Magnetic Resonance Imaging of Healthy and Diseased Brain Networks
An important aspect of neuroscience is to characterize the underlying connectivity patterns of the human brain (i.e., human connectomics). Over the past few years, researchers have demonstrated that by combining a variety of different neuroimaging technologies (e.g., structural MRI, diffusion MRI an...
I tiakina i:
| Ngā kaituhi matua: | , |
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| Hōputu: | Online |
| Reo: | Ingarihi |
| I whakaputaina: |
Frontiers Media SA
2021
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| Ngā marau: | |
| Urunga tuihono: | 18190 |
| Ngā Tūtohu: |
Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!
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| _version_ | 1869516278391111680 |
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| author | Yong He Alan Evans |
| author_browse | Alan Evans Yong He |
| author_facet | Yong He Alan Evans |
| author_sort | Yong He |
| collection | Directory of Open Access Books |
| description | An important aspect of neuroscience is to characterize the underlying connectivity patterns of the human brain (i.e., human connectomics). Over the past few years, researchers have demonstrated that by combining a variety of different neuroimaging technologies (e.g., structural MRI, diffusion MRI and functional MRI) with sophisticated analytic strategies such as graph theory, it is possible to noninvasively map the patterns of structural and functional connectivity of human whole-brain networks. With these novel approaches, many studies have shown that human brain networks have nonrandom properties such as modularity, small-worldness and highly connected hubs. Importantly, these quantifiable network properties change with age, learning and disease. Moreover, there is growing evidence for behavioral and genetic correlates. Network analysis of neuroimaging data is opening up a new avenue of research into the understanding of the organizational principles of the brain that will be of interest for all basic scientists and clinical researchers. Such approaches are powerful but there are a number of challenging issues when extracting reliable brain networks from various imaging modalities and analyzing the topological properties, e.g., definitions of network nodes and edges and reproducibility of network analysis. We assembled contributions related to the state-of-the-art methodologies of brain connectivity and the applications involving development, aging and neuropsychiatric disorders such as Alzheimer’s disease, schizophrenia, attention deficit hyperactivity disorder and mood and anxiety disorders. It is anticipated that the articles in this Research Topic will provide a greater range and depth of provision for the field of imaging connectomics. |
| format | Online |
| id | doab-20.500.12854ir-52566 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | Frontiers Media SA |
| publisherStr | Frontiers Media SA |
| record_format | ojs |
| spelling | doab-20.500.12854ir-525662024-04-05T12:35:36Z Magnetic Resonance Imaging of Healthy and Diseased Brain Networks Yong He Alan Evans RC321-571 Q1-390 connectomics connectivity graph theory MRI Small-world thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAN Neurosciences An important aspect of neuroscience is to characterize the underlying connectivity patterns of the human brain (i.e., human connectomics). Over the past few years, researchers have demonstrated that by combining a variety of different neuroimaging technologies (e.g., structural MRI, diffusion MRI and functional MRI) with sophisticated analytic strategies such as graph theory, it is possible to noninvasively map the patterns of structural and functional connectivity of human whole-brain networks. With these novel approaches, many studies have shown that human brain networks have nonrandom properties such as modularity, small-worldness and highly connected hubs. Importantly, these quantifiable network properties change with age, learning and disease. Moreover, there is growing evidence for behavioral and genetic correlates. Network analysis of neuroimaging data is opening up a new avenue of research into the understanding of the organizational principles of the brain that will be of interest for all basic scientists and clinical researchers. Such approaches are powerful but there are a number of challenging issues when extracting reliable brain networks from various imaging modalities and analyzing the topological properties, e.g., definitions of network nodes and edges and reproducibility of network analysis. We assembled contributions related to the state-of-the-art methodologies of brain connectivity and the applications involving development, aging and neuropsychiatric disorders such as Alzheimer’s disease, schizophrenia, attention deficit hyperactivity disorder and mood and anxiety disorders. It is anticipated that the articles in this Research Topic will provide a greater range and depth of provision for the field of imaging connectomics. 2021-02-11T18:32:34Z 2021-02-11T18:32:34Z 2016-01-19 14:05:46 2015 book 18190 16648714 9782889194353 https://directory.doabooks.org/handle/20.500.12854/52566 eng Frontiers Research Topics image/jpeg Attribution 4.0 International http://www.frontiersin.org/books/Magnetic_Resonance_Imaging_of_Healthy_and_Diseased_Brain_Networks/452 http://journal.frontiersin.org/researchtopic/948/magnetic-resonance-imaging-of-healthy-and-diseased-brain-networks Frontiers Media SA 10.3389/978-2-88919-435-3 10.3389/978-2-88919-435-3 bf5ce210-e72e-4860-ba9b-c305640ff3ae 9782889194353 365 open access |
| spellingShingle | RC321-571 Q1-390 connectomics connectivity graph theory MRI Small-world thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAN Neurosciences Yong He Alan Evans Magnetic Resonance Imaging of Healthy and Diseased Brain Networks |
| title | Magnetic Resonance Imaging of Healthy and Diseased Brain Networks |
| title_full | Magnetic Resonance Imaging of Healthy and Diseased Brain Networks |
| title_fullStr | Magnetic Resonance Imaging of Healthy and Diseased Brain Networks |
| title_full_unstemmed | Magnetic Resonance Imaging of Healthy and Diseased Brain Networks |
| title_short | Magnetic Resonance Imaging of Healthy and Diseased Brain Networks |
| title_sort | magnetic resonance imaging of healthy and diseased brain networks |
| topic | RC321-571 Q1-390 connectomics connectivity graph theory MRI Small-world thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAN Neurosciences |
| topic_facet | RC321-571 Q1-390 connectomics connectivity graph theory MRI Small-world thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAN Neurosciences |
| url | 18190 |
| work_keys_str_mv | AT yonghe magneticresonanceimagingofhealthyanddiseasedbrainnetworks AT alanevans magneticresonanceimagingofhealthyanddiseasedbrainnetworks |