TY - JOUR
T1 - The influence of construction methodology on structural brain network measures
T2 - a review
AU - Qi, S.
AU - Meesters, S.
AU - Nicolay, K.
AU - ter Haar Romeny, B.M.
AU - Ossenblok, P.
PY - 2015/9/30
Y1 - 2015/9/30
N2 - Structural brain networks based on diffusion MRI and tractography show robust attributes such as small-worldness, hierarchical modularity, and rich-club organization. However, there are large discrepancies in the reports about specific network measures. It is hypothesized that these discrepancies result from the influence of construction methodology. We surveyed the methodological options and their influences on network measures. It is found that most network measures are sensitive to the scale of brain parcellation, MRI gradient schemes and orientation model, and the tractography algorithm, which is in accordance with the theoretical analysis of the small-world network model. Different network weighting schemes represent different attributes of brain networks, which makes these schemes incomparable between studies. Methodology choice depends on the specific study objectives and a clear understanding of the pros and cons of a particular methodology. Because there is no way to eliminate these influences, it seems more practical to quantify them, optimize the methodologies, and construct structural brain networks with multiple spatial resolutions, multiple edge densities, and multiple weighting schemes.
AB - Structural brain networks based on diffusion MRI and tractography show robust attributes such as small-worldness, hierarchical modularity, and rich-club organization. However, there are large discrepancies in the reports about specific network measures. It is hypothesized that these discrepancies result from the influence of construction methodology. We surveyed the methodological options and their influences on network measures. It is found that most network measures are sensitive to the scale of brain parcellation, MRI gradient schemes and orientation model, and the tractography algorithm, which is in accordance with the theoretical analysis of the small-world network model. Different network weighting schemes represent different attributes of brain networks, which makes these schemes incomparable between studies. Methodology choice depends on the specific study objectives and a clear understanding of the pros and cons of a particular methodology. Because there is no way to eliminate these influences, it seems more practical to quantify them, optimize the methodologies, and construct structural brain networks with multiple spatial resolutions, multiple edge densities, and multiple weighting schemes.
KW - Diffusion MRI
KW - Tractography
KW - Networks
KW - Connectivity
KW - Methodology
U2 - 10.1016/j.jneumeth.2015.06.016
DO - 10.1016/j.jneumeth.2015.06.016
M3 - Article
C2 - 26129743
SN - 0165-0270
VL - 253
SP - 170
EP - 182
JO - Journal of Neuroscience Methods
JF - Journal of Neuroscience Methods
ER -