What makes our daily life so simple? What helps us know what is happening now, what we are thinking now, and what we are doing now? We are aware of the present moment or any changes occurring in that moment, and this ability helps us function effectively to cope with immediate environmental changes in our daily lives. This capacity is called working memory. The term working memory was coined by Miller, Galanter, and Pribram in 1960 (Baddeley, 2003). It refers to the temporary storage in the brain for the manipulation of information necessary to perform cognitive tasks. According to Baddeley and Hitch's (1974) study, working memory consists of three main components, a control system, the central executive, and two storage systems, the visuospatial sketchpad and the phonological loop (cited in Baddeley, 2003). The phonological loop stores and processes auditory input while the visuospatial sketchpad stores and processes visual input in working memory. The visuospatial sketchpad can be divided into visual subsystems and spatial subsystems. It constructs and manipulates visual images and represents visual working memory (VWM). Many recent studies have focused on investigating the neural correlation and functional organization of working memory encoding across different tasks. They were able to localize activities in specific parts of the brain during a visual working memory task in sighted participants using electrophysiological recording. They observed the activation of brain areas associated with processing visual stimuli and it fascinated many researchers to observe brain activation for different modality tasks in blind participants. During their studies, they reported cross-modal activation of occipital brain structures in a blinded manner...... middle of article ......l MRI In addition to MEG data, T1-weighted structural MRI scans were obtained for all participants. Data were acquired on a 3 Tesla system (Siemens Magnetom Trio). For source reconstruction, individual single-shell models were derived from the segmentation of these structural MRIs. Source reconstruction: All data types were analyzed using Matlab with custom scripts and the open source Matlab Field Trip and SPM2 toolkits. A linear beamforming approach was applied to estimate the spectral amplitude and phase of neuronal population signals at the cortical source (Gross, Kujala, Hamalainen, Timmermann, Schnitzler, & Salmelin, 2001; Siegel et al. 2008). This source reconstruction technique used an adaptive spatial filter, which transmitted activity from a specific location of interest with unity gain and suppressed activity from other locations as much as possible...