Neural Substrates for Early Data Reduction in Fast Vision: A Psychophysical Investigation

被引:0
|
作者
Castellotti, Serena [1 ,2 ]
Del Viva, Maria Michela [2 ]
机构
[1] Univ Pisa, Dept Translat Res New Technol Med & Surg, I-56126 Pisa, Italy
[2] Univ Florence, Dept Neurosci Psychol Drug Res & Child Hlth NEUROF, I-50135 Florence, Italy
基金
欧洲研究理事会;
关键词
fast vision; visual data reduction; early feature extraction; constrained maximum entropy; visual sketches; visual saliency; psychophysics; flicker adaptation; contrast sensitivity; magnocellular pathway; LATERAL GENICULATE-NUCLEUS; RESPONSE PROPERTIES; RECEPTIVE-FIELDS; GANGLION-CELLS; NEURONS; ADAPTATION; MOVEMENT; PARALLEL; MOTION; LGN;
D O I
10.3390/brainsci14080753
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
To ensure survival, the visual system must rapidly extract the most important elements from a large stream of information. This necessity clashes with the computational limitations of the human brain, so a strong early data reduction is required to efficiently process information in fast vision. A theoretical early vision model, recently developed to preserve maximum information using minimal computational resources, allows efficient image data reduction by extracting simplified sketches containing only optimally informative, salient features. Here, we investigate the neural substrates of this mechanism for optimal encoding of information, possibly located in early visual structures. We adopted a flicker adaptation paradigm, which has been demonstrated to specifically impair the contrast sensitivity of the magnocellular pathway. We compared flicker-induced contrast threshold changes in three different tasks. The results indicate that, after adapting to a uniform flickering field, thresholds for image discrimination using briefly presented sketches increase. Similar threshold elevations occur for motion discrimination, a task typically targeting the magnocellular system. Instead, contrast thresholds for orientation discrimination, a task typically targeting the parvocellular system, do not change with flicker adaptation. The computation performed by this early data reduction mechanism seems thus consistent with magnocellular processing.
引用
收藏
页数:14
相关论文
共 10 条
  • [1] Psychophysical investigation of ganglion cell loss in early glaucoma
    Spry, PGD
    Johnson, CA
    Mansberger, SL
    Cioffi, GA
    JOURNAL OF GLAUCOMA, 2005, 14 (01) : 11 - 19
  • [2] Vision-for-perception and vision-for-action: Which model is compatible with the available psychophysical and neuropsychological data?
    Schenk, Thomas
    Franz, Volker
    Bruno, Nicola
    VISION RESEARCH, 2011, 51 (08) : 812 - 818
  • [3] What shape are the neural response functions underlying opponent coding in face space? A psychophysical investigation
    Susilo, Tirta
    McKone, Elinor
    Edwards, Mark
    VISION RESEARCH, 2010, 50 (03) : 300 - 314
  • [4] Investigation of Neural Substrates of Erroneous Behavior in a Delayed-Response Task
    Chae, Soyoung
    Sohn, Jeong-Woo
    Kim, Sung-Phil
    ENEURO, 2022, 9 (02)
  • [5] A population-coding model of attention's influence on contrast response: Estimating neural effects from psychophysical data
    Pestilli, Franco
    Ling, Sam
    Carrasco, Marisa
    VISION RESEARCH, 2009, 49 (10) : 1144 - 1153
  • [6] Common (and multiple) neural substrates for static and dynamic motion after-effects: A rTMS investigation
    Campana, Gianluca
    Maniglia, Marcello
    Pavan, Andrea
    CORTEX, 2013, 49 (09) : 2590 - 2594
  • [7] Artificial Neural Network and Data Dimensionality Reduction Based on Machine Learning Methods for PMSM Model Order Reduction
    Raia, Maria Raluca
    Ruba, Mircea
    Nemes, Raul Octavian
    Martis, Claudia
    IEEE ACCESS, 2021, 9 : 102345 - 102354
  • [8] Reduction of a kinetic model for Na+ channel activation, and fast and slow inactivation within a neural or cardiac membrane
    Vaccaro, S. R.
    PHYSICAL REVIEW E, 2019, 99 (03)
  • [9] Investigation of Pig Activity Based on Video Data and Semi-Supervised Neural Networks
    Wutke, Martin
    Schmitt, Armin Otto
    Traulsen, Imke
    Gueltas, Mehmet
    AGRIENGINEERING, 2020, 2 (04): : 581 - 595
  • [10] Targeted dimensionality reduction enables reliable estimation of neural population coding accuracy from trial-limited data
    Heller, Charles R.
    David, Stephen, V
    PLOS ONE, 2022, 17 (07):