TY - GEN
T1 - Activation analysis on fMRI time series using stochastic context-free model
AU - Xu, Xingzhong
AU - Man, Hong
PY - 2014
Y1 - 2014
N2 - In this paper, a novel statistical tool, stochastic context-free models (SCFMs), is introduced to model and analyze brain voxel activation in fMRI time series. SCFMs characterize the dynamic process where Blood-oxygen-level dependent (BOLD) responses are assumed to be driven by brain voxel activation in pre-designed experiments. Classical state space methods such as hidden Markov models(HMMs) make strong Markov assumptions on states behaviors. Whereas, in SCFMs, more powerful context-free grammar rules are used to model such behaviors in accordance to paradigm design. The methodologies of evaluation, inference, and decoding based on SCFMs are presented. Experimental results using both HMMs and SCFMs show that the later models can better capture the completeness of the target activation patterns, and encapsulate more hierarchical information in the resulting probabilistic parsing tree.
AB - In this paper, a novel statistical tool, stochastic context-free models (SCFMs), is introduced to model and analyze brain voxel activation in fMRI time series. SCFMs characterize the dynamic process where Blood-oxygen-level dependent (BOLD) responses are assumed to be driven by brain voxel activation in pre-designed experiments. Classical state space methods such as hidden Markov models(HMMs) make strong Markov assumptions on states behaviors. Whereas, in SCFMs, more powerful context-free grammar rules are used to model such behaviors in accordance to paradigm design. The methodologies of evaluation, inference, and decoding based on SCFMs are presented. Experimental results using both HMMs and SCFMs show that the later models can better capture the completeness of the target activation patterns, and encapsulate more hierarchical information in the resulting probabilistic parsing tree.
UR - http://www.scopus.com/inward/record.url?scp=84904176149&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84904176149&partnerID=8YFLogxK
U2 - 10.1109/WOCC.2014.6839914
DO - 10.1109/WOCC.2014.6839914
M3 - Conference contribution
AN - SCOPUS:84904176149
SN - 9781479952496
T3 - 2014 23rd Wireless and Optical Communication Conference, WOCC 2014
BT - 2014 23rd Wireless and Optical Communication Conference, WOCC 2014
T2 - 2014 23rd Wireless and Optical Communication Conference, WOCC 2014
Y2 - 9 May 2014 through 10 May 2014
ER -