The impact of signal-to-noise ratio on contextual cueing in children and adults

被引:16
|
作者
Yang, Yingying [1 ]
Merrill, Edward C. [1 ]
机构
[1] Univ Alabama, Dept Psychol, Tuscaloosa, AL 35401 USA
关键词
Children; Contextual cueing; Signal-to-noise ratio; Animal silhouettes; Spatial learning; Implicit learning; SCHOOL-AGE-CHILDREN; WORKING-MEMORY; DEVELOPMENTAL DIFFERENCES; SPATIAL CONTEXT; LIFE-SPAN; VISUAL CONTEXT; YOUNG-ADULTS; IMPLICIT; ATTENTION; SEARCH;
D O I
10.1016/j.jecp.2014.12.005
中图分类号
B844 [发展心理学(人类心理学)];
学科分类号
040202 ;
摘要
Contextual cueing refers to a form of implicit spatial learning where participants incidentally learn to associate a target location with its repeated spatial context. Successful contextual learning produces an efficient visual search through familiar environments. Despite the fact that children exhibit the basic ability of implicit spatial learning, their general effectiveness in this form of learning can be compromised by other development-dependent factors. Learning to extract useful information (signal) in the presence of various amounts of irrelevant or distracting information (noise) characterizes one of the most important changes that occur with cognitive development. This research investigated whether signal-to-noise ratio (SIN) affects contextual cueing differently in children and adults. S/N was operationally defined as the ratio of repeated versus new displays encountered over time. Three ratio conditions were created: high (100%), medium (67%), and low (33%) conditions. Results suggested no difference in the acquisition of contextual learning effects in the high and medium conditions across three age groups (6- to 8-year-olds, 10- to 12-year-olds, and young adults). However, a significant developmental difference emerged in the low SIN condition. As predicted, adults exhibited significant contextual cueing effects, whereas older children showed marginally significant contextual cueing and younger children did not show cueing effects. Group differences in the ability to exhibit implicit contextual learning under low SIN conditions and the implications of this difference are discussed. (C) 2015 Elsevier Inc. All rights reserved.
引用
收藏
页码:65 / 83
页数:19
相关论文
共 50 条
  • [31] Signal-to-noise ratio in stretch processing
    Long, T.
    Wang, Y.
    Zeng, T.
    ELECTRONICS LETTERS, 2010, 46 (10) : 720 - 721
  • [32] SIGNAL-TO-NOISE RATIO OF RECORDED ECG
    KIRSNER, RLG
    MEDICAL & BIOLOGICAL ENGINEERING, 1972, 10 (01): : 111 - &
  • [33] SIGNAL-TO-NOISE RATIO IN AMPLITUDE QUANTIZERS
    HARIHARA.PR
    JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA, 1969, 45 (01): : 301 - &
  • [34] THE SIGNAL-TO-NOISE RATIO WITH DIODE DETECTION
    KHISHAM, A
    TELECOMMUNICATIONS AND RADIO ENGINEERING, 1989, 44 (07) : 63 - 66
  • [35] Measuring the signal-to-noise ratio of a neuron
    Czanner, Gabriela
    Sarma, Sridevi V.
    Ba, Demba
    Eden, Uri T.
    Wu, Wei
    Eskandar, Emad
    Lim, Hubert H.
    Temereanca, Simona
    Suzuki, Wendy A.
    Brown, Emery N.
    PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2015, 112 (23) : 7141 - 7146
  • [36] Signal-to-noise ratio in stochastic resonance
    Chattah, AK
    Briozzo, CB
    Osenda, O
    Caceres, MO
    MODERN PHYSICS LETTERS B, 1996, 10 (22): : 1085 - 1094
  • [37] SIGNAL-TO-NOISE RATIO IN AM RECEIVERS
    FUBINI, EG
    JOHNSON, DC
    PROCEEDINGS OF THE INSTITUTE OF RADIO ENGINEERS, 1948, 36 (12): : 1461 - 1466
  • [38] CONFIDENCE INTERVALS FOR THE SIGNAL-TO-NOISE RATIO AND DIFFERENCE OF SIGNAL-TO-NOISE RATIOS OF GAMMA DISTRIBUTIONS
    Thangjai, Warisa
    Niwitpong, Suparat
    ADVANCES AND APPLICATIONS IN MATHEMATICAL SCIENCES, 2019, 18 (06): : 503 - 520
  • [39] Comparing the trustworthiness of signal-to-noise ratio and peak signal-to-noise ratio in processing noisy partial discharge signals
    Najafipour, Abbas
    Babaee, Abbas
    Shahrtash, S. Mohammad
    IET SCIENCE MEASUREMENT & TECHNOLOGY, 2013, 7 (02) : 112 - 118
  • [40] Measurement of Signal-to-Noise Ratio and Signal-to-Noise and Distortion Ratio Using Histogram Test in Time Domain Analysis
    Jain, Manish
    Sharma, Prakash Chandra
    Tiwari, Pradeep Kumar
    Gupta, Rohit Kumar
    SMART SYSTEMS: INNOVATIONS IN COMPUTING (SSIC 2021), 2022, 235 : 403 - 410