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Correlation means that there is a relationship between two or more variables (such as ice cream consumption and crime), but this relationship does not necessarily imply cause and effect. When two variables are correlated, it simply means that as one variable changes, so does the other. We can measure correlation by calculating a statistic known as a correlation coefficient. A correlation coefficient is a number from -1 to +1 that indicates the strength and direction of the relationship between...
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Default network correlations analyzed on native surfaces.

Tyler M Seibert1, James B Brewer

  • 1Department of Bioengineering, University of California, San Diego, 9500 Gilman Dr., La Jolla, CA 92093-0949, USA. tseibert@ucsd.edu

Journal of Neuroscience Methods
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Summary
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Researchers explored brain activity disruptions in Alzheimer's disease and related dementias using advanced fMRI analysis. This new method improves accuracy by analyzing individual brain surfaces, aiding in understanding default network changes.

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Area of Science:

  • Neuroimaging
  • Cognitive Neuroscience
  • Neurology

Background:

  • Interregional correlations in blood oxygenation level dependent (BOLD) fMRI signals are disrupted in diseases like Alzheimer's disease (AD) and mild cognitive impairment.
  • Default network regions, overlapping with early amyloid deposition areas, show abnormal activity, even in healthy elderly individuals with high amyloid burden.
  • Current analysis methods transform functional data to atlases, potentially overlooking anatomical variations and atrophy in subjects.

Purpose of the Study:

  • To assess the utility of FreeSurfer cortical parcellation for analyzing default network functional correlations on native individual subject surfaces.
  • To develop a method that better accounts for anatomical variation, especially in the presence of atrophy.
  • To apply this novel approach to resting-state fMRI data across various subject groups.

Main Methods:

  • Utilized FreeSurfer cortical parcellation to analyze default network functional correlations directly on individual subject's native cortical surfaces.
  • Performed group-level quantitative analysis by comparing correlations between equivalent cortical structures across different subjects.
  • Applied the method to resting-state fMRI data from young healthy controls, cognitively unimpaired elderly, and patients with Alzheimer's disease, Parkinson's disease, Parkinson's disease dementia, and dementia with Lewy bodies.

Main Results:

  • The FreeSurfer-based native surface analysis method was successfully applied to resting-state fMRI data.
  • Preliminary results were obtained from diverse clinical groups, demonstrating the method's applicability in neurodegenerative disease research.
  • This approach offers a more anatomically precise way to study functional connectivity compared to atlas-based methods.

Conclusions:

  • The FreeSurfer cortical parcellation approach provides a robust method for analyzing default network functional correlations on native individual surfaces.
  • This technique enhances the accuracy of interregional correlation analysis by accommodating individual anatomical variations and atrophy.
  • The findings support the use of this surface-based analysis for investigating brain function in aging and neurodegenerative diseases, including Alzheimer's and Parkinson's disease.