Methods for analysis of brain connectivity: An IFCN-sponsored review
•There are a variety of technologies valuable for exploring human brain connectivity.•The main aspects of anatomical, functional and effective connectivity are described.•A multimodality approach can be useful to evaluate the human brain connectome. The goal of this paper is to examine existing meth...
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| Published in: | Clinical neurophysiology Vol. 130; no. 10; pp. 1833 - 1858 |
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| Main Authors: | , , , , , , , , , , , , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Netherlands
Elsevier B.V
01.10.2019
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| Subjects: | |
| ISSN: | 1388-2457, 1872-8952, 1872-8952 |
| Online Access: | Get full text |
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| Abstract | •There are a variety of technologies valuable for exploring human brain connectivity.•The main aspects of anatomical, functional and effective connectivity are described.•A multimodality approach can be useful to evaluate the human brain connectome.
The goal of this paper is to examine existing methods to study the “Human Brain Connectome” with a specific focus on the neurophysiological ones. In recent years, a new approach has been developed to evaluate the anatomical and functional organization of the human brain: the aim of this promising multimodality effort is to identify and classify neuronal networks with a number of neurobiologically meaningful and easily computable measures to create its connectome. By defining anatomical and functional connections of brain regions on the same map through an integrated approach, comprising both modern neurophysiological and neuroimaging (i.e. flow/metabolic) brain-mapping techniques, network analysis becomes a powerful tool for exploring structural–functional connectivity mechanisms and for revealing etiological relationships that link connectivity abnormalities to neuropsychiatric disorders. Following a recent IFCN-endorsed meeting, a panel of international experts was selected to produce this current state-of-art document, which covers the available knowledge on anatomical and functional connectivity, including the most commonly used structural and functional MRI, EEG, MEG and non-invasive brain stimulation techniques and measures of local and global brain connectivity. |
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| AbstractList | The goal of this paper is to examine existing methods to study the "Human Brain Connectome" with a specific focus on the neurophysiological ones. In recent years, a new approach has been developed to evaluate the anatomical and functional organization of the human brain: the aim of this promising multimodality effort is to identify and classify neuronal networks with a number of neurobiologically meaningful and easily computable measures to create its connectome. By defining anatomical and functional connections of brain regions on the same map through an integrated approach, comprising both modern neurophysiological and neuroimaging (i.e. flow/metabolic) brain-mapping techniques, network analysis becomes a powerful tool for exploring structural-functional connectivity mechanisms and for revealing etiological relationships that link connectivity abnormalities to neuropsychiatric disorders. Following a recent IFCN-endorsed meeting, a panel of international experts was selected to produce this current state-of-art document, which covers the available knowledge on anatomical and functional connectivity, including the most commonly used structural and functional MRI, EEG, MEG and non-invasive brain stimulation techniques and measures of local and global brain connectivity. •There are a variety of technologies valuable for exploring human brain connectivity.•The main aspects of anatomical, functional and effective connectivity are described.•A multimodality approach can be useful to evaluate the human brain connectome. The goal of this paper is to examine existing methods to study the “Human Brain Connectome” with a specific focus on the neurophysiological ones. In recent years, a new approach has been developed to evaluate the anatomical and functional organization of the human brain: the aim of this promising multimodality effort is to identify and classify neuronal networks with a number of neurobiologically meaningful and easily computable measures to create its connectome. By defining anatomical and functional connections of brain regions on the same map through an integrated approach, comprising both modern neurophysiological and neuroimaging (i.e. flow/metabolic) brain-mapping techniques, network analysis becomes a powerful tool for exploring structural–functional connectivity mechanisms and for revealing etiological relationships that link connectivity abnormalities to neuropsychiatric disorders. Following a recent IFCN-endorsed meeting, a panel of international experts was selected to produce this current state-of-art document, which covers the available knowledge on anatomical and functional connectivity, including the most commonly used structural and functional MRI, EEG, MEG and non-invasive brain stimulation techniques and measures of local and global brain connectivity. The goal of this paper is to examine existing methods to study the "Human Brain Connectome" with a specific focus on the neurophysiological ones. In recent years, a new approach has been developed to evaluate the anatomical and functional organization of the human brain: the aim of this promising multimodality effort is to identify and classify neuronal networks with a number of neurobiologically meaningful and easily computable measures to create its connectome. By defining anatomical and functional connections of brain regions on the same map through an integrated approach, comprising both modern neurophysiological and neuroimaging (i.e. flow/metabolic) brain-mapping techniques, network analysis becomes a powerful tool for exploring structural-functional