Literature DB >> 29608936

Entrainment to the CIECAM02 and CIELAB colour appearance models in the human cortex.

Andrew Thwaites1, Cai Wingfield2, Eric Wieser3, Andrew Soltan4, William D Marslen-Wilson5, Ian Nimmo-Smith6.   

Abstract

In human visual processing, information from the visual field passes through numerous transformations before perceptual attributes such as colour are derived. The sequence of transforms involved in constructing perceptions of colour can be approximated by colour appearance models such as the CIE (2002) colour appearance model, abbreviated as CIECAM02. In this study, we test the plausibility of CIECAM02 as a model of colour processing by looking for evidence of its cortical entrainment. The CIECAM02 model predicts that colour is split in to two opposing chromatic components, red-green and cyan-yellow (termed CIECAM02-a and CIECAM02-b respectively), and an achromatic component (termed CIECAM02-A). Entrainment of cortical activity to the outputs of these components was estimated using measurements of electro- and magnetoencephalographic (EMEG) activity, recorded while healthy subjects watched videos of dots changing colour. We find entrainment to chromatic component CIECAM02-a at approximately 35 ms latency bilaterally in occipital lobe regions, and entrainment to achromatic component CIECAM02-A at approximately 75 ms latency, also bilaterally in occipital regions. For comparison, transforms from a less physiologically plausible model (CIELAB) were also tested, with no significant entrainment found.
Copyright © 2018 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  CIECAM02; CIELAB; Colour perception; Entrainment; Magnetoencephalography; Model expression

Mesh:

Year:  2018        PMID: 29608936     DOI: 10.1016/j.visres.2018.01.011

Source DB:  PubMed          Journal:  Vision Res        ISSN: 0042-6989            Impact factor:   1.886


  4 in total

1.  A visual object segmentation algorithm with spatial and temporal coherence inspired by the architecture of the visual cortex.

Authors:  Juan A Ramirez-Quintana; Raul Rangel-Gonzalez; Mario I Chacon-Murguia; Graciela Ramirez-Alonso
Journal:  Cogn Process       Date:  2021-11-15

2.  Rapidly and exactly determining postharvest dry soybean seed quality based on machine vision technology.

Authors:  Ping Lin; Li Xiaoli; Du Li; Shanchao Jiang; Zhiyong Zou; Qun Lu; Yongming Chen
Journal:  Sci Rep       Date:  2019-11-20       Impact factor: 4.379

3.  Fluctuating environmental light limits number of surfaces visually recognizable by colour.

Authors:  David H Foster
Journal:  Sci Rep       Date:  2021-01-22       Impact factor: 4.379

4.  Colour constancy failures expected in colourful environments.

Authors:  David H Foster; Adam Reeves
Journal:  Proc Biol Sci       Date:  2022-01-26       Impact factor: 5.349

  4 in total

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