There is a nice review paper on FMRI connectivity in Neuroimage:
Stephen M. Smith, The future of FMRI connectivity, NeuroImage, accepted by 2012.
Clearly, it attracts the interests of many researchers in this field, since it has been one of the most downloaded papers in the journal (but now it is just an accepted paper)!
Here is the abstract:
“FMRI connectivity” encompasses many areas of research, including resting-state networks, biophysical modelling of task-FMRI data and bottom-up simulation of multiple individual neurons interacting with each other. In this brief paper I discuss several outstanding areas that I believe will see exciting developments in the next few years, in particular concentrating on how I think the currently separate approaches will increasingly need to take advantage of each others' respective complementarities.
And the outline of the contents:
Contents
Introduction - brief review of concepts
Networkmodellingvianodesandedges;functionalvs.effectiveconnectivity.
Spatial patterns of connectivity
Connectivity modelling from multiple subjects
Model complexity
Bottom-up modelling
Graph theory
FMRI network modelling methods
Causality
Patterns of conditional independence; observational vs. interventional studies
Dynamic biological Bayesian models
Future
Nonlinearities and temporal nonstationarities
Other issues… and conclusions
Although this is a brief review paper, the author has tried to cover many important aspects of fMRI connectivity. But I think there are two aspects may need to put more words. One is the sparsity based models in the section of model complexity. The second is how to verify the fidelity of an estimated connectivity network. Hope I can see the two issues especially the second one are discussed in details in future's review papers.
No comments:
Post a Comment
Note: Only a member of this blog may post a comment.