Abstract Numerous studies show that mental health conditions are linked to abnormal activity in specific brain networks. In major depressive disorder (MDD) the frontoparietal network (FPN) experiences reduced activity and disrupted connectivity, closely tied to clinical symptoms. Transcranial Magnetic Stimulation (TMS) has gained FDA approval as a non-invasive, effective alternative for drug resistant MDD patients. While repetitive TMS (rTMS) administered to dorsolateral prefrontal cortex (DFPLC) using a single coil alleviates depressive symptoms, it fails to restore the global connectivity of the FPN. Therefore, this proposal leverages the use of our recently developed multichannel TMS (mTMS) array system combined with electroencephalography (EEG) to simultaneously modulate and record activity across multiple nodes of a cortical network. To implement network-specific multifocal TMS for neuropsychiatric disorders, several technical aspects need to be further developed. The network subregion targets need to be identified for each individual and here we propose to use combined functional and structural connectivity measures obtained from Magnetic Resonance Imaging (MRI) data for maximal spatial specificity. We use computational methods to determine the best possible combination of all coil elements in the array to stimulate the network nodes, while minimizing the effects elsewhere. We will utilize a whole-head TMS compatible EEG system to quantify the changes in functional connectivity