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ocn795124311 |
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OCoLC |
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20240909213021.0 |
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m o d |
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cr cnu---unuuu |
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120611s2011 enka ob 001 0 eng d |
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|a N$T
|b eng
|e pn
|c N$T
|d CDX
|d E7B
|d YDXCP
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|d OCLCQ
|d OCLCF
|d OCLCA
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|d OCLCQ
|d STBDS
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|d WYU
|d OCLCO
|d OCLCA
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| 019 |
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|a 817088166
|a 819504709
|a 821643724
|a 1063970640
|a 1086935736
|a 1124407941
|a 1298456087
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| 020 |
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|a 9780199874767
|q (electronic bk.)
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|a 019987476X
|q (electronic bk.)
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|a 1280691662
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|a 9780199918379
|q (ebook)
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|a 0199918376
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|z 9780195387247
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|z 0195387244
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| 035 |
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|a (OCoLC)795124311
|z (OCoLC)817088166
|z (OCoLC)819504709
|z (OCoLC)821643724
|z (OCoLC)1063970640
|z (OCoLC)1086935736
|z (OCoLC)1124407941
|z (OCoLC)1298456087
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| 050 |
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4 |
|a QP357.5
|b .S46 2011eb
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| 072 |
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7 |
|a MED
|x 057000
|2 bisacsh
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| 072 |
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7 |
|a PSY
|x 020000
|2 bisacsh
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| 049 |
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|a HCDD
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| 245 |
0 |
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|a Sensory cue integration /
|c edited by Julia Trommershäuser, Konrad Körding, and Michael S. Landy.
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| 260 |
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|a Oxford ;
|a New York :
|b Oxford University Press,
|c 2011.
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| 300 |
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|a 1 online resource (xiii, 446 pages) :
|b color illustrations
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| 336 |
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|a text
|b txt
|2 rdacontent
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| 337 |
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|a computer
|b c
|2 rdamedia
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| 338 |
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|a online resource
|b cr
|2 rdacarrier
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| 490 |
1 |
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|a Computational neuroscience
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| 504 |
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|a Includes bibliographical references and index.
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| 505 |
0 |
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|t Ideal-observer models of cue integration /
|r Michael S. Landy, Martin S. Banks and David C. Knill --
|t Casual inference in sensorimotor learning and control /
|r Kunlin Wei and Konrad P. Kording --
|t The role of generative knowledge in object perception /
|r Peter W. Battaglia, Daniel Kersten and Paul Schrater --
|t Generative probabilistic modeling: understanding casual sensorimotor integration /
|r Sethu Vijayakumar, Timothy Hospedales and Adrian Haith --
|t Modeling cue integration in cluttered environments /
|r Maneesh Sahani and Louise Whiteley --
|t Recruitment of new visual cues for perceptual appearance /
|r Benjamin T. Backus --
|t Combining image signals before three-dimensional reconstruction: the intrinsic constraint model of cue integration /
|r Fulvio Domini and Carrado Caudek --
|t Cue combination: beyond optimality /
|r Pedro Rosas and Felix A. Wichmann --
|t Priors and learning in cue integration /
|r Anna Seydell, David C. Knill and Julia Trommershauser --
|t Multisensory integration and calibration in adults and children /
|r David Burr, Paola Binda and Monica Gori --
|t The Statistical relationship between depth, visual cues, and human perception /
|r Martin S. Banks, Johannes Burge and Robert T. Held --
|t Multisensory perception: from integration to remapping /
|r Marc O. Ernst and Massimiliano Di Luca --
|t Humans multisensory perception, from integration to segregation, follows Bayesian inference /
|r Ladan Shams and Ulrik Beierholm --
|t Cues and pseudocues in texture and shape perception /
|r Michael S. Landy [and others] --
|t Optimality principles apply to a broad range of information integration problems in perception and action /
|r Melchi M. Mitchel, Anne-Marie Brouwer, Robert A. Jacobs and David C. Knill --
|t Self-motion perception: multisensory integration in extrastriate visual cortex /
|r Christopher R. Fetsch, Yong Gu, Gregory C. DeAngelis, and Dora E. Angelaki --
|t Probing neural correlates of cue integration /
|r Christopher A. Buneo, Gregory Apker and Ying Shi --
|t Computational models of multisensory integration in the cat superior colliculus /
|r Benjamin A. Rowland, Barry E. Stein and Terrence R. Stanford --
|t Decoding the cortical representation of depth /
|r Andrew E. Welchman --
|t Dynamic cue combination in distributional population code networks /
|r Rama Natarajan and Richard S. Zemel --
|t A neural implementation of optimal cue integration /
|r Wei Ji Ma, Jeff Beck and Alexandre Pouget --
|t Contextual modulations of visual receptive fields: a Bayesian perspective /
|r Sophie Deneve and Timm Lochmann.
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| 588 |
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|a Print version record.
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| 520 |
8 |
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|a This text is concerned with sensory cue integration both within and between sensory modalities, and focuses on the emerging way of thinking about cue combination in terms of uncertainty.
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| 650 |
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|a Computational neuroscience.
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| 650 |
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0 |
|a Cognitive neuroscience.
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| 650 |
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0 |
|a Senses and sensation.
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| 650 |
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|a Neural networks (Computer science)
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| 650 |
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7 |
|a simulation.
|2 aat
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| 650 |
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7 |
|a MEDICAL
|x Neuroscience.
|2 bisacsh
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| 650 |
|
7 |
|a PSYCHOLOGY
|x Neuropsychology.
|2 bisacsh
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| 650 |
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7 |
|a Neural networks (Computer science)
|2 fast
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| 650 |
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7 |
|a Cognitive neuroscience
|2 fast
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| 650 |
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7 |
|a Computational neuroscience
|2 fast
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| 650 |
|
7 |
|a Senses and sensation
|2 fast
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| 700 |
1 |
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|a Trommershauser, Julia.
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| 700 |
1 |
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|a Kording, Konrad.
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| 700 |
1 |
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|a Landy, Michael S.
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| 758 |
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|i has work:
|a Sensory cue integration (Text)
|1 https://id.oclc.org/worldcat/entity/E39PCGFDW4wTcFp7xMkhwxRPKm
|4 https://id.oclc.org/worldcat/ontology/hasWork
|
| 776 |
0 |
8 |
|i Print version:
|t Sensory cue integration.
|d Oxford ; New York : Oxford University Press, 2011
|z 9780195387247
|w (DLC) 2010049048
|w (OCoLC)689548961
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| 830 |
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0 |
|a Computational neuroscience.
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| 856 |
4 |
0 |
|u https://holycross.idm.oclc.org/login?auth=cas&url=https://academic.oup.com/book/1603
|y Click for online access
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| 903 |
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|a OUP-SOEBA
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| 994 |
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|a 92
|b HCD
|