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008			230422s2008 sz | s |||| 0|eng d
020			_a9783031016226
024	7		_a10.1007/978-3-031-01622-6 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQP383.15 _b2008 EB
100	1		_aAstolfi, Laura _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9688205
245	1	0	_aEstimation of Cortical Connectivity in Humans : _bAdvanced Signal Processing Techniques _cby Laura Astolfi, Fabio Babiloni
250			_a1st edition 2008
264		1	_aCham _bSpringer International Publishing _c2008
300			_a1 recurso en línea (XVI, 93 páginas)
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aSynthesis Lectures on Biomedical Engineering _x1930-0336
505	0		_aIntroduction -- Estimation of the Effective Connectivity from Stationary Data by Structural Equation Modeling -- Estimation of the Functional Connectivity from Stationary Data by Multivariate Autoregressive Methods -- Estimation of Cortical Activity by the use of Realistic Head Modeling -- Application: Estimation of Connectivity from Movement-Related Potentials -- Application to High-Resolution EEG Recordings in a Cognitive Task (Stroop Test) -- Application to Data Related to the Intention of Limb Movements in Normal Subjects and in a Spinal Cord Injured Patient -- The Instantaneous Estimation of the Time-Varying Cortical Connectivity by Adaptive Multivariate Estimators -- Time-Varying Connectivity from Event-Related Potentials.
520			_aIn the last ten years many different brain imaging devices have conveyed a lot of information about the brain functioning in different experimental conditions. In every case, the biomedical engineers, together with mathematicians, physicists and physicians are called to elaborate the signals related to the brain activity in order to extract meaningful and robust information to correlate with the external behavior of the subjects. In such attempt, different signal processing tools used in telecommunications and other field of engineering or even social sciences have been adapted and re-used in the neuroscience field. The present book would like to offer a short presentation of several methods for the estimation of the cortical connectivity of the human brain. The methods here presented are relatively simply to implement, robust and can return valuable information about the causality of the activation of the different cortical areas in humans using non invasive electroencephalographic recordings. The knowledge of such signal processing tools will enrich the arsenal of the computational methods that a engineer or a mathematician could apply in the processing of brain signals. Table of Contents: Introduction / Estimation of the Effective Connectivity from Stationary Data by Structural Equation Modeling / Estimation of the Functional Connectivity from Stationary Data by Multivariate Autoregressive Methods / Estimation of Cortical Activity by the use of Realistic Head Modeling / Application: Estimation of Connectivity from Movement-Related Potentials / Application to High-Resolution EEG Recordings in a Cognitive Task (Stroop Test) / Application to Data Related to the Intention of Limb Movements in Normal Subjects and in a Spinal Cord Injured Patient / The Instantaneous Estimation of the Time-Varying Cortical Connectivity by Adaptive Multivariate Estimators / Time-Varying Connectivity from Event-Related Potentials.
988			_aSynthesis Collection of Technology_2008
650		7	_2embne _9141010 _aNeuropsicología
650		7	_2embne _9145032 _aCorteza cerebral
650		7	_2embne _9139534 _aElectroencefalografía
700	1		_aBabiloni, Fabio _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686757
776	0	8	_iPrinted edition: _z9783031004940
776	0	8	_iPrinted edition: _z9783031027505
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-01622-6 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b04/2023 _dz _eIG _zSI