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Effects of spatial smoothing on group-level differences in functional brain networks.

Ana María Triana1, Enrico Glerean2, Jari Saramäki1

  • 1Department of Computer Science, School of Science, Aalto University, Espoo, Finland.

Network Neuroscience (Cambridge, Mass.)
|September 5, 2020
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Summary

Spatial smoothing significantly impacts functional brain network differences between patient groups and controls. Increasing smoothing can make networks more distinct or similar, depending on the analysis type and network density.

Keywords:
AutismFunctional connectivityNetwork-based statisticSpatial smoothingfMRI preprocessing

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Area of Science:

  • Neuroimaging
  • Computational Neuroscience
  • Brain Network Analysis

Background:

  • Functional magnetic resonance imaging (fMRI) is crucial for identifying brain differences in clinical populations.
  • Preprocessing fMRI data is essential for artifact control and quality improvement.
  • Spatial smoothing, a common preprocessing step, is known to alter functional network structure.

Purpose of the Study:

  • To investigate the impact of spatial smoothing on group-level functional brain network differences.
  • To analyze how varying Gaussian kernel sizes affect network distinctions between patients and controls.
  • To assess the influence of smoothing on network differences in autism spectrum disorder and bipolar disorder cohorts.

Main Methods:

  • Utilized fMRI data from patients with autism spectrum disorder and bipolar disorder, alongside healthy controls.
  • Applied spatial smoothing with Gaussian kernels ranging from 0 to 32 mm.
  • Analyzed both weighted and thresholded functional brain networks.
  • Examined effects on network differences, link differences, effect sizes, and dependence on region of interest (ROI) size and link length.

Main Results:

  • Spatial smoothing demonstrably affects group-level network differences.
  • For weighted networks, increased smoothing led to greater inter-group differences.
  • For thresholded networks, greater smoothing resulted in more similar networks, contingent on network density.
  • Smoothing altered effect sizes of individual link differences, varying with link length but not ROI size.

Conclusions:

  • The choice of spatial smoothing kernel has significant and often unpredictable consequences on observed functional brain network differences.
  • Findings highlight the need for careful consideration and reporting of spatial smoothing parameters in neuroimaging studies.
  • Preprocessing choices, particularly spatial smoothing, can substantially influence conclusions drawn from group comparisons in clinical neuroscience.