TY - GEN
T1 - Distributional representation for resting-state functional brain connectivity analysis
AU - Zhu, Jiating
AU - Cao, Jiannong
PY - 2018/1/1
Y1 - 2018/1/1
N2 - Most analyses on functional brain connectivity across a group of brains are under the assumption that the positions of the voxels are aligned into a common space. However, the alignment errors are inevitable. To address such issue, a distributional representation for resting-state functional brain connectivity is proposed here. Unlike other relevant connectivity analyses that only consider connections with higher correlation values between voxels, the distributional approach takes the whole picture. The spatial structure of connectivity is captured by the distance between voxels so that the relative position information is preserved. The distributional representation can be visualized to find outliers in a large dataset. The centroid of a group of brains is discovered. The experimental results show that resting-state brains are distributed on the ‘orbit’ around their categorical centroid. In contrast to the main-stream representation such as selected network properties for disease classification, the proposed representation is task-free, which provides a promising foundation for further analysis on functional brain connectivity in various ends.
AB - Most analyses on functional brain connectivity across a group of brains are under the assumption that the positions of the voxels are aligned into a common space. However, the alignment errors are inevitable. To address such issue, a distributional representation for resting-state functional brain connectivity is proposed here. Unlike other relevant connectivity analyses that only consider connections with higher correlation values between voxels, the distributional approach takes the whole picture. The spatial structure of connectivity is captured by the distance between voxels so that the relative position information is preserved. The distributional representation can be visualized to find outliers in a large dataset. The centroid of a group of brains is discovered. The experimental results show that resting-state brains are distributed on the ‘orbit’ around their categorical centroid. In contrast to the main-stream representation such as selected network properties for disease classification, the proposed representation is task-free, which provides a promising foundation for further analysis on functional brain connectivity in various ends.
KW - Categorical centroid
KW - Distributional representation
KW - Functional brain connectivity
KW - Outliers visualization
UR - http://www.scopus.com/inward/record.url?scp=85058572396&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-05587-5_20
DO - 10.1007/978-3-030-05587-5_20
M3 - Conference article published in proceeding or book
AN - SCOPUS:85058572396
SN - 9783030055868
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 205
EP - 215
BT - Brain Informatics - International Conference, BI 2018, Proceedings
A2 - Yang, Yang
A2 - Yamamoto, Vicky
A2 - Wang, Shouyi
A2 - Jones, Erick
A2 - Su, Jianzhong
A2 - Mitchell, Tom
A2 - Iasemidis, Leon
PB - Springer-Verlag
T2 - International Conference on Brain Informatics, BI 2018
Y2 - 7 December 2018 through 9 December 2018
ER -