Relating categorization to set summary statistics perception

被引:0
作者
Noam Khayat
Shaul Hochstein
机构
[1] Hebrew University,Life Sciences Institute and Edmond and Lily Safra Center (ELSC) for Brain Research
来源
Attention, Perception, & Psychophysics | 2019年 / 81卷
关键词
Categorization; Prototype; Boundary; Summary statistics; Ensemble; Mean; Range;
D O I
暂无
中图分类号
学科分类号
摘要
Two cognitive processes have been explored that compensate for the limited information that can be perceived and remembered at any given moment. The first parsimonious cognitive process is object categorization. We naturally relate objects to their category, assume they share relevant category properties, often disregarding irrelevant characteristics. Another scene organizing mechanism is representing aspects of the visual world in terms of summary statistics. Spreading attention over a group of objects with some similarity, one perceives an ensemble representation of the group. Without encoding detailed information of individuals, observers process summary data concerning the group, including set mean for various features (from circle size to face expression). Just as categorization may include/depend on prototype and intercategory boundaries, so set perception includes property mean and range. We now explore common features of these processes. We previously investigated summary perception of low-level features with a rapid serial visual presentation (RSVP) paradigm and found that participants perceive both the mean and range extremes of stimulus sets, automatically, implicitly, and on-the-fly, for each RSVP sequence, independently. We now use the same experimental paradigm to test category representation of high-level objects. We find participants perceive categorical characteristics better than they code individual elements. We relate category prototype to set mean and same/different category to in/out-of-range elements, defining a direct parallel between low-level set perception and high-level categorization. The implicit effects of mean or prototype and set or category boundaries are very similar. We suggest that object categorization may share perceptual-computational mechanisms with set summary statistics perception.
引用
收藏
页码:2850 / 2872
页数:22
相关论文
共 50 条
  • [31] PRED-LD: efficient imputation of GWAS summary statistics
    Georgios A. Manios
    Aikaterini Michailidi
    Panagiota I. Kontou
    Pantelis G. Bagos
    BMC Bioinformatics, 26 (1) : 107
  • [32] SumStatsRehab: an efficient algorithm for GWAS summary statistics assessment and restoration
    Mykyta Matushyn
    Madhuchanda Bose
    Abdallah Amr Mahmoud
    Lewis Cuthbertson
    Carlos Tello
    Karatuğ Ozan Bircan
    Andrew Terpolovsky
    Varuna Bamunusinghe
    Umar Khan
    Biljana Novković
    Manfred G. Grabherr
    Puya G. Yazdi
    BMC Bioinformatics, 23
  • [33] Convolutional Neural Networks as Summary Statistics for Approximate Bayesian Computation
    Akesson, Mattias
    Singh, Prashant
    Wrede, Fredrik
    Hellander, Andreas
    IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS, 2022, 19 (06) : 3353 - 3365
  • [34] How may the basal ganglia contribute to auditory categorization and speech perception?
    Lim, Sung-Joo
    Fiez, Julie A.
    Holt, Lori L.
    FRONTIERS IN NEUROSCIENCE, 2014, 8
  • [35] SumStatsRehab: an efficient algorithm for GWAS summary statistics assessment and restoration
    Matushyn, Mykyta
    Bose, Madhuchanda
    Mahmoud, Abdallah Amr
    Cuthbertson, Lewis
    Tello, Carlos
    Bircan, Karatug Ozan
    Terpolovsky, Andrew
    Bamunusinghe, Varuna
    Khan, Umar
    Novkovic, Biljana
    Grabherr, Manfred G.
    Yazdi, Puya G.
    BMC BIOINFORMATICS, 2022, 23 (01)
  • [36] Evaluating the estimation of genetic correlation and heritability using summary statistics
    Ju Zhang
    Fredrick R. Schumacher
    Molecular Genetics and Genomics, 2021, 296 : 1221 - 1234
  • [37] Evaluating the estimation of genetic correlation and heritability using summary statistics
    Zhang, Ju
    Schumacher, Fredrick R.
    MOLECULAR GENETICS AND GENOMICS, 2021, 296 (06) : 1221 - 1234
  • [38] The goldmine of GWAS summary statistics: a systematic review of methods and tools
    Kontou, Panagiota I.
    Bagos, Pantelis G.
    BIODATA MINING, 2024, 17 (01):
  • [39] Approximate Bayesian computation in controlled branching processes: the role of summary statistics
    Miguel González
    Rodrigo Martínez
    Carmen Minuesa
    Inés del Puerto
    Revista de la Real Academia de Ciencias Exactas, Físicas y Naturales. Serie A. Matemáticas, 2020, 114
  • [40] An evaluation of time series summary statistics as features for clinical prediction tasks
    Guo, Chonghui
    Lu, Menglin
    Chen, Jingfeng
    BMC MEDICAL INFORMATICS AND DECISION MAKING, 2020, 20 (01)