4月(yuè)11日 Attentional Control and Biomarkers in Healthy Aging and Early Stage Alzheimer’s Disease

時(shí)間:2019-04-04浏覽:141設置

講座題目:Attentional Control and Biomarkers in Healthy Aging and Early Stage Alzheimer’s Disease

  

主講人(rén):Prof. David A. Balota , Washington University in St. Louis

主持人(rén)蒯曙光(guāng)研究員(yuán)

開始時(shí)間:2019-4-11 13:00-14:00

講座地址:中北(běi)校區(qū)俊秀樓107

主辦單位:科技處, 心理(lǐ)與認知科學學院,上海市腦(nǎo)功能基因組學重點實驗室

  

報告人(rén)簡介:

David A. Balota is a Professor at Department of Psychological and Brain Sciences, Washington University in St. Louis. Professor Balota works on issues related to visual word recognition, semantic memory, priming on implicit memory tests, and attention systems that modulate performance within each of these domains. He investigates these phenomena within young adults, older adults, and individuals who have dementing illnesses such as senile dementia of the Alzheimer's type.


報告内容簡介

Historically, additive factors logic has had an important influence on separating discrete stages of cognitive processing.  Quantitative models suggest that analyses of reaction time distributions of targeted variables are particularly informative regarding such stages.  Additive factors logic in memory scanning will be briefly reviewed and extended to the observation of additive effects of word frequency and stimulus degradation in lexical decision performance.  This latter pattern has important implications for current models of how words are recognized during reading tasks.  However, recent evidence indicates that this pattern of additivity in visual word recognition may be modulated by the presence of semantically related priming trials, and may also be modulated by cross trial carry over effects uncovered by linear mixed effects analyses.  Both issues are explored and the additive effects appear to remain.  Commonly used reaction time transformations are shown to influence the presence of additive or interactive effects in the same dataset by changing the shape of the underlying reaction time distributions.  Additive effects remain an important tool to uncovering the cognitive/neural architecture of human cognition.

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