MARC 主機 00000nam a2200469 i 4500
001 978-3-319-32285-8
003 DE-He213
005 20161102100647.0
006 m o d
007 cr nn 008maaau
008 160512s2016 gw s 0 eng d
020 9783319322858|q(electronic bk.)
020 9783319322841|q(paper)
024 7 10.1007/978-3-319-32285-8|2doi
040 GP|cGP|erda
041 0 eng
050 4 RC386.6.E86
072 7 PBWH|2bicssc
072 7 MAT003000|2bisacsh
082 04 612.813|223
100 1 Kolossa, Antonio,|eauthor
245 10 Computational modeling of neural activities for
statistical inference /|cby Antonio Kolossa
264 1 Cham :|bSpringer International Publishing :|bImprint:
Springer,|c2016
300 1 online resource (xxiv, 127 pages) :|billustrations,
digital ;|c24 cm
336 text|btxt|2rdacontent
337 computer|bc|2rdamedia
338 online resource|bcr|2rdacarrier
347 text file|bPDF|2rda
505 0 Basic Principles of ERP Research, Surprise, and
Probability Estimation -- Introduction to Model Estimation
and Selection Methods -- A New Theory of Trial-by-Trial
P300 Amplitude Fluctuations -- Bayesian Inference and the
Urn-Ball Task -- Summary and Outlook
520 This authored monograph supplies empirical evidence for
the Bayesian brain hypothesis by modeling event-related
potentials (ERP) of the human electroencephalogram (EEG)
during successive trials in cognitive tasks. The employed
observer models are useful to compute probability
distributions over observable events and hidden states,
depending on which are present in the respective tasks.
Bayesian model selection is then used to choose the model
which best explains the ERP amplitude fluctuations. Thus,
this book constitutes a decisive step towards a better
understanding of the neural coding and computing of
probabilities following Bayesian rules. The target
audience primarily comprises research experts in the field
of computational neurosciences, but the book may also be
beneficial for graduate students who want to specialize in
this field
650 0 Evoked potentials (Electrophysiology)|xStatistical methods
650 14 Mathematics
650 24 Mathematical Models of Cognitive Processes and Neural
Networks
650 24 Biomedical Engineering
650 24 Neurosciences
650 24 Physiological, Cellular and Medical Topics
650 24 Simulation and Modeling
710 2 SpringerLink (Online service)
773 0 |tSpringer eBooks
856 40 |uhttps://dx.doi.org/10.1007/978-3-319-32285-8
912 Springer|b110507134615
