Maximizing the negentropy maximizes the mutual information.

In general, ICA components are neither ranked nor orthogonal.

Criteria for independence are mutual information between components and non-Gaussianity of components.

Non-Gaussianity can be measured by the second cumulant.

Infomax maximizes the mutual information between components.

Fast ICA relies on whitening and rotating the data.

The ICA solution is unique.

For ICA, one needs more sources than observations.