![]() ![]() As comparison performance is better when the overlap is relatively small, the large distance number pairs are easier to process because of the smaller overlap between the signals ( Dehaene, 2007). The numbers are stored as noisy signals, and the closer the two numbers on the ANS, the larger the overlap of the two respective signal distributions is. There are several explanations for this phenomenon termed the numerical distance effect.Īccording to the dominant model, numbers are stored on a continuous (analog) and noisy representation called the Analog Number System (ANS). In a symbolic number comparison task, performance is better (i.e., error rates are lower and reaction times are shorter) when the numerical distance is relatively large, e.g., comparing 1 vs. The Numerical Distance Effect and its Explanations It was found that the omitted number range (the distance between 3 and 7) was considered in the distance effect as 1, and not as 4, suggesting that the distance effect does not follow the values of the numbers predicted by the dominant explanation, but it follows the small-large property association predicted by the alternative explanations. To dissociate the two potential sources of the distance effect, in the present study, participants learned new artificial number digits only for the values between 1 and 3, and between 7 and 9, thus, leaving out the numbers between 4 and 6. In everyday number use, the value of the numbers and the association between the numbers and the small-large categories strongly correlate thus, the two explanations have the same predictions for the distance effect. According to alternative explanations, the distance effect may be rooted in the association between the numbers and the small-large categories, and performance is better when the numbers show relatively high differences in their strength of association with the small-large properties. According to the dominant explanation, the distance effect is rooted in a noisy representation, and performance is proportional to the size of the overlap between the noisy representations of the two values. In a comparison task, the larger the distance between the two numbers to be compared, the better the performance-a phenomenon termed as the numerical distance effect. 2Doctoral School of Psychology, ELTE Eötvös Loránd University, Budapest, Hungary. ![]() 1Department of Cognitive Psychology, Institute of Psychology, ELTE Eötvös Loránd University, Budapest, Hungary.Attila Krajcsi 1 * † and Petia Kojouharova 1,2 † ![]()
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