Capacity and Allocation across Sensory and Short-Term Memories.

Q2 Medicine Vision (Switzerland) Pub Date : 2022-03-01 DOI:10.3390/vision6010015
Shaoying Wang, Srimant P Tripathy, Haluk Öğmen
{"title":"Capacity and Allocation across Sensory and Short-Term Memories.","authors":"Shaoying Wang,&nbsp;Srimant P Tripathy,&nbsp;Haluk Öğmen","doi":"10.3390/vision6010015","DOIUrl":null,"url":null,"abstract":"<p><p>Human memory consists of sensory memory (SM), short-term memory (STM), and long-term memory (LTM). SM enables a large capacity, but decays rapidly. STM has limited capacity, but lasts longer. The traditional view of these memory systems resembles a leaky hourglass, the large top and bottom portions representing the large capacities of SM and LTM, whereas the narrow portion in the middle represents the limited capacity of STM. The \"leak\" in the top part of the hourglass depicts the rapid decay of the contents of SM. However, recently, it was shown that major bottlenecks for motion processing exist prior to STM, and the \"leaky hourglass\" model was replaced by a \"leaky flask\" model with a narrower top part to capture bottlenecks prior to STM. The leaky flask model was based on data from one study, and the first goal of the current paper was to test if the leaky flask model would generalize by using a different set of data. The second goal of the paper was to explore various block diagram models for memory systems and determine the one best supported by the data. We expressed these block diagram models in terms of statistical mixture models and, by using the Bayesian information criterion (BIC), found that a model with four components, viz., SM, attention, STM, and guessing, provided the best fit to our data. In summary, we generalized previous findings about early qualitative and quantitative bottlenecks, as expressed in the leaky flask model and showed that a four-process model can provide a good explanation for how visual information is processed and stored in memory.</p>","PeriodicalId":36586,"journal":{"name":"Vision (Switzerland)","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8955927/pdf/","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Vision (Switzerland)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/vision6010015","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 1

Abstract

Human memory consists of sensory memory (SM), short-term memory (STM), and long-term memory (LTM). SM enables a large capacity, but decays rapidly. STM has limited capacity, but lasts longer. The traditional view of these memory systems resembles a leaky hourglass, the large top and bottom portions representing the large capacities of SM and LTM, whereas the narrow portion in the middle represents the limited capacity of STM. The "leak" in the top part of the hourglass depicts the rapid decay of the contents of SM. However, recently, it was shown that major bottlenecks for motion processing exist prior to STM, and the "leaky hourglass" model was replaced by a "leaky flask" model with a narrower top part to capture bottlenecks prior to STM. The leaky flask model was based on data from one study, and the first goal of the current paper was to test if the leaky flask model would generalize by using a different set of data. The second goal of the paper was to explore various block diagram models for memory systems and determine the one best supported by the data. We expressed these block diagram models in terms of statistical mixture models and, by using the Bayesian information criterion (BIC), found that a model with four components, viz., SM, attention, STM, and guessing, provided the best fit to our data. In summary, we generalized previous findings about early qualitative and quantitative bottlenecks, as expressed in the leaky flask model and showed that a four-process model can provide a good explanation for how visual information is processed and stored in memory.

Abstract Image

Abstract Image

Abstract Image

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
感觉记忆和短期记忆的容量和分配。
人类的记忆包括感觉记忆(SM)、短期记忆(STM)和长期记忆(LTM)。SM容量大,但衰减快。STM容量有限,但持续时间更长。这些存储系统的传统观点就像一个漏漏的沙漏,顶部和底部的大部分代表SM和LTM的大容量,而中间的窄部分代表STM的有限容量。沙漏顶部的“泄漏”描述了SM含量的快速衰减。然而,最近有研究表明,运动处理的主要瓶颈在STM之前就已经存在,因此将“漏漏沙漏”模型替换为顶部较窄的“漏漏烧瓶”模型,以捕捉STM之前的瓶颈。漏烧瓶模型基于一项研究的数据,本文的第一个目标是测试漏烧瓶模型是否可以通过使用不同的数据集进行推广。本文的第二个目标是探索存储系统的各种方框图模型,并确定数据最支持的一个。我们用统计混合模型来表达这些框图模型,并使用贝叶斯信息准则(BIC),发现一个包含四个组成部分的模型,即SM、注意力、STM和猜测,最适合我们的数据。综上所述,我们总结了先前关于早期定性和定量瓶颈的发现,如漏烧瓶模型所表达的,并表明四过程模型可以很好地解释视觉信息是如何被加工和存储在记忆中的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Vision (Switzerland)
Vision (Switzerland) Health Professions-Optometry
CiteScore
2.30
自引率
0.00%
发文量
62
审稿时长
11 weeks
期刊最新文献
Optical Bench Evaluation of a Novel, Hydrophobic, Acrylic, One-Piece, Polyfocal Intraocular Lens with a "Zig-Zag" L-Loop Haptic Design. Optimal Timing for Intraocular Pressure Measurement Following Phacoemulsification Cataract Surgery: A Systematic Review and a Meta-Analysis. Corneal Endothelial Microscopy: Does a Manual Recognition of the Endothelial Cells Help the Morphometric Analysis Compared to a Fully Automatic Approach? Combined Epiretinal Proliferation and Internal Limiting Membrane Inverted Flap for the Treatment of Large Macular Holes. Comparison of Four Methods for Measuring Heterophoria and Accommodative Convergence over Accommodation Ratio.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1