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Related Concept Videos

Brain Waves01:23

Brain Waves

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Brain waves are electrical signals generated by the neurons in the brain, which are regularly monitored to measure mental activities. Brain waves and their frequency ranges can be measured using an electroencephalogram or EEG. There are four main types of brain waves, each with distinct characteristics:
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Electroencephalography Network Indices as Biomarkers of Upper Limb Impairment in Chronic Stroke
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Weighted network measures reveal differences between dementia types: An EEG study.

Ramtin Mehraram1,2,3, Marcus Kaiser3,4, Ruth Cromarty1

  • 1Institute of Neuroscience, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne, UK.

Human Brain Mapping
|December 10, 2019
PubMed
Summary
This summary is machine-generated.

Electroencephalography (EEG) reveals distinct brain network patterns differentiating dementia with Lewy bodies (DLB) from Alzheimer's disease (AD). These EEG biomarkers may aid in early diagnosis, distinguishing DLB from AD and Parkinson's disease dementia (PDD).

Keywords:
Alzheimer's diseaseLewy bodyParkinson's diseasebiomarkerbrain connectivitygraph theoryproportional thresholding

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Area of Science:

  • Neuroscience
  • Biomarkers
  • Medical Imaging

Background:

  • Distinguishing dementia with Lewy bodies (DLB) from Alzheimer's disease (AD) is challenging, particularly in early stages.
  • Electroencephalography (EEG) offers a non-invasive, cost-effective method for assessing brain network alterations.
  • Limited research exists on EEG-based brain network changes in DLB and Parkinson's disease dementia (PDD) compared to AD.

Purpose of the Study:

  • To identify EEG network biomarkers capable of differentiating between AD, DLB, and PDD.
  • To evaluate the reliability of weighted network matrices in preserving network topology for diagnostic accuracy.
  • To investigate alterations in brain network connectivity across different dementia subtypes.

Main Methods:

  • Comparison of brain network connectivity patterns using EEG data from AD, DLB, PDD patients, and healthy controls (HC).
  • Analysis of network properties in different EEG frequency bands (α, β, θ).
  • Assessment of weighted versus unweighted network matrices for diagnostic performance and topological preservation.

Main Results:

  • Dementia groups exhibited reduced connectivity in the α-band compared to HC.
  • DLB showed distinct patterns: weaker posterior-anterior connectivity in the β-band and increased network segregation in the θ-band compared to AD.
  • Weighted network measures demonstrated greater consistency and reflected reduced connectivity strength in dementia groups.

Conclusions:

  • β- and θ-band EEG network measures show potential as biomarkers for discriminating DLB from AD.
  • α-band network alterations appear similar in DLB and PDD compared to HC, possibly reflecting attentional network impairments.
  • EEG-based network analysis provides valuable insights into the differential pathophysiology of various dementia types.