68 ± 10.79 years old), all of whom underwent a computer-based battery of SN tests evaluating egocentric, allocentric, and mixed SN strategies and diffusion-weighted and T1-weighted Magnetic Resonance Imaging (MRI). To evaluate the topological features of the structural connectivity network, we calculated its measures such as the global efficiency, local efficiency, clustering coefficient, and shortest path length with GRETNA. We determined the correlation between SN accuracy and network topological properties. Compared to NC, MCI subjects demonstrated a lower egocentric navigation accuracy. Compared with NC, MCI subjects showed significantly decreased clustering coefficients in the left middle frontal gyrus, right rectus, right superior parietal gyrus, and right inferior parietal gyrus and decreased shortest path length in the left paracentral lobule. We observed significant positive correlations of the shortest path length in the left paracentral lobule with both the mixed allocentric–egocentric and the allocentric accuracy measured by the average total errors. A decreased clustering coefficient in the right inferior parietal gyrus was associated with a larger allocentric navigation error. White matter hyperintensities (WMH) did not affect the correlation between network properties and SN accuracy. This study demonstrated that structural connectivity network abnormalities, especially in the frontal and parietal gyri, are associated with a lower SN accuracy, independently of WMH, providing a new insight into the brain mechanisms associated with SN impairment in MCI.

Optimizing Navigation Satellite Enhancement Information Distribution Network Based on X10 and MPI

2011 ◽  
Vol 58-60 ◽  
pp. 2177-2182
Author(s):  
Jun Xia Liu ◽  
Shao Hua Liu ◽  
Jun Sheng Yu ◽  
Peng Xie ◽  
Ze Jian Lu ◽  
...  
Keyword(s):  
Shortest Path ◽  
Path Length ◽  
Large Scale ◽  
Sparse Matrix ◽  
Distribution Network ◽  
Small World ◽  
Clustering Coefficient ◽  
Navigation Satellite ◽  
Information Distribution ◽  
Performance Requirements

To meet large-scale and time-sensitive needs of navigation Satellite enhance information distribution network in Global Position System(GPS)/Beidou and other systems [1], use small-world network model of complex network to study the topology. Small-world model has a large clustering coefficient and smaller average shortest path length so it can meet performance requirements better. Use Python language to product WS model, and simulate the important parameter-the average shortest path length. Use Dijkstra parallel algorithm and sparse matrix storage method to simulate under the use of X10 parallel language. Analyze the relationship between average shortest path length and random reconnection probability. Additionally, simulate in parallel MPI library and compare the two.

ANALISIS PERINGKAT TOP BRAND OJEK ONLINE MENGGUNAKAN JEJARING SOSIAL PERCAKAPAN TWITTER

2019 ◽  
Vol 24 (2) ◽  
pp. 88-104
Author(s):  
Ilham Aminudin ◽  
Dyah Anggraini
Keyword(s):  
Social Media ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Path Length ◽  
Average Path Length ◽  
Average Degree ◽  
Clustering Coefficient ◽  
R Programming

Banyak bisnis mulai muncul dengan melibatkan pengembangan teknologi internet. Salah satunya adalah bisnis di aplikasi berbasis penyedia layanan di bidang moda transportasi berbasis online yang ternyata dapat memberikan solusi dan menjawab berbagai kekhawatiran publik tentang layanan transportasi umum. Kemacetan lalu lintas di kota-kota besar dan ketegangan publik dengan keamanan transportasi umum diselesaikan dengan adanya aplikasi transportasi online seperti Grab dan Gojek yang memberikan kemudahan dan kenyamanan bagi penggunanya Penelitian ini dilakukan untuk menganalisa keaktifan percakapan brand jasa transportasi online di jejaring sosial Twitter berdasarkan properti jaringan. Penelitian dilakukan dengan dengan mengambil data dari percakapan pengguna di social media Twitter dengan cara crawling menggunakan Bahasa pemrograman R programming dan software R Studio dan pembuatan model jaringan dengan software Gephy. Setelah itu data dianalisis menggunakan metode social network analysis yang terdiri berdasarkan properti jaringan yaitu size, density, modularity, diameter, average degree, average path length, dan clustering coefficient dan nantinya hasil analisis akan dibandingkan dari setiap properti jaringan kedua brand jasa transportasi Online dan ditentukan strategi dalam meningkatkan dan mempertahankan keaktifan serta tingkat kehadiran brand jasa transportasi online, Grab dan Gojek.

scholarly journals Topological measures for identifying and predicting the spread of complex contagions

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Douglas Guilbeault ◽  
Damon Centola
Keyword(s):  
Social Networks ◽  
Shortest Path ◽  
Empirical Data ◽  
Path Length ◽  
Centrality Measures ◽  
Social Phenomena ◽  
Node Centrality ◽  
Network Connectedness ◽  
Topological Measures ◽  
Definition Of

AbstractThe standard measure of distance in social networks – average shortest path length – assumes a model of “simple” contagion, in which people only need exposure to influence from one peer to adopt the contagion. However, many social phenomena are “complex” contagions, for which people need exposure to multiple peers before they adopt. Here, we show that the classical measure of path length fails to define network connectedness and node centrality for complex contagions. Centrality measures and seeding strategies based on the classical definition of path length frequently misidentify the network features that are most effective for spreading complex contagions. To address these issues, we derive measures of complex path length and complex centrality, which significantly improve the capacity to identify the network structures and central individuals best suited for spreading complex contagions. We validate our theory using empirical data on the spread of a microfinance program in 43 rural Indian villages.

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