000			04230nam a22004335i 4500
999			_c387161 _d387161
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003			ES-MaUEC
005			20230211163144.0
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007			cr nn 008mamaa
008			220601s2010 sz | s |||| 0|eng d
020			_a9783031016448
024	7		_a10.1007/978-3-031-01644-8 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQP376 _b2010 EB
100	1		_aDe Vico Fallani, Fabrizio _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686756
245	1	4	_aThe Graph Theoretical Approach in Brain Functional Networks : _bTheory and Applications _cby Fabrizio Fallani, Fabio Babiloni
250			_a1st edition 2010
264		1	_aCham _bSpringer International Publishing _c2010
300			_a1 recurso en línea (XII, 84 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 -- Brain Functional Connectivity -- Graph Theory -- High-Resolution EEG -- Cortical Networks in Spinal Cord Injured Patients -- Cortical Networks During a Lifelike Memory Task -- Application to Time-varying Cortical Networks -- Conclusions.
520			_aThe present book illustrates the theoretical aspects of several methodologies related to the possibility of i) enhancing the poor spatial information of the electroencephalographic (EEG) activity on the scalp and giving a measure of the electrical activity on the cortical surface. ii) estimating the directional influences between any given pair of channels in a multivariate dataset. iii) modeling the brain networks as graphs. The possible applications are discussed in three different experimental designs regarding i) the study of pathological conditions during a motor task, ii) the study of memory processes during a cognitive task iii) the study of the instantaneous dynamics throughout the evolution of a motor task in physiological conditions. The main outcome from all those studies indicates clearly that the performance of cognitive and motor tasks as well as the presence of neural diseases can affect the brain network topology. This evidence gives the power of reflecting cerebral "states" or "traits" to the mathematical indexes derived from the graph theory. In particular, the observed structural changes could critically depend on patterns of synchronization and desynchronization - i.e. the dynamic binding of neural assemblies - as also suggested by a wide range of previous electrophysiological studies. Moreover, the fact that these patterns occur at multiple frequencies support the evidence that brain functional networks contain multiple frequency channels along which information is transmitted. The graph theoretical approach represents an effective means to evaluate the functional connectivity patterns obtained from scalp EEG signals. The possibility to describe the complex brain networks sub-serving different functions in humans by means of "numbers" is a promising tool toward the generation of a better understanding of the brain functions. Table of Contents: Introduction / Brain Functional Connectivity / Graph Theory / High-Resolution EEG / Cortical Networks in Spinal Cord Injured Patients / Cortical Networks During a Lifelike Memory Task / Application to Time-varying Cortical Networks / Conclusions.
988			_aSynthesis Collection of Technology_2010
650		7	_2embne _9146336 _aGrafos, Teoría de
650		7	_2embne _9678664 _aRedes neuronales artificiales
650		7	_2embne _9139534 _aElectroencefalografía _x Modelos matemáticos
700	1		_aBabiloni, Fabio _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686757
776	0	8	_iPrinted edition: _z9783031005169
776	0	8	_iPrinted edition: _z9783031027727
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-01644-8 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b02/2023 _dz _esc _zSI