Construction and analysis of brain networks from different neuroimaging techniques

Prajapati, Rutvi; Emerson, Isaac Arnold

doi:10.1080/00207454.2020.1837802

Cited by 7 publications

(2 citation statements)

References 143 publications

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“…In recent years, resting-state functional magnetic resonance imaging (fMRI) has been widely applied to detect functional connectivity and regional neural activity according to spontaneous blood oxygen level-dependent (BOLD) signal fluctuations at rest, which substantially reduces the potential influences of task performance [5,6]. Using seedbased approaches or independent component analysis, a growing body of resting-state MRI studies have revealed associations between FOG and dysfunction in multiple brain networks, including the locomotor network, executive-attention associative frontoparietal network, visual occipitotemporal network, and limbic network [7][8][9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Brain network topology and future development of freezing of gait in Parkinson’s disease: a longitudinal study

Lei

Peng

et al. 2021

J Neurol

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Background Freezing of gait (FOG) is a common disabling gait disturbance in Parkinson's disease (PD). The objectives of this study were to explore alterations in the topological organization of whole-brain functional networks in patients with PD who will develop FOG. Methods We recruited 20 patients with PD who developed FOG (PD-FOGt) during a 5-year follow-up period, 20 patients with PD who did not developed FOG (PD-FOGn) within the follow-up period, and 20 healthy control subjects. Using graph theory approaches, we performed a comparative analysis of the topological organization of whole-brain functional networks among the groups, and further explored their potential relationships with latency to develop FOG. Results At baseline, the global topological properties of functional brain networks in PD-FOGt and PD-FOGn showed no abnormalities. Additionally, regarding regional topological properties, compared with PD-FOGn patients, PD-FOGt patients exhibited decreased nodal centrality in the left middle frontal gyrus (MFG). Although there were no significant differences compared with PD-FOGn patients, the PD-FOGt group exhibited the lowest nodal centrality values in the frontal cortex (left gyrus rectus), and visual cortex (bilateral inferior occipital gyrus and left fusiform gyrus), and the highest nodal centrality values in the cerebellum (vermis_6) among the three groups. However, no relationship was found between the nodal centrality in above brain regions and latency to develop FOG. Conclusion This study demonstrates the disrupted regional topological organization might contribute to the future development of FOG in PD patients, especially associated with damage to the left MFG.

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Section: Introductionmentioning

confidence: 99%

Brain network topology and future development of freezing of gait in Parkinson’s disease: a longitudinal study

Lei

Peng

et al. 2021

J Neurol

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“…The two fundamental elements of the network are edges and nodes, where nodes represent the brain regions and edges depict the functional connectivity between two brain regions or nodes. The Region of interest for this category are frontoparietal, cingulo-opercular, sensorimotor, occipital, and cerebellum were selected from Dosenbach atlas [ 21] to draw functional connectome and the output is shown in Fig. 6.…”

Section: Network Construction and Functional Connectomementioning

confidence: 99%

Diagnosis of Parkinson’s disease using EEG and fMRI

Jiji¹,

Rajesh

Lakshmi³

2022

Multimed Tools Appl

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Parkinson's disease is a brain disorder that leads to shaking, stiffness, and di culty with walking, balance, and coordination. Parkinson's symptoms usually begin gradually and get worse over time. As the disease progresses, people may have di culty walking and talking. In this system, an Architecture is proposed for Parkinson's disease detection by investigating the topological properties of functional brain networks within fMRI and EEG Signals of Healthy Control (normal) and PD patients. For fMRI the functional whole-brain connectome was constructed by thresholding partial correlation matrices of 160 regions from Dosenbach brain atlas. 160 x 160 functional correlation matrix was constructed using the Pearson correlation. From the graph theory approach, network metrics were analysed. For EEG spatial and Bispectrum features are extracted. Finally, Adaboost Classi er is used to classify whether it is normal or PD.

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A Hybrid Approach for Classifying Parkinson’s Disease from Brain MRI

Sreelakshmi¹,

Mathew²

2022

Lecture Notes in Networks and Systems

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Construction and analysis of brain networks from different neuroimaging techniques

Cited by 7 publications

References 143 publications

Brain network topology and future development of freezing of gait in Parkinson’s disease: a longitudinal study

Brain network topology and future development of freezing of gait in Parkinson’s disease: a longitudinal study

Diagnosis of Parkinson’s disease using EEG and fMRI

A Hybrid Approach for Classifying Parkinson’s Disease from Brain MRI

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