nilearn.connectome: Functional Connectivity

Tools for computing functional connectivity matrices and also implementation of algorithm for sparse multi subjects learning of Gaussian graphical models.

Classes:

ConnectivityMeasure([cov_estimator, kind, ...])

A class that computes different kinds of functional connectivity matrices.

GroupSparseCovariance([alpha, tol, ...])

Covariance and precision matrix estimator.

GroupSparseCovarianceCV([alphas, ...])

Sparse inverse covariance w/ cross-validated choice of the parameter.

Functions:

sym_matrix_to_vec(symmetric[, discard_diagonal])

Return the flattened lower triangular part of an array.

vec_to_sym_matrix(vec[, diagonal])

Return the symmetric matrix given its flattened lower triangular part.

group_sparse_covariance(subjects, alpha[, ...])

Compute sparse precision matrices and covariance matrices.

cov_to_corr(covariance)

Return correlation matrix for a given covariance matrix.

prec_to_partial(precision)

Return partial correlation matrix for a given precision matrix.