PMID- 36609668
OWN - NLM
STAT- MEDLINE
DCOM- 20230412
LR  - 20230421
IS  - 1559-0089 (Electronic)
IS  - 1539-2791 (Linking)
VI  - 21
IP  - 2
DP  - 2023 Apr
TI  - IABC: A Toolbox for Intelligent Analysis of Brain Connectivity.
PG  - 303-321
LID - 10.1007/s12021-022-09617-z [doi]
AB  - Brain functional networks and connectivity have played an important role in 
      exploring brain function for understanding the brain and disclosing the 
      mechanisms of brain disorders. Independent component analysis (ICA) is one of the 
      most widely applied data-driven methods to extract brain functional 
      networks/connectivity. However, it is hard to guarantee the reliability of 
      networks/connectivity due to the randomness of component order and the difficulty 
      in selecting an optimal component number in ICA. To facilitate the analysis of 
      brain functional networks and connectivity using ICA, we developed a MATLAB 
      toolbox called Intelligent Analysis of Brain Connectivity (IABC). IABC 
      incorporates our previously proposed group information guided independent 
      component analysis (GIG-ICA), NeuroMark, and splitting-merging assisted reliable 
      ICA (SMART ICA) methods, which can estimate reliable individual-subject 
      neuroimaging measures for further analysis. After user inputs functional magnetic 
      resonance imaging (fMRI) data of multiple subjects that are regularly organized 
      (e.g., in Brain Imaging Data Structure (BIDS)) and clicks a few buttons to set 
      parameters, IABC automatically outputs brain functional networks, their related 
      time courses, and functional network connectivity of each subject. All these 
      neuroimaging measures are promising for providing clues in understanding brain 
      function and differentiating brain disorders.
CI  - (c) 2023. The Author(s), under exclusive licence to Springer Science+Business 
      Media, LLC, part of Springer Nature.
FAU - Du, Yuhui
AU  - Du Y
AD  - School of Computer and Information Technology, Shanxi University, Taiyuan, China. 
      duyuhui@sxu.edu.cn.
FAU - Kong, Yanshu
AU  - Kong Y
AD  - School of Computer and Information Technology, Shanxi University, Taiyuan, China.
FAU - He, Xingyu
AU  - He X
AD  - School of Computer and Information Technology, Shanxi University, Taiyuan, China.
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20230107
PL  - United States
TA  - Neuroinformatics
JT  - Neuroinformatics
JID - 101142069
SB  - IM
MH  - Humans
MH  - Reproducibility of Results
MH  - *Brain/diagnostic imaging
MH  - Brain Mapping/methods
MH  - Magnetic Resonance Imaging/methods
MH  - *Brain Diseases
OTO - NOTNLM
OT  - BIDS
OT  - Brain functional networks
OT  - Functional network connectivity
OT  - IABC
OT  - Independent component analysis
EDAT- 2023/01/08 06:00
MHDA- 2023/04/12 06:42
CRDT- 2023/01/07 16:45
PHST- 2022/11/30 00:00 [accepted]
PHST- 2023/04/12 06:42 [medline]
PHST- 2023/01/08 06:00 [pubmed]
PHST- 2023/01/07 16:45 [entrez]
AID - 10.1007/s12021-022-09617-z [pii]
AID - 10.1007/s12021-022-09617-z [doi]
PST - ppublish
SO  - Neuroinformatics. 2023 Apr;21(2):303-321. doi: 10.1007/s12021-022-09617-z. Epub 
      2023 Jan 7.