Competition Model of Attention and Memory

注意力和记忆力的竞争模型

基本信息

批准号：
7690311
负责人：
MARY C POTTER
金额：
$ 27.93万
依托单位：
MASSACHUSETTS INSTITUTE OF TECHNOLOGY
依托单位国家：
美国
项目类别：
财政年份：
1992
资助国家：
美国
起止时间：
1992-08-01 至 2011-11-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7690311
关键词：
Accident and Emergency department Accidents Accounting Address Air Attention Automobile Driving Behavioral Biological Neural Networks Blindness Blinking Cities Collaborations Complex Computer Simulation Conscious Crime Cues Data Detection Disease Electroencephalography Emergency Situation Environment Event Eye Follow-Up Studies Investigation Letters Life Light Link Location Mediating Medical Memory Modeling Monitor Pattern Performance Process Reading Regulation Relative (related person)Reporting Research Research Personnel Resources Series Short-Term Memory Signal Transduction Sorting - Cell Movement Specific qualifier value Spottings Stimulus Stream Structure Symptoms Testing Visual Visual Fields Visual Pathways Visual attention Visual system structure improved magnocellular memory encoding neuroimaging parvocellular research study response trafficking

项目摘要

DESCRIPTION (provided by applicant): The overall aim of this proposal is to understand and model the processes that underlie the formation of conscious, reportable memories of otherwise fleeting visual representations. When we are looking for something, we can pick out that target surprisingly quickly when our eyes light on it. This is shown by presenting items one after the other at rates of 10 or even 20 a second using rapid serial visual presentation (RSVP). Such experiments with sequences of letters, words, or pictures have shown that the first target is easy to spot, but then it is strikingly difficult to detect a second target for the next half second (500 ms), an effect called an attentional blink. A complex sequence of processes occurs in that 500 ms, starting with detection of the first target, followed by a brief period of enhanced attention called transient attention which rapidly draws attentional resources to the location of the target. After this initial burst of attention, the blink occurs, making it very difficult to spot a new target anywhere in the visual field for 200-500 ms afterwards. Surprisingly, this blink is entirely eliminated by presenting an unbroken stream of targets. Thus a string of targets keeps attention engaged, but if there is a gap in the targets, attention is switched off. This effect suggests that there is a struggle between top down and bottom up control for attention. To understand these dynamics, a computational model of the temporal control of attention is explored in collaboration with B. Wyble. The eSTST model produces predictions that are tested with a series of 18 experiments aimed at exploring the competitive regulation of attention in several domains, including single streams of characters, spatial arrays, repetitions, words, pictures, and sentence reading. Computational modeling of the sort described here makes potentially informative links with disorders of attention because the model relates behavioral phenomena to neurally plausible structures. As a result, the model's account of attentional control can be related to anatomically specified structures in neuroimaging studies, as well as to temporally specified brainwave signals in EEG studies. The attentional processes and their limits that we propose to study have broad importance for many practical situations in modern life in which the visual environment changes rapidly, including city driving, air traffic control, and response to medical emergencies.

描述（由申请人提供）：该提案的总体目的是理解和建模是形成有意识的，可报告的回忆的过程。当我们寻找东西时，当我们的眼睛对它发光时，我们可以迅速挑选出该目标。通过使用快速串行视觉呈现（RSVP）以10甚至20的速度向一个接一个的项目呈现，这表明了这一点。使用字母，单词或图片序列的实验表明，第一个目标很容易发现，但是很难检测到下半秒（500毫秒）的第二个目标，这种效果称为注意眨眼。从检测第一个目标开始，在500毫秒内发生了复杂的过程序列，然后是一个短暂的加强注意力，称为瞬态注意力，迅速将注意力资源吸引到目标位置。经过最初的关注，眨眼就会发生，因此在200-500毫秒之后，很难在视野中的任何地方发现一个新目标。令人惊讶的是，通过提出一系列目标流，完全消除了这种眨眼。因此，一连串的目标可以使注意力吸引，但是如果目标存在差距，请关注注意力。这种效果表明，自上而下和自下而上的控制以吸引注意力。为了了解这些动力，与B. Wyble合作探索了关注时间控制的计算模型。 ESTST模型产生了通过一系列18个实验进行测试的预测，旨在探索几个领域的竞争性调节，包括单个字符，空间阵列，重复，单词，图片和句子阅读。此处描述的那种计算建模与关注障碍的潜在信息联系，因为该模型将行为现象与神经合理的结构联系起来。结果，该模型对注意力控制的描述可能与神经成像研究中的解剖学结构以及脑电图研究中的时间指定的脑电波信号有关。我们建议研究的注意力过程及其局限性对于现代生活中许多实际情况至关重要，在这些情况下，视觉环境迅速变化，包括城市驾驶，空中交通管制以及对医疗紧急情况的反应。