Literature DB >> 20434327

Getting real-sensory processing of natural stimuli.

Wolfgang Einhäuser1, Peter König.   

Abstract

Normal sensory experience rarely presents us with isolated bars, gratings, or other stimuli that have shaped our knowledge of sensory representations. Instead, typical input adheres to certain statistical regularities, which make it 'natural' and cannot be adequately modeled by linear superposition of simple stimuli. Natural stimuli necessitate a paradigm shift with a focus on downstream processing. This shift currently follows three main lines: quantification of the information a downstream area can read out (decoding); describing a representation as the optimization of computational principles with respect to natural input (normative approach); understanding the sensory representation as optimal for the systems' tasks and intended actions (behavioral context). The interaction between representational levels, intermediate-level features, and bidirectional coupling through attention are key elements for sensory processing. 2010 Elsevier Ltd. All rights reserved.

Mesh:

Year:  2010        PMID: 20434327     DOI: 10.1016/j.conb.2010.03.010

Source DB:  PubMed          Journal:  Curr Opin Neurobiol        ISSN: 0959-4388            Impact factor:   6.627


  13 in total

1.  Visual categorization of natural movies by rats.

Authors:  Kasper Vinken; Ben Vermaercke; Hans P Op de Beeck
Journal:  J Neurosci       Date:  2014-08-06       Impact factor: 6.167

2.  Visual pattern discrimination by population retinal ganglion cells' activities during natural movie stimulation.

Authors:  Ying-Ying Zhang; Ru-Bin Wang; Xiao-Chuan Pan; Hai-Qing Gong; Pei-Ji Liang
Journal:  Cogn Neurodyn       Date:  2013-08-14       Impact factor: 5.082

3.  Distinct fMRI Responses to Self-Induced versus Stimulus Motion during Free Viewing in the Macaque.

Authors:  Brian E Russ; Takaaki Kaneko; Kadharbatcha S Saleem; Rebecca A Berman; David A Leopold
Journal:  J Neurosci       Date:  2016-09-14       Impact factor: 6.167

4.  A computational theory of visual receptive fields.

Authors:  Tony Lindeberg
Journal:  Biol Cybern       Date:  2013-11-07       Impact factor: 2.086

5.  Overt attention and context factors: the impact of repeated presentations, image type, and individual motivation.

Authors:  Kai Kaspar; Peter König
Journal:  PLoS One       Date:  2011-07-05       Impact factor: 3.240

6.  Modeling invariant object processing based on tight integration of simulated and empirical data in a Common Brain Space.

Authors:  Judith C Peters; Joel Reithler; Rainer Goebel
Journal:  Front Comput Neurosci       Date:  2012-03-09       Impact factor: 2.380

7.  Sparse coding can predict primary visual cortex receptive field changes induced by abnormal visual input.

Authors:  Jonathan J Hunt; Peter Dayan; Geoffrey J Goodhill
Journal:  PLoS Comput Biol       Date:  2013-05-09       Impact factor: 4.475

8.  Emotions' impact on viewing behavior under natural conditions.

Authors:  Kai Kaspar; Teresa-Maria Hloucal; Jürgen Kriz; Sonja Canzler; Ricardo Ramos Gameiro; Vanessa Krapp; Peter König
Journal:  PLoS One       Date:  2013-01-09       Impact factor: 3.240

9.  The impact of expert visual guidance on trainee visual search strategy, visual attention and motor skills.

Authors:  Daniel R Leff; David R C James; Felipe Orihuela-Espina; Ka-Wai Kwok; Loi Wah Sun; George Mylonas; Thanos Athanasiou; Ara W Darzi; Guang-Zhong Yang
Journal:  Front Hum Neurosci       Date:  2015-10-14       Impact factor: 3.169

10.  Phase synchrony facilitates binding and segmentation of natural images in a coupled neural oscillator network.

Authors:  Holger Finger; Peter König
Journal:  Front Comput Neurosci       Date:  2014-01-27       Impact factor: 2.380

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.