کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6026256 1580905 2014 7 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Changing Zaire to Congo: The fate of no-longer relevant mnemonic information
ترجمه فارسی عنوان
تغییر زئیر به کنگو: سرنوشت اطلاعات مربوط به مننژیکی مرتبط نیست
موضوعات مرتبط
علوم زیستی و بیوفناوری علم عصب شناسی علوم اعصاب شناختی
چکیده انگلیسی
In an ever-changing world there is constant pressure on revising long-term memory, such when people or countries change name. What happens to the old, pre-existing information? One possibility is that old associations gradually are weakened and eventually lost. Alternatively, old and no longer relevant information may still be an integral part of memory traces. To test the hypothesis that old mnemonic information still becomes activated when people correctly retrieve new, currently relevant information, brain activity was measured with fMRI while participants performed a cued-retrieval task. Paired associates (symbol-sound and symbol-face pairs) were first learned during two days. Half of the associations were then updated during the next two days, followed by fMRI scanning on day 5 and also 18 months later. As expected, retrieval reactivated sensory cortex related to the most recently learned association (visual cortex for symbol-face pairs, auditory cortex for symbol-sound pairs). Critically, retrieval also reactivated sensory cortex related to the no-longer relevant associate. Eighteen months later, only non-updated symbol-face associations were intact. Intriguingly, a subset of the updated associations was now treated as though the original association had taken over, in that memory performance was significantly worse than chance and that activity in sensory cortex for the original but not the updated associate correlated (negatively) with performance. Moreover, the degree of “residual” reactivation during day 5 inversely predicted memory performance 18 months later. Thus, updating of long-term memory involves adding new information to already existing networks, in which old information can stay resilient for a long time.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: NeuroImage - Volume 101, 1 November 2014, Pages 1-7
نویسندگان
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