Connectivity brain networks based on wavelet correlation analysis in Parkinson fMRI data

Skidmore, Frank; Korenkevych, Dmytro; Liu, Y.; He, Guojun; Bullmore, Edward T.; Pardalos, Pãnos M.

doi:10.1016/j.neulet.2011.05.030

Cited by 133 publications

(124 citation statements)

References 16 publications

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“…Skidmore et al (2011) found decreased mean global efficiency in PD, as well as decreased efficiency for many nodes including precuneus/cuneus, middle frontal gyrus, supplementary and precentral regions, calcarine and secondary visual regions, and cerebellum. Göttlich et al (2013) also observed decreased global efficiency and increased characteristic path length in PD.…”

Section: Neuroimaging Of Pdmentioning

confidence: 85%

Neuroimaging of Parkinson's disease: Expanding views

Weingarten

Sundman

Hickey

et al. 2015

Neuroscience & Biobehavioral Reviews

137

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Advances in molecular and structural and functional neuroimaging are rapidly expanding the complexity of neurobiological understanding of Parkinson’s disease (PD). This review article begins with an introduction to PD neurobiology as a foundation for interpreting neuroimaging findings that may further lead to more integrated and comprehensive understanding of PD. Diverse areas of PD neuroimaging are then reviewed and summarized, including positron emission tomography, single photon emission computed tomography, magnetic resonance spectroscopy and imaging, transcranial sonography, magnetoencephalography, and multimodal imaging, with focus on human studies published over the last five years. These included studies on differential diagnosis, co-morbidity, genetic and prodromal PD, and treatments from L-DOPA to brain stimulation approaches, transplantation and gene therapies. Overall, neuroimaging has shown that PD is a neurodegenerative disorder involving many neurotransmitters, brain regions, structural and functional connections, and neurocognitive systems. A broad neurobiological understanding of PD will be essential for translational efforts to develop better treatments and preventive strategies. Many questions remain and we conclude with some suggestions for future directions of neuroimaging of PD.

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Section: Neuroimaging Of Pdmentioning

confidence: 85%

Neuroimaging of Parkinson's disease: Expanding views

Weingarten

Sundman

Hickey

et al. 2015

Neuroscience & Biobehavioral Reviews

137

View full text Add to dashboard Cite

show abstract

“…Using Rs-fMRI and graph theory, researchers have explored PD-related abnormal functional brain network in PD, including topological architecture [6,7] and spontaneous brain activity [8]. For example, PD patients exhibit marked decrease in nodal and global efficiency [9], local efficiency, and local clustering coefficient [10]. Furthermore, major reductions in long-range connection in PD patients with mild, or no, cognitive impairment were detected [11].…”

Section: Introductionmentioning

confidence: 99%

Disrupted Brain Network Hubs in Subtype-Specific Parkinson's Disease

Chen

et al. 2017

Eur Neurol

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Background/Aims: The topological organization of brain functional networks is impaired in Parkinson's disease (PD). However, the altered patterns of functional network hubs in different subtypes of PD are not completely understood. Methods: 3T resting-state functional MRI and voxel-based graph-theory analysis were employed to systematically investigate the intrinsic functional connectivity patterns of whole-brain networks. We enrolled 31 patients with PD (12 tremor dominant [TD] and 19 with postural instability/gait difficulty [PIGD]) and 22 matched healthy controls. Whole-brain voxel-wise functional networks were constructed by measuring the temporal correlations of each pair of brain voxels. Functional connectivity strength was calculated to explore the brain network hubs. Results: We found that both the TD and PIGD subtypes had comprehensive disrupted regions. These mainly involved the basal ganglia, cerebellum, superior temporal gyrus, pre- and postcentral gyri, inferior frontal gyrus, middle temporal gyrus, lingual gyrus, insula, and parahippocampal gyrus. Furthermore, the PIGD subgroup had more disrupted hubs in the cerebellum than the TD subgroup. These disruptions of hub connectivity were not correlated with the HY stage or disease duration. Conclusion: Our results emphasize the subtype-specific PD-related degeneration of brain hubs, providing novel insights into the pathophysiological mechanisms of connectivity dysfunction in different PD subgroups.

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“…(i) Using fMRI: to investigate the efficiency of functional brain networks of PD patients, Skidmore et al [122] constructed functional brain networks of 14 PD patients and 15 HCs. They found decreased global efficiency and decreased nodal efficiency in the left supplementary motor cortex, contiguous precentral regions, the calcarine cortices, secondary visual regions, and the certain regions within the cerebellum in PD patients.…”

Section: Functional Brain Network In Pdmentioning

confidence: 99%

Complex Brain Network Analysis and Its Applications to Brain Disorders: A Survey

et al. 2017

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It is well known that most brain disorders are complex diseases, such as Alzheimer's disease (AD) and schizophrenia (SCZ). In general, brain regions and their interactions can be modeled as complex brain network, which describe highly efficient information transmission in a brain. Therefore, complex brain network analysis plays an important role in the study of complex brain diseases. With the development of noninvasive neuroimaging and electrophysiological techniques, experimental data can be produced for constructing complex brain networks. In recent years, researchers have found that brain networks constructed by using neuroimaging data and electrophysiological data have many important topological properties, such as small-world property, modularity, and rich club. More importantly, many brain disorders have been found to be associated with the abnormal topological structures of brain networks. These findings provide not only a new perspective to explore the pathological mechanisms of brain disorders, but also guidance for early diagnosis and treatment of brain disorders. The purpose of this survey is to provide a comprehensive overview for complex brain network analysis and its applications to brain disorders.

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Connectivity brain networks based on wavelet correlation analysis in Parkinson fMRI data

Cited by 133 publications

References 16 publications

Neuroimaging of Parkinson's disease: Expanding views

Neuroimaging of Parkinson's disease: Expanding views

Disrupted Brain Network Hubs in Subtype-Specific Parkinson's Disease

Complex Brain Network Analysis and Its Applications to Brain Disorders: A Survey

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