Wein, Simon and Deco, Gustavo and Tome, Ana Maria and Goldhacker, Markus and Malloni, Wilhelm M. and Greenlee, Mark W. and Lang, Elmar W. (2021) Brain Connectivity Studies on Structure-Function Relationships: A Short Survey with an Emphasis on Machine Learning. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE, 2021: 5573740. ISSN 1687-5265, 1687-5273
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This short survey reviews the recent literature on the relationship between the brain structure and its functional dynamics. Imaging techniques such as diffusion tensor imaging (DTI) make it possible to reconstruct axonal fiber tracks and describe the structural connectivity (SC) between brain regions. By measuring fluctuations in neuronal activity, functional magnetic resonance imaging (fMRI) provides insights into the dynamics within this structural network. One key for a better understanding of brain mechanisms is to investigate how these fast dynamics emerge on a relatively stable structural backbone. So far, computational simulations and methods from graph theory have been mainly used for modeling this relationship. Machine learning techniques have already been established in neuroimaging for identifying functionally independent brain networks and classifying pathological brain states. This survey focuses on methods from machine learning, which contribute to our understanding of functional interactions between brain regions and their relation to the underlying anatomical substrate.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | INDEPENDENT COMPONENT ANALYSIS; GRAPH-THEORETICAL ANALYSIS; MULTIVARIATE TIME-SERIES; USER-FRIENDLY TOOLBOX; RESTING-STATE; HUMAN CONNECTOME; DEFAULT-MODE; FMRI DATA; GRANGER CAUSALITY; NETWORK DYNAMICS |
| Subjects: | 000 Computer science, information & general works > 004 Computer science 100 Philosophy & psychology > 150 Psychology 500 Science > 570 Life sciences 600 Technology > 600 Technology (Applied sciences) |
| Divisions: | Human Sciences > Institut für Psychologie > Lehrstuhl für Psychologie I (Allgemeine Psychologie I und Methodenlehre) - Prof. Dr. Mark W. Greenlee Biology, Preclinical Medicine > Institut für Biophysik und physikalische Biochemie > Prof. Dr. Elmar Lang |
| Depositing User: | Petra Gürster |
| Date Deposited: | 21 Dec 2022 05:40 |
| Last Modified: | 21 Dec 2022 05:40 |
| URI: | https://pred.uni-regensburg.de/id/eprint/46215 |
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