The reported studies on EEG inverse by multiple signal classification (MUSIC) show the classical MUSIC algorithm suffers from two shortcomings:be sensitive to a color noise and fail in identifying synchronously active sources.Recent studies reveal that the MUSIC-based algorithm may be improved in depressing spatial coherent noise if the classical zero delay correlation matrix is replaced by a non-zero delay-correlation matrix

or by a high-order cumulant matrix

or by incorporating known noise covariance matrix in the zero-delay correlation matrix.And the MUSIC algorithm can be extended to identify synchronous actives through a recursive strategy.In this work

an iterative

multi-dimensional and delay-correlation MUSIC is proposed

where the color noise is depressed by the non-zero delay correlation and the synchronous active sources are identified by the iterative multi-dimensional MUSIC search.Simulation and VEP data tests show a good reconstruction is obtained.