Objective: The stereo electroencephalogram (SEEG) recordings are the sate of the art tool used in pre-surgical evaluation of drug-unresponsive epileptic patients. Coupled with SEEG, electrical cortical stimulation (CS) offer a complementary tool to investigate the lesioned/healthy brain regions and to identify the epileptic zones with precision. However, the propagation of this stimulation inside the brain masks the cerebral activity recorded by nearby multi-contact SEEG electrodes. The objective of this paper is to propose a novel filtering approach for suppressing the CS artifact in SEEG signals using time, frequency as well as spatial information. Methods: The method combines spatial filtering with tunable-Q wavelet transform (TQWT). SEEG signals are spatially filtered to isolate the CS artifacts within a few number of sources/components. The artifacted components are then decomposed into oscillatory background and sharp varying transient signals using tunable-Q wavelet transform (TQWT). The CS artifact is assumed to lie in the transient part of the signal. Using prior known time-frequency information of the CS artifacts, we selectively mask the wavelet coefficients of the transient signal and extract out any remaining significant electro-physiological activity. Results: We have applied our proposed method of CS artifact suppression on simulated and real SEEG signals with convincing performance. The experimental A. Bhattacharyya 2 results indicate the effectiveness of the proposed approach. Conclusion: The proposed method suppresses CS artifacts without affecting the background SEEG signal. Significance: The proposed method can be applied for suppressing both low and high frequency CS artifacts and outperforms current methods from the literature. Index Terms cortical stimulation, SEEG, tunable-Q wavelet transform, subspace correlation approach, blind source separation.