Multiple-shooting adjoint method for whole-brain dynamic causal modeling

@inproceedings{Zhuang2021MultipleshootingAM,
  title={Multiple-shooting adjoint method for whole-brain dynamic causal modeling},
  author={Juntang Zhuang and Nicha C. Dvornek and Sekhar C. Tatikonda and Xenophon Papademetris and Pamela Ventola and James S. Duncan},
  booktitle={IPMI},
  year={2021}
}
Dynamic causal modeling (DCM) is a Bayesian framework to infer directed connections between compartments, and has been used to describe the interactions between underlying neural populations based on functional neuroimaging data. DCM is typically analyzed with the expectation-maximization (EM) algorithm. However, because the inversion of a large-scale continuous system is difficult when noisy observations are present, DCM by EM is typically limited to a small number of compartments (< 10… 

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