دانلود مقاله ISI انگلیسی شماره 71114
ترجمه فارسی عنوان مقاله

توزیع قدرت حافظه ذهنی: قدرت فهرست و تعصب واکنش

عنوان انگلیسی
The distribution of subjective memory strength: List strength and response bias
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
71114 2009 23 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Cognitive Psychology, Volume 59, Issue 4, December 2009, Pages 297–319

ترجمه کلمات کلیدی
حافظه اپیزودیک؛ مدل های ریاضی؛ اثرات آینه؛ رمزگذاری - بازشناسی حافظه - نظریه تشخیص سیگنال؛ استحکام
کلمات کلیدی انگلیسی
Episodic memory; Mathematical models; Mirror effects; Encoding; Recognition memory; Signal detection theory; Strength
پیش نمایش مقاله
پیش نمایش مقاله  توزیع قدرت حافظه ذهنی: قدرت فهرست و تعصب واکنش

چکیده انگلیسی

Models of recognition memory assume that memory decisions are based partially on the subjective strength of the test item. Models agree that the subjective strength of targets increases with additional time for encoding however the origin of the subjective strength of foils remains disputed. Under the fixed strength assumption the distribution of memory strength for foils is invariant across experimental manipulations of encoding. For example, the subjective strength of foils may depend solely on the pre-experimental history of the item, thus encoding manipulations have no impact. In contrast, under the differentiation assumption the subjective strength of foils depends on the nature of the traces stored in episodic memory. If those traces are well encoded, the subjective strength of foils will be lower than the case where noisy traces are stored (e.g., when targets received minimal encoding). The fixed strength and differentiation accounts are tested by measuring direct ratings of memory strength. In Experiments 1 and 2, item strength is varied via repetition and in Experiment 3 response bias is varied via the relative proportion of targets on the test list. For all experiments empirical distributions of memory strength were obtained and compared to the distributions predicted by the two accounts. The differentiation assumption provides the most parsimonious account of the data.