Quantitative Neuroscience: Models, Algorithms, Diagnostics, and Therapeutic Applications
Advances in the field of signal processing, nonlinear dynamics, statistics, and optimization theory, combined with marked improvement in instrumenta tion and development of computers systems, have made it possible to apply the power of mathematics to the task of understanding the human brain. This...
Gespeichert in:
| Weitere Verfasser: | , , , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Boston, MA
Springer US
2004
|
| Schriftenreihe: | Biocomputing
2 |
| Schlagworte: | |
| Online-Zugang: | FHI01 BTU01 Volltext |
| Zusammenfassung: | Advances in the field of signal processing, nonlinear dynamics, statistics, and optimization theory, combined with marked improvement in instrumenta tion and development of computers systems, have made it possible to apply the power of mathematics to the task of understanding the human brain. This verita ble revolution already has resulted in widespread availability of high resolution neuroimaging devices in clinical as well as research settings. Breakthroughs in functional imaging are not far behind. Mathematical tech niques developed for the study of complex nonlinear systems and chaos already are being used to explore the complex nonlinear dynamics of human brain phys iology. Global optimization is being applied to data mining expeditions in an effort to find knowledge in the vast amount of information being generated by neuroimaging and neurophysiological investigations. These breakthroughs in the ability to obtain, store and analyze large datasets offer, for the first time, exciting opportunities to explore the mechanisms underlying normal brain func tion as well as the affects of diseases such as epilepsy, sleep disorders, movement disorders, and cognitive disorders that affect millions of people every year. Ap plication of these powerful tools to the study of the human brain requires, by necessity, collaboration among scientists, engineers, neurobiologists and clini cians. Each discipline brings to the table unique knowledge, unique approaches to problem solving, and a unique language |
| Beschreibung: | 1 Online-Ressource (XI, 262 p. 61 illus) |
| ISBN: | 9781461302254 |
| DOI: | 10.1007/978-1-4613-0225-4 |
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| 520 | |a Advances in the field of signal processing, nonlinear dynamics, statistics, and optimization theory, combined with marked improvement in instrumenta tion and development of computers systems, have made it possible to apply the power of mathematics to the task of understanding the human brain. This verita ble revolution already has resulted in widespread availability of high resolution neuroimaging devices in clinical as well as research settings. Breakthroughs in functional imaging are not far behind. Mathematical tech niques developed for the study of complex nonlinear systems and chaos already are being used to explore the complex nonlinear dynamics of human brain phys iology. Global optimization is being applied to data mining expeditions in an effort to find knowledge in the vast amount of information being generated by neuroimaging and neurophysiological investigations. These breakthroughs in the ability to obtain, store and analyze large datasets offer, for the first time, exciting opportunities to explore the mechanisms underlying normal brain func tion as well as the affects of diseases such as epilepsy, sleep disorders, movement disorders, and cognitive disorders that affect millions of people every year. Ap plication of these powerful tools to the study of the human brain requires, by necessity, collaboration among scientists, engineers, neurobiologists and clini cians. Each discipline brings to the table unique knowledge, unique approaches to problem solving, and a unique language | ||
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| spelling | Quantitative Neuroscience Models, Algorithms, Diagnostics, and Therapeutic Applications edited by P. M. Pardalos, J. C. Sackellares, P. R. Carney, L. D. Iasemidis Boston, MA Springer US 2004 1 Online-Ressource (XI, 262 p. 61 illus) txt rdacontent c rdamedia cr rdacarrier Biocomputing 2 Advances in the field of signal processing, nonlinear dynamics, statistics, and optimization theory, combined with marked improvement in instrumenta tion and development of computers systems, have made it possible to apply the power of mathematics to the task of understanding the human brain. This verita ble revolution already has resulted in widespread availability of high resolution neuroimaging devices in clinical as well as research settings. Breakthroughs in functional imaging are not far behind. Mathematical tech niques developed for the study of complex nonlinear systems and chaos already are being used to explore the complex nonlinear dynamics of human brain phys iology. Global optimization is being applied to data mining expeditions in an effort to find knowledge in the vast amount of information being generated by neuroimaging and neurophysiological investigations. These breakthroughs in the ability to obtain, store and analyze large datasets offer, for the first time, exciting opportunities to explore the mechanisms underlying normal brain func tion as well as the affects of diseases such as epilepsy, sleep disorders, movement disorders, and cognitive disorders that affect millions of people every year. Ap plication of these powerful tools to the study of the human brain requires, by necessity, collaboration among scientists, engineers, neurobiologists and clini cians. Each discipline brings to the table unique knowledge, unique approaches to problem solving, and a unique language Engineering Biomedical Engineering Optimization Algorithms Mathematical Modeling and Industrial Mathematics Mathematical models Mathematical optimization Biomedical engineering Pardalos, P. M. edt Sackellares, J. C. edt Carney, P. R. edt Iasemidis, L. D. edt Erscheint auch als Druck-Ausgabe 9781461379515 https://doi.org/10.1007/978-1-4613-0225-4 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Quantitative Neuroscience Models, Algorithms, Diagnostics, and Therapeutic Applications Engineering Biomedical Engineering Optimization Algorithms Mathematical Modeling and Industrial Mathematics Mathematical models Mathematical optimization Biomedical engineering |
| title | Quantitative Neuroscience Models, Algorithms, Diagnostics, and Therapeutic Applications |
| title_auth | Quantitative Neuroscience Models, Algorithms, Diagnostics, and Therapeutic Applications |
| title_exact_search | Quantitative Neuroscience Models, Algorithms, Diagnostics, and Therapeutic Applications |
| title_full | Quantitative Neuroscience Models, Algorithms, Diagnostics, and Therapeutic Applications edited by P. M. Pardalos, J. C. Sackellares, P. R. Carney, L. D. Iasemidis |
| title_fullStr | Quantitative Neuroscience Models, Algorithms, Diagnostics, and Therapeutic Applications edited by P. M. Pardalos, J. C. Sackellares, P. R. Carney, L. D. Iasemidis |
| title_full_unstemmed | Quantitative Neuroscience Models, Algorithms, Diagnostics, and Therapeutic Applications edited by P. M. Pardalos, J. C. Sackellares, P. R. Carney, L. D. Iasemidis |
| title_short | Quantitative Neuroscience |
| title_sort | quantitative neuroscience models algorithms diagnostics and therapeutic applications |
| title_sub | Models, Algorithms, Diagnostics, and Therapeutic Applications |
| topic | Engineering Biomedical Engineering Optimization Algorithms Mathematical Modeling and Industrial Mathematics Mathematical models Mathematical optimization Biomedical engineering |
| topic_facet | Engineering Biomedical Engineering Optimization Algorithms Mathematical Modeling and Industrial Mathematics Mathematical models Mathematical optimization Biomedical engineering |
| url | https://doi.org/10.1007/978-1-4613-0225-4 |
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