connectivity mechanisms and for revealing etiological relationships that link connectivity abnormalities to neuropsychiatric disorders. Following a recent IFCN-endorsed meeting, a panel of international experts was selected to produce this current state-of-art document, which covers the available knowledge on anatomical and functional connectivity, including the most commonly used structural and functional MRI, EEG, MEG and non-invasive brain stimulation techniques and measures of local and global brain connectivity.The goal of this paper is to examine existing methods to study the "Human Brain Connectome" with a specific focus on the neurophysiological ones. In recent years, a new approach has been developed to evaluate the anatomical and functional organization of the human brain: the aim of this promising multimodality effort is to identify and classify neuronal networks with a number of neurobiologically meaningful and easily computable measures to create its connectome. By defining anatomical and functional connections of brain regions on the same map through an integrated approach, comprising both modern neurophysiological and neuroimaging (i.e. flow/metabolic) brain-mapping techniques, network analysis becomes a powerful tool for exploring structural-functional connectivity mechanisms and for revealing etiological relationships that link connectivity abnormalities to neuropsychiatric disorders. Following a recent IFCN-endorsed meeting, a panel of international experts was selected to produce this current state-of-art document, which covers the available knowledge on anatomical and functional connectivity, including the most commonly used structural and functional MRI, EEG, MEG and non-invasive brain stimulation techniques and measures of local and global brain connectivity. |
| Author | Ferreri, F. Nitsche, M.A. Shirota, Y. Hallett, M. Gerloff, C. Vecchio, F. Ugawa, Y. Bertini, G. Rossini, P.M. Ziemann, U. Pestilli, F. Bentivoglio, M. Tesoriero, C. Di Iorio, R. Miraglia, F. Rosanova, M. Ilmoniemi, R.J. |
| Author_xml | – sequence: 1 givenname: P.M. surname: Rossini fullname: Rossini, P.M. organization: Institute of Neurology, Area of Neuroscience, Catholic University of Sacred Heart, Rome, Italy – sequence: 2 givenname: R. surname: Di Iorio fullname: Di Iorio, R. email: r.diiorio@live.it organization: Neurology Unit, IRCCS Polyclinic A. Gemelli Foundation, Rome, Italy – sequence: 3 givenname: M. surname: Bentivoglio fullname: Bentivoglio, M. organization: Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona, Verona, Italy – sequence: 4 givenname: G. surname: Bertini fullname: Bertini, G. organization: Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona, Verona, Italy – sequence: 5 givenname: F. surname: Ferreri fullname: Ferreri, F. organization: Department of Neuroscience, University of Padua, Padua, Italy – sequence: 6 givenname: C. surname: Gerloff fullname: Gerloff, C. organization: Department of Neurology, University Medical Center Hamburg-Eppendorf, Germany – sequence: 7 givenname: R.J. surname: Ilmoniemi fullname: Ilmoniemi, R.J. organization: Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland – sequence: 8 givenname: F. surname: Miraglia fullname: Miraglia, F. organization: Institute of Neurology, Area of Neuroscience, Catholic University of Sacred Heart, Rome, Italy – sequence: 9 givenname: M.A. surname: Nitsche fullname: Nitsche, M.A. organization: Leibniz Research Centre for Working Environment and Human Factors, Department of Psychology and Neurosciences, Dortmund, Germany – sequence: 10 givenname: F. surname: Pestilli fullname: Pestilli, F. organization: Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA – sequence: 11 givenname: M. surname: Rosanova fullname: Rosanova, M. organization: Department of Biomedical and Clinical Sciences “L. Sacco”, University of Milan, Milan, Italy – sequence: 12 givenname: Y. surname: Shirota fullname: Shirota, Y. organization: Department of Neurology, The University of Tokyo, Tokyo, Japan – sequence: 13 givenname: C. surname: Tesoriero fullname: Tesoriero, C. organization: Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona, Verona, Italy – sequence: 14 givenname: Y. surname: Ugawa fullname: Ugawa, Y. organization: Department of Neuro-Regeneraion, Fukushima Medical University, Fukushima, Japan – sequence: 15 givenname: F. surname: Vecchio fullname: Vecchio, F. organization: Brain Connectivity Lab, IRCCS San Raffaele Pisana, Rome, Italy – sequence: 16 givenname: U. surname: Ziemann fullname: Ziemann, U. organization: Department of Neurology & Stroke and Hertie-Institute for Clinical Brain Research, Eberhard-Karls University of Tübingen, Tübingen, Germany – sequence: 17 givenname: M. surname: Hallett fullname: Hallett, M. organization: Human Motor Control Section, National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD, USA |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/31401492$$D View this record in MEDLINE/PubMed |
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| Snippet | •There are a variety of technologies valuable for exploring human brain connectivity.•The main aspects of anatomical, functional and effective connectivity are... The goal of this paper is to examine existing methods to study the "Human Brain Connectome" with a specific focus on the neurophysiological ones. In recent... |
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| SubjectTerms | Anatomical connectivity Brain - diagnostic imaging Brain - physiology Brain connectivity Connectome - methods Connectomics EEG Effective connectivity Electroencephalography - methods fMRI Functional connectivity Human brain connectome Humans Magnetic Resonance Imaging - methods Magnetoencephalography - methods MEG Nerve Net - diagnostic imaging Nerve Net - physiology Neural Pathways - diagnostic imaging Neural Pathways - physiology Non-invasive brain stimulation TMS-EEG Transcranial Magnetic Stimulation - methods |
| Title | Methods for analysis of brain connectivity: An IFCN-sponsored review |
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