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007			cr nn nnnaamaa
008			190104s2019 gw | o |||| 0|eng d
020			_a9783030036881
024	7		_a10.1007/978-3-030-03688-1 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aBF311 _b2019 EB
100	1		_aTurner, Brandon M., _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9674073 _d1985-
245	1	0	_aJoint Models of Neural and Behavioral Data / _cBrandon M. Turner, Birte U. Forstmann, Mark Steyvers.
250			_aFirst edition 2019
264		1	_aCham _bSpringer International Publishing : _bImprint: Springer _c2019
300			_a recurso en línea (XIII, 109 páginas) _b29 ilustraciones, 25 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_atext file _bPDF
490	0		_aComputational Approaches to Cognition and Perception _x2510-1889
505	0		_aChapter 1. Motivation -- Chapter 2. A Tutorial on Joint Modeling -- Chapter 3. Assessing Model Performance with Generalization Tests -- Chapter 4. Applications -- Chapter 5. Future Directions -- Chapter 6. Other Approaches. .
520	3		_aThis book presents a flexible Bayesian framework for combining neural and cognitive models. Traditionally, studies in cognition and cognitive sciences have been done by either observing behavior (e.g., response times, percentage correct, etc.) or by observing neural activity (e.g., the BOLD response). These two types of observations have traditionally supported two separate lines of study, which are led by two different cognitive modelers. Joining neuroimaging and computational modeling in a single hierarchical framework allows the neural data to influence the parameters of the cognitive model and allows behavioral data to constrain the neural model. This Bayesian approach can be used to reveal interactions between behavioral and neural parameters, and ultimately, between neural activity and cognitive mechanisms. Chapters demonstrate the utility of this Bayesian model with a variety of applications, and feature a tutorial chapter where the methods can be applied to an example problem. The book also discusses other joint modeling approaches and future directions. Joint Models of Neural and Behavioral Data will be of interest to advanced graduate students and postdoctoral candidates in an academic setting as well as researchers in the fields of cognitive psychology and neuroscience.
988			_aSpringer_Psychology_2019
650		7	_aCiencia cognitiva _2embne _9406963
650		7	_aProcesos cognitivos _2embne _9413145
700			_aForstmann, Birte U. _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _993469
700	1		_aSteyvers, Mark _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9674120
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783030036874
776	0	8	_iPrinted edition: _z9783030036898
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-03688-1 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b06/2020 _dz _eo _zSI