Large-scale neural models and dynamic causal modelling

@article{Lee2006LargescaleNM,
  title={Large-scale neural models and dynamic causal modelling},
  author={L. Lee and Karl J. Friston and B. Horwitz},
  journal={NeuroImage},
  year={2006},
  volume={30},
  pages={1243-1254}
}
Dynamic causal modelling (DCM) is a method for estimating and making inferences about the coupling among small numbers of brain areas, and the influence of experimental manipulations on that coupling [Friston, K.J., Harrison, L., Penny, W., 2003 Dynamic causal modelling. Neuroimage 19, 1273-1302]. Large-scale neural modelling aims to construct neurobiologically grounded computational models with emergent behaviours that inform our understanding of neuronal systems. One such model has been used… Expand
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  • 34
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  • 112
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References

SHOWING 1-10 OF 16 REFERENCES
Comparing dynamic causal models
  • 790
  • PDF
Investigating the neural basis for functional and effective connectivity. Application to fMRI
  • 102
  • PDF
Predicting human functional maps with neural net modeling
  • 55
  • PDF
Dynamic causal modelling
  • 3,490
  • PDF
Nonlinear Responses in fMRI: The Balloon Model, Volterra Kernels, and Other Hemodynamics
  • 999
  • PDF
The elusive concept of brain connectivity
  • B. Horwitz
  • Computer Science, Medicine
  • NeuroImage
  • 2003
  • 701
  • PDF
A report of the functional connectivity workshop, Dusseldorf 2002
  • 241
  • PDF
Nonlinear Coupling between Evoked rCBF and BOLD Signals: A Simulation Study of Hemodynamic Responses
  • 67
  • PDF
...
1
2
...