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Related Concept Videos

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.
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Dementia is a collective term for cognitive disorders primarily affecting memory, thinking, and reasoning. It is not a specific disease but a syndrome, with Alzheimer's disease being the most common cause, accounting for approximately 60-80% of cases. Other types include vascular dementia, Lewy body dementia, and frontotemporal dementia. Dementia affects millions worldwide, particularly older adults, though it is not a normal part of aging.
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Alzheimer's Disease (AD), a neurodegenerative disorder, is pathologically identified by amyloid plaques and neurofibrillary tangles composed of tau protein. AD pharmacotherapy aims to manage cognitive symptoms, delay disease progression, and treat behavioral symptoms. The treatment is primarily symptomatic and palliative, with no definitive disease-modifying therapy available. Cholinesterase inhibitors, including donepezil (Aricept), rivastigmine (Exelon), and galantamine (Razadyne), are...
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Related Experiment Video

Updated: Jun 14, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

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Path Integration Detects Prodromal Alzheimer's Disease and Predicts Cognitive Decline.

Haruo Hanyu1,2, Yumi Koyama3, Kazuki Umekida3

  • 1Dementia Research Center, Tokyo General Hospital, Tokyo, Japan.

Journal of Alzheimer'S Disease : JAD
|September 6, 2024
PubMed
Summary
This summary is machine-generated.

Path integration performance in a 3D virtual reality task can detect individuals with mild cognitive impairment at high risk for Alzheimer's disease (AD). This navigation assessment accurately predicts cognitive decline, serving as a potential screening tool for prodromal AD.

Keywords:
Alzheimer’s diseasemild cognitive impairmentpath integrationprodromal Alzheimer’s diseaseprogressionvirtual reality

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Area of Science:

  • Neuroscience
  • Cognitive Science
  • Medical Imaging

Background:

  • The entorhinal cortex shows early involvement in Alzheimer's disease (AD).
  • Grid cells within the medial entorhinal cortex are crucial for spatial navigation.
  • Spatial navigation deficits may indicate early AD pathology.

Purpose of the Study:

  • To evaluate path integration performance as a method for detecting mild cognitive impairment (MCI) patients at high risk for AD.
  • To determine if path integration performance can predict future cognitive decline.
  • To assess the utility of a 3D virtual reality navigation task for identifying prodromal AD.

Main Methods:

  • Assessed path integration in 71 patients with early MCI (EMCI) and late MCI (LMCI).
  • Utilized a 3D virtual reality navigation task to measure performance.
  • Subdivided LMCI patients into LMCI+ (with AD imaging features) and LMCI- (without AD features).

Main Results:

  • Path integration performance was significantly lower in LMCI+ patients compared to EMCI and LMCI-.
  • Lower performance correlated with MCI progression over 12 months.
  • The task achieved high accuracy (0.88 sensitivity, 0.70 specificity) in distinguishing progressive from stable MCI.

Conclusions:

  • The 3D virtual reality navigation task effectively detects prodromal AD and predicts cognitive decline.
  • This simple, noninvasive, and inexpensive task may serve as a screening tool for prodromal AD.
  • The findings support the use of navigation tasks in identifying individuals for therapeutic interventions in early AD stages.