Characterizing and Differentiating Brain State Dynamics via Hidden Markov Models

scientific article published on 21 October 2014

Characterizing and Differentiating Brain State Dynamics via Hidden Markov Models is …
instance of (P31):
scholarly articleQ13442814

External links are
P356DOI10.1007/S10548-014-0406-2
P932PMC publication ID4405424
P698PubMed publication ID25331991

P2093author name stringJing Zhang
Xiang Li
Tianming Liu
Li Xie
Dajiang Zhu
Lingjiang Li
Changfeng Jin
Jinli Ou
Rongxin Jiang
Yaowu Chen
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Functional disconnection and compensation in mild cognitive impairment: evidence from DLPFC connectivity using resting-state fMRIQ28742342
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A tutorial on hidden Markov models and selected applications in speech recognitionQ29396607
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The anatomical basis of functional localization in the cortexQ30709892
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Functional neuroimaging studies in posttraumatic stress disorder: review of current methods and findingsQ31059871
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Stuck in a rut: rethinking depression and its treatmentQ34459160
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Dynamic functional connectomics signatures for characterization and differentiation of PTSD patientsQ37591583
Connectomics signatures of prenatal cocaine exposure affected adolescent brainsQ37638001
Unsupervised learning of functional network dynamics in resting state fMRI.Q38601690
Detecting brain state changes via fiber-centered functional connectivity analysisQ39559619
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The human connectome: just another 'ome?Q48299994
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P433issue5
P921main subjecthidden Markov modelQ176769
P304page(s)666-679
P577publication date2014-10-21
P1433published inBrain TopographyQ15757692
P1476titleCharacterizing and Differentiating Brain State Dynamics via Hidden Markov Models
P478volume28

Reverse relations

cites work (P2860)
Q33854480Age-Related Decline in the Variation of Dynamic Functional Connectivity: A Resting State Analysis
Q26749109Bayesian Inference for Functional Dynamics Exploring in fMRI Data
Q91140163Brain network dynamics in schizophrenia: Reduced dynamism of the default mode network
Q39941059Evaluation of sliding window correlation performance for characterizing dynamic functional connectivity and brain states
Q57809629Functional Brain Connectivity Revealed by Sparse Coding of Large-Scale Local Field Potential Dynamics
Q57184670Large-scale Circuitry Interactions upon Earthquake Experiences Revealed by Recurrent Neural Networks
Q47594134Methods and Considerations for Dynamic Analysis of Functional MR Imaging Data
Q56706928Modeling dynamic functional connectivity using a wishart mixture model
Q89641972Questions and controversies in the study of time-varying functional connectivity in resting fMRI
Q30971457Realizing the potential of mobile mental health: new methods for new data in psychiatry
Q58119506Recognizing Brain States Using Deep Sparse Recurrent Neural Network
Q55331834Simulations to benchmark time-varying connectivity methods for fMRI.
Q30275549Structure and Topology Dynamics of Hyper-Frequency Networks during Rest and Auditory Oddball Performance

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