A new model-based intrinsic connectivity measure: global functional connectivity

Intrinsic connectivity is attractive over seeded connectivity methods as there is no need for localization. However, to-date the measures used for intrinsic connectivity as described in the literature suffer several limitations. We were inspired to apply a Gaussian normalization process by a recent method using the distribution of correlation at each voxel. The new method is very attractive from a theoretical standpoint, as it only depends on the shape of the t-score distribution at each voxel and an appropriately-fitted theoretical Gaussian. Our results support the use of this new measure.

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