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020			_a9789813295230
024	7		_a10.1007/978-981-32-9523-0 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aRC386.5 _b2019 EB
100	1		_aHu, Dewen _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9673830
245	1	0	_aPattern Analysis of the Human Connectome _cby Dewen Hu, Ling-Li Zeng
250			_aFirst edition
264		1	_aSingapore _bSpringer International Publishing _c2019
300			_a1 recurso en línea (VIII, 258 páginas) _b86 ilustraciones, 81 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_atext file _bPDF
490	0		_aBiomedical and Life Sciences (Springer-11642)
505	0		_aIntroduction -- Multivariate pattern analysis of whole-brain functional connectivity in major depression -- Discriminative analysis of nonlinear functional connectivity in schizophrenia -- Predicting individual brain maturity using window-based dynamic functional connectivity -- Locally linear embedding of functional connectivity for classification -- Locally linear embedding of anatomical connectivity for classification -- Locality preserving projection of functional connectivity for regression -- Intrinsic discriminant analysis of functional connectivity for multi-class classification -- Sparse representation of dynamic functional connectivity in depression -- Low-rank learning of functional connectivity reveals neural traits of individual differences -- Multi-task learning of structural MRI for multi-site classification -- Deep discriminant auto-encoder network for multi-site fMRI classification.
520	3		_aThis book presents recent advances in pattern analysis of the human connectome. The human connectome, measured by magnetic resonance imaging at the macroscale, provides a comprehensive description of how brain regions are connected. Based on machine learning methods, multiviarate pattern analysis can directly decode psychological or cognitive states from brain connectivity patterns. Although there are a number of works with chapters on conventional human connectome encoding (brain-mapping), there are few resources on human connectome decoding (brain-reading). Focusing mainly on advances made over the past decade in the field of manifold learning, sparse coding, multi-task learning, and deep learning of the human connectome and applications, this book helps students and researchers gain an overall picture of pattern analysis of the human connectome. It also offers valuable insights for clinicians involved in the clinical diagnosis and treatment evaluation of neuropsychiatric disorders.
988			_aPrimersemestre_2020_BiomedLife
650		7	_2embne _9174342 _aCerebro _xEnfermedades _xDiagnóstico
700	1		_aZeng, Ling-Li _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9673831
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9789813295223
776	0	8	_iPrinted edition: _z9789813295247
776	0	8	_iPrinted edition: _z9789813295254
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-981-32-9523-0 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE _n0
998			_b05/2020 _dz _ea _zSI