{"title":"Exploring age-related functional brain changes during audio-visual integration tasks in early to mid-adulthood","authors":"Prerna Singh , Ayush Tripathi , Tapan Kumar Gandhi , Lalan Kumar","doi":"10.1016/j.neuri.2024.100172","DOIUrl":null,"url":null,"abstract":"<div><p>The seamless integration of visual and auditory information is a fundamental aspect of human cognition. Although age-related functional changes in Audio-Visual Integration (AVI) have been extensively explored in the past, thorough studies across various age groups remain insufficient. Previous studies have provided valuable insights into age-related AVI using EEG-based sensor data. However, these studies have been limited in their ability to capture spatial information related to brain source activation and their connectivity. To address these gaps, our study conducted a comprehensive audio-visual integration task with a specific focus on assessing the brain maturation effects in various age groups, particularly in early-mid adulthood. We presented visual, auditory, and audio-visual stimuli and recorded EEG data from Young (18–25 years), Transition (26–33 years), and Middle (34–50 years) age cohort healthy participants. We utilized source-based features for the classification of these age groups. We aimed to understand how aging affects brain activation and functional connectivity among hubs during audio-visual tasks. Our findings unveiled diminished levels of brain activation among middle-aged individuals, which escalate when exposed to AVI stimuli. Lower frequency bands showed substantial changes with increasing age during AVI. Our results demonstrated that implementing the k-means elbow method during the AVI task successfully categorized brain regions into five distinct brain networks. Additionally, we observed increased functional connectivity in middle age, particularly in the frontal, temporal, and occipital regions. These results highlight the compensatory neural mechanisms involved in aging during cognitive tasks.</p></div>","PeriodicalId":74295,"journal":{"name":"Neuroscience informatics","volume":"4 4","pages":"Article 100172"},"PeriodicalIF":0.0000,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772528624000177/pdfft?md5=dc193c32edd7c262e7a74f98e3ce48b2&pid=1-s2.0-S2772528624000177-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neuroscience informatics","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2772528624000177","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The seamless integration of visual and auditory information is a fundamental aspect of human cognition. Although age-related functional changes in Audio-Visual Integration (AVI) have been extensively explored in the past, thorough studies across various age groups remain insufficient. Previous studies have provided valuable insights into age-related AVI using EEG-based sensor data. However, these studies have been limited in their ability to capture spatial information related to brain source activation and their connectivity. To address these gaps, our study conducted a comprehensive audio-visual integration task with a specific focus on assessing the brain maturation effects in various age groups, particularly in early-mid adulthood. We presented visual, auditory, and audio-visual stimuli and recorded EEG data from Young (18–25 years), Transition (26–33 years), and Middle (34–50 years) age cohort healthy participants. We utilized source-based features for the classification of these age groups. We aimed to understand how aging affects brain activation and functional connectivity among hubs during audio-visual tasks. Our findings unveiled diminished levels of brain activation among middle-aged individuals, which escalate when exposed to AVI stimuli. Lower frequency bands showed substantial changes with increasing age during AVI. Our results demonstrated that implementing the k-means elbow method during the AVI task successfully categorized brain regions into five distinct brain networks. Additionally, we observed increased functional connectivity in middle age, particularly in the frontal, temporal, and occipital regions. These results highlight the compensatory neural mechanisms involved in aging during cognitive tasks.
视觉和听觉信息的无缝整合是人类认知的一个基本方面。虽然与年龄相关的视听整合(AVI)功能变化在过去已被广泛探讨,但对不同年龄组的深入研究仍然不足。以往的研究利用基于脑电图的传感器数据对与年龄相关的视听整合提供了宝贵的见解。然而,这些研究在捕捉与脑源激活及其连接相关的空间信息方面能力有限。为了弥补这些不足,我们的研究开展了一项综合视听整合任务,重点评估不同年龄组,尤其是成年早中期的大脑成熟效应。我们向年轻组(18-25 岁)、过渡组(26-33 岁)和中年组(34-50 岁)的健康参与者提供了视觉、听觉和视听刺激,并记录了他们的脑电图数据。我们利用基于源的特征对这些年龄组进行了分类。我们旨在了解衰老如何影响视听任务中的大脑激活和枢纽间的功能连接。我们的研究结果揭示了中年人大脑激活水平的下降,这种下降在暴露于 AVI 刺激时会加剧。在视听任务中,随着年龄的增长,低频带也发生了很大变化。我们的研究结果表明,在 AVI 任务中采用 k-means 弯头法成功地将大脑区域划分为五个不同的大脑网络。此外,我们还观察到中年人的功能连接性增强,尤其是在额叶、颞叶和枕叶区域。这些结果凸显了在认知任务中衰老所涉及的补偿性神经机制。
Neuroscience informaticsSurgery, Radiology and Imaging, Information Systems, Neurology, Artificial Intelligence, Computer Science Applications, Signal Processing, Critical Care and Intensive Care Medicine, Health Informatics, Clinical Neurology, Pathology and Medical Technology