Toward Affirmation of Recovery of Deeply Embedded Autobiographical Memory with Background Music and Identification of an EEG Biomarker in Combination with EDA Signal Using Wearable Sensors
{"title":"Toward Affirmation of Recovery of Deeply Embedded Autobiographical Memory with Background Music and Identification of an EEG Biomarker in Combination with EDA Signal Using Wearable Sensors","authors":"Rupak Kumar Das, N. Imtiaz, Arshia A. Khan","doi":"10.3390/ctn6040026","DOIUrl":null,"url":null,"abstract":"There is no disputing the role that background music plays in memory recall. Music has the power to activate the brain and trigger deeply ingrained memories. For dementia patients, background music is a common therapy because of this. Previous studies used music to recall lyrics, series of words, and long- and short-term memories. In this research, electroencephalogram (EEG) and electrodermal activity (EDA) data are collected from 40 healthy participants using wearable sensors during nine music sessions (three happy, three sad, and three neutral). A post-study survey is given to all participants after each piece of music to know if they recalled any autobiographical memories. The main objective is to find an EEG biomarker using the collected qualitative and quantitative data for autobiographical memory recall. The study finds that for all four EEG channels, alpha power rises considerably (on average 16.2%) during the memory “recall” scenario (F3: p = 0.0066, F7: p = 0.0386, F4: p = 0.0023, and F8: p = 0.0288) compared to the “no-recall” situation. Beta power also increased significantly for two channels (F3: p = 0.0100 and F4: p = 0.0210) but not for others (F7: p = 0.6792 and F8: p = 0.0814). Additionally, the phasic standard deviation (p = 0.0260), phasic max (p = 0.0011), phasic energy (p = 0.0478), tonic min (p = 0.0092), tonic standard deviation (p = 0.0171), and phasic energy (p = 0.0478) are significantly different for the EDA signal. The authors conclude by interpreting increased alpha power (8–12 Hz) as a biomarker for autobiographical memory recall.","PeriodicalId":242430,"journal":{"name":"Clinical and Translational Neuroscience","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical and Translational Neuroscience","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/ctn6040026","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
There is no disputing the role that background music plays in memory recall. Music has the power to activate the brain and trigger deeply ingrained memories. For dementia patients, background music is a common therapy because of this. Previous studies used music to recall lyrics, series of words, and long- and short-term memories. In this research, electroencephalogram (EEG) and electrodermal activity (EDA) data are collected from 40 healthy participants using wearable sensors during nine music sessions (three happy, three sad, and three neutral). A post-study survey is given to all participants after each piece of music to know if they recalled any autobiographical memories. The main objective is to find an EEG biomarker using the collected qualitative and quantitative data for autobiographical memory recall. The study finds that for all four EEG channels, alpha power rises considerably (on average 16.2%) during the memory “recall” scenario (F3: p = 0.0066, F7: p = 0.0386, F4: p = 0.0023, and F8: p = 0.0288) compared to the “no-recall” situation. Beta power also increased significantly for two channels (F3: p = 0.0100 and F4: p = 0.0210) but not for others (F7: p = 0.6792 and F8: p = 0.0814). Additionally, the phasic standard deviation (p = 0.0260), phasic max (p = 0.0011), phasic energy (p = 0.0478), tonic min (p = 0.0092), tonic standard deviation (p = 0.0171), and phasic energy (p = 0.0478) are significantly different for the EDA signal. The authors conclude by interpreting increased alpha power (8–12 Hz) as a biomarker for autobiographical memory recall.
背景音乐在记忆中的作用是毋庸置疑的。音乐有激活大脑和触发根深蒂固的记忆的力量。因此,对痴呆症患者来说,背景音乐是一种常见的治疗方法。以前的研究使用音乐来回忆歌词、一系列单词以及长期和短期记忆。在这项研究中,使用可穿戴传感器收集了40名健康参与者在9场音乐(3场快乐音乐、3场悲伤音乐和3场中性音乐)期间的脑电图(EEG)和皮电活动(EDA)数据。在每一段音乐之后,研究人员对所有参与者进行了一项研究后调查,以了解他们是否回忆起了任何自传体记忆。主要目的是利用收集到的自传体记忆的定性和定量数据寻找脑电图生物标志物。研究发现,在记忆“回忆”场景中(F3: p = 0.0066, F7: p = 0.0386, F4: p = 0.0023, F8: p = 0.0288),与“不回忆”情况相比,在所有四个脑电图通道中,α功率显著上升(平均16.2%)。两个通道的Beta功率也显著增加(F3: p = 0.0100和F4: p = 0.0210),但其他通道没有(F7: p = 0.6792和F8: p = 0.0814)。此外,EDA信号的相位标准差(p = 0.0260)、相位最大值(p = 0.0011)、相位能量(p = 0.0478)、强音最小值(p = 0.0092)、强音标准差(p = 0.0171)和相位能量(p = 0.0478)存在显著差异。作者的结论是,增加的阿尔法能量(8-12赫兹)是自传体记忆回忆的生物标志物。