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Alzheimer's Disease: Overview01:26

Alzheimer's Disease: Overview

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Alzheimer's Disease (AD) is a continually advancing neurodegenerative disorder, distinguished by escalating memory loss, cognitive dysfunction, and dementia. The disease unfolds in three stages: preclinical, mild cognitive impairment (MCI), and dementia. Its onset is insidious, and the progression gradual, with the cause not well explained by other disorders.
The clinical diagnosis of AD hinges on the presence of memory and other cognitive impairments. Biomarkers, such as changes in Aβ...
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Seizures: Classification01:13

Seizures: Classification

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Epilepsy is primarily characterized by unpredictable seizures, either provoked by an identifiable factor, such as injury or illness, or unprovoked, occurring spontaneously without apparent cause.
Seizures are typically classified into two main categories: focal and generalized seizures.
Focal Seizures
Focal seizures originate from specific regions of the brain. These seizures are further sub-classified into two types:
2.5K
Cognitive Development During Adulthood01:30

Cognitive Development During Adulthood

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Cognitive development continues throughout adulthood, undergoing significant shifts across early, middle, and late stages. Individual transition occurs from adolescent idealism to pragmatic and adaptable thinking in early adulthood. During this period, individuals learn to integrate personal beliefs with the recognition that other perspectives are equally valid. Exposure to the complexities of modern society, diverse experiences, and higher education contribute to this adaptive thought process,...
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Alzheimer Disease l: Introduction01:29

Alzheimer Disease l: Introduction

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Alzheimer disease is a chronic, progressive, and irreversible neurodegenerative disorder and the most common cause of dementia in older adults. It leads to gradual neuronal loss, causing cognitive decline, behavioral changes, and loss of functional independence.Risk Factors and EtiologyThe disease is multifactorial. Age is the strongest risk factor, with prevalence doubling every 5 years after age 65. Genetic factors include mutations in genes such as APP, PSEN1, and PSEN2, which are associated...
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Alzheimer Disease ll: Pathophysiology01:23

Alzheimer Disease ll: Pathophysiology

35
Alzheimer disease involves structural changes in the brain that begin long before symptoms appear. The most distinctive features are extracellular neuritic plaques and intracellular neurofibrillary tangles.Neuritic plaques form in the cerebral cortex and around blood vessels. These plaques contain a dense core of beta-amyloid (Aβ)—a toxic protein fragment that clumps outside neurons. The core is surrounded by damaged neuronal extensions, as well as reactive astrocytes and...
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Dementia l: Introduction01:22

Dementia l: Introduction

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Dementia is an acquired, progressive syndrome characterized by a decline in multiple cognitive domains severe enough to impair daily functioning and reduce independence. Although memory loss is a central feature, the diagnosis requires additional deficits involving language, executive function, visuospatial skills, judgment, calculation, or abstract reasoning. These cognitive impairments reflect underlying neurodegenerative or vascular processes that gradually disrupt neuronal networks...
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相关实验视频

Updated: May 4, 2026

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance
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A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance

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罗图卷积网络量化了越来越多的结构-功能差异在认知衰退连续的结构-功能差异.

Gurur Gamgam1, Zerrin Yıldırım2, Alkan Kabakçıoğlu3

  • 1VAVlab, Department of Electrical And Electronics Eng., Bogazici University, Istanbul, 34342, Turkiye.

Computer methods and programs in biomedicine
|July 2, 2024
PubMed
概括
此摘要是机器生成的。

结构功能差异学习网络 (sfDLN) 量化了大脑连接不匹配,超过了目前对阿尔茨海默氏症痴呆症 (ADD) 诊断的方法.

关键词:
阿尔茨海默氏症是阿尔茨海默氏症的一种疾病.大脑连接组连接组痴呆症是一种痴呆症.图形神经网络的神经网络结构功能差异的不一致性结构-功能差距的差距.

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Application of Granger Causality Analysis of the Directed Functional Connection in Alzheimer's Disease and Mild Cognitive Impairment
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Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
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相关实验视频

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科学领域:

  • 神经科学是一个神经科学.
  • 机器学习 机器学习
  • 医疗成像医学成像

背景情况:

  • 阿尔茨海默病痴呆症 (ADD) 改变了大脑的连接,但目前的措施缺乏诊断特异性.
  • 图形神经网络 (GNN) 在大脑研究中表现有前途,但通常使用单模网络.
  • 结构性和功能性大脑连接的相互依赖性至关重要,但在ADD研究中经常被忽视.

研究的目的:

  • 开发一种新的深度学习模型,结构功能差异学习网络 (sfDLN),以量化阿尔茨海默病中大脑连接的破坏.
  • 利用结构功能差异得分作为认知衰退的诊断生物标志物.
  • 将sfDLN的诊断性能与现有的最先进的分类器进行比较.

主要方法:

  • 采用了语GNN架构 (sfDLN),假设增加结构功能不匹配与认知衰退 (主观认知障碍 (SCI) 到轻度认知障碍 (MCI) 到ADD).
  • 输入数据包括来自扩散MRI的结构性脑连接体 (sNET) 和来自fMRI的稀疏功能性脑连接体 (lNET).
  • sfDLN被训练以提取连接组表示和差异得分,然后在MCI队列上盲目测试.

主要成果:

  • sfDLN生成的差异得分显示了ADD和SCI受试者之间的显著差异.
  • 对SCI与ADD的留下一个缺点分类实现了88%的准确性,超过了现有的基于GNN的方法.
  • 对MCI受试者的盲目评估证实了sfDLN能够捕捉中间认知衰退阶段的能力.
  • 在GNNExplainer分析中,在差异得分中确定了与ADD相关的神经学上相关的皮质区域.

结论:

  • 随着认知衰退的增加,大脑结构-功能和降低,支持研究的假设.
  • 量化的差异,植根于ADD相关的大脑区域,作为一个强大的诊断生物标志物.
  • 与当前基于GNN的方法相比,sfDLN在分类ADD方面表现优越.