The expanding horizons of network neuroscience: From description to prediction and control
The field of network neuroscience has emerged as a natural framework for the study of the brain and has been increasingly applied across divergent problems in neuroscience. From a disciplinary perspective, network neuroscience originally emerged as a formal integration of graph theory (from mathemat...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-09-01
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| Series: | NeuroImage |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1053811922003743 |
| _version_ | 1818114837553610752 |
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| author | Pragya Srivastava Panagiotis Fotiadis Linden Parkes Dani S. Bassett |
| author_facet | Pragya Srivastava Panagiotis Fotiadis Linden Parkes Dani S. Bassett |
| author_sort | Pragya Srivastava |
| collection | DOAJ |
| description | The field of network neuroscience has emerged as a natural framework for the study of the brain and has been increasingly applied across divergent problems in neuroscience. From a disciplinary perspective, network neuroscience originally emerged as a formal integration of graph theory (from mathematics) and neuroscience (from biology). This early integration afforded marked utility in describing the interconnected nature of neural units, both structurally and functionally, and underscored the relevance of that interconnection for cognition and behavior. But since its inception, the field has not remained static in its methodological composition. Instead, it has grown to use increasingly advanced graph-theoretic tools and to bring in several other disciplinary perspectives—including machine learning and systems engineering—that have proven complementary. In doing so, the problem space amenable to the discipline has expanded markedly. In this review, we discuss three distinct flavors of investigation in state-of-the-art network neuroscience: (i) descriptive network neuroscience, (ii) predictive network neuroscience, and (iii) a perturbative network neuroscience that draws on recent advances in network control theory. In considering each area, we provide a brief summary of the approaches, discuss the nature of the insights obtained, and highlight future directions. |
| first_indexed | 2024-12-11T03:57:04Z |
| format | Article |
| id | doaj.art-b51db9736cc74695ba5eb269e18b9522 |
| institution | Directory Open Access Journal |
| issn | 1095-9572 |
| language | English |
| last_indexed | 2024-12-11T03:57:04Z |
| publishDate | 2022-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | NeuroImage |
| spelling | doaj.art-b51db9736cc74695ba5eb269e18b95222022-12-22T01:21:46ZengElsevierNeuroImage1095-95722022-09-01258119250The expanding horizons of network neuroscience: From description to prediction and controlPragya Srivastava0Panagiotis Fotiadis1Linden Parkes2Dani S. Bassett3Department of Bioengineering, University of Pennsylvania, Philadelphia PA 19104, USADepartment of Bioengineering, University of Pennsylvania, Philadelphia PA 19104, USA; Department of Neuroscience, University of Pennsylvania, Philadelphia PA 19104, USADepartment of Bioengineering, University of Pennsylvania, Philadelphia PA 19104, USADepartment of Bioengineering, University of Pennsylvania, Philadelphia PA 19104, USA; Department of Physics & Astronomy, University of Pennsylvania, Philadelphia PA 19104, USA; Department of Electrical & Systems Engineering, University of Pennsylvania, Philadelphia PA 19104, USA; Department of Neurology, University of Pennsylvania, Philadelphia PA 19104, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia PA 19104, USA; Santa Fe Institute, Santa Fe NM 87501, USA; Corresponding author at: Department of Bioengineering, University of Pennsylvania, Philadelphia PA 19104, USA.The field of network neuroscience has emerged as a natural framework for the study of the brain and has been increasingly applied across divergent problems in neuroscience. From a disciplinary perspective, network neuroscience originally emerged as a formal integration of graph theory (from mathematics) and neuroscience (from biology). This early integration afforded marked utility in describing the interconnected nature of neural units, both structurally and functionally, and underscored the relevance of that interconnection for cognition and behavior. But since its inception, the field has not remained static in its methodological composition. Instead, it has grown to use increasingly advanced graph-theoretic tools and to bring in several other disciplinary perspectives—including machine learning and systems engineering—that have proven complementary. In doing so, the problem space amenable to the discipline has expanded markedly. In this review, we discuss three distinct flavors of investigation in state-of-the-art network neuroscience: (i) descriptive network neuroscience, (ii) predictive network neuroscience, and (iii) a perturbative network neuroscience that draws on recent advances in network control theory. In considering each area, we provide a brief summary of the approaches, discuss the nature of the insights obtained, and highlight future directions.http://www.sciencedirect.com/science/article/pii/S1053811922003743Descriptive network neurosciencePredictive network neurosciencePerturbative network neuroscienceControl theory for brain networks |
| spellingShingle | Pragya Srivastava Panagiotis Fotiadis Linden Parkes Dani S. Bassett The expanding horizons of network neuroscience: From description to prediction and control NeuroImage Descriptive network neuroscience Predictive network neuroscience Perturbative network neuroscience Control theory for brain networks |
| title | The expanding horizons of network neuroscience: From description to prediction and control |
| title_full | The expanding horizons of network neuroscience: From description to prediction and control |
| title_fullStr | The expanding horizons of network neuroscience: From description to prediction and control |
| title_full_unstemmed | The expanding horizons of network neuroscience: From description to prediction and control |
| title_short | The expanding horizons of network neuroscience: From description to prediction and control |
| title_sort | expanding horizons of network neuroscience from description to prediction and control |
| topic | Descriptive network neuroscience Predictive network neuroscience Perturbative network neuroscience Control theory for brain networks |
| url | http://www.sciencedirect.com/science/article/pii/S1053811922003743 |
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