Contributions of low- and high-level properties to neural processing of visual scenes in the human brain

被引:106
|
作者
Groen, Iris I. A. [1 ]
Silson, Edward H. [1 ]
Baker, Chris I. [1 ]
机构
[1] NIH, Lab Brain & Cognit, 10 Ctr Dr 10-3N228, Bethesda, MD 20892 USA
基金
美国国家卫生研究院;
关键词
natural scenes; functional magnetic resonance imaging; electro-encephalography; category-selectivity; retinotopy; image statistics; PARAHIPPOCAMPAL PLACE AREA; TIME-COURSE; IMAGE STATISTICS; DECISION-MAKING; REPRESENTATIONS; INFORMATION; CORTEX; CATEGORIZATION; RECOGNITION; SHAPE;
D O I
10.1098/rstb.2016.0102
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Visual scene analysis in humans has been characterized by the presence of regions in extrastriate cortex that are selectively responsive to scenes compared with objects or faces. While these regions have often been interpreted as representing high-level properties of scenes (e.g. category), they also exhibit substantial sensitivity to low-level (e.g. spatial frequency) and mid-level (e.g. spatial layout) properties, and it is unclear how these disparate findings can be united in a single framework. In this opinion piece, we suggest that this problem can be resolved by questioning the utility of the classical low- to high-level framework of visual perception for scene processing, and discuss why low-and mid-level properties may be particularly diagnostic for the behavioural goals specific to scene perception as compared to object recognition. In particular, we highlight the contributions of low-level vision to scene representation by reviewing (i) retinotopic biases and receptive field properties of scene-selective regions and (ii) the temporal dynamics of scene perception that demonstrate overlap of low-and mid-level feature representations with those of scene category. We discuss the relevance of these findings for scene perception and suggest a more expansive framework for visual scene analysis. This article is part of the themed issue 'Auditory and visual scene analysis'.
引用
收藏
页数:11
相关论文
共 50 条
  • [1] Neurophysiologic analyses of low- and high-level visual processing in Alzheimer disease
    Fernandez, Roberto
    Kavcic, Voyko
    Duffy, Charles J.
    NEUROLOGY, 2007, 68 (24) : 2066 - 2076
  • [2] Contributions of low- and high-level contextual mechanisms to human face perception
    Canoluk, Mehmet Umut
    Moors, Pieter
    Goffaux, Valerie
    PLOS ONE, 2023, 18 (05):
  • [3] Adaptation of neural responses to naturalistic visual categories in low- and high-level visual cortex
    Brands, Amber M.
    Flinker, Adeen
    Devore, Sasha
    Devinsky, Orrin
    Doyle, Werner
    Winawer, Jonathan
    Groen, Iris I. A.
    PERCEPTION, 2021, 50 (1_SUPPL) : 75 - 75
  • [4] Understanding Low- and High-Level Contributions to Fixation Prediction
    Kuemmerer, Matthias
    Wallis, Thomas S. A.
    Gatys, Leon A.
    Bethge, Matthias
    2017 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV), 2017, : 4799 - 4808
  • [5] Spatial Frequency Training Modulates Neural Face Processing: Learning Transfers from Low- to High-Level Visual Features
    Peters, Judith C.
    van den Boomen, Cartin
    Kemner, Chantal
    FRONTIERS IN HUMAN NEUROSCIENCE, 2017, 11
  • [6] Neurons in the human hippocampus and amygdala respond to both low- and high-level image properties
    Steinmetz, Peter N.
    Cabrales, Elaine
    Wilson, Michael S.
    Baker, Christopher P.
    Thorp, Christopher K.
    Smith, Kris A.
    Treiman, David M.
    JOURNAL OF NEUROPHYSIOLOGY, 2011, 105 (06) : 2874 - 2884
  • [7] Neural Correlates of Fixated Low- and High-level Scene Properties during Active Scene Viewing
    Henderson, John M.
    Goold, Jessica E.
    Choi, Wonil
    Hayes, Taylor R.
    JOURNAL OF COGNITIVE NEUROSCIENCE, 2020, 32 (10) : 2013 - 2023
  • [8] Detecting high-level and low-level properties in visual images and visual percepts
    Rouw, R
    Kosslyn, SM
    Hamel, R
    COGNITION, 1997, 63 (02) : 209 - 226
  • [9] Visual mismatch negativity (vMMN) for low- and high-level deviances: A control study
    Domonkos File
    Bálint File
    Flóra Bodnár
    István Sulykos
    Krisztina Kecskés-Kovács
    István Czigler
    Attention, Perception, & Psychophysics, 2017, 79 : 2153 - 2170
  • [10] Visual mismatch negativity (vMMN) for low- and high-level deviances: A control study
    File, Domonkos
    File, Balint
    Bodnar, Flora
    Sulykos, Istvan
    Kecskes-Kovacs, Krisztina
    Czigler, Istvan
    ATTENTION PERCEPTION & PSYCHOPHYSICS, 2017, 79 (07) : 2153 - 2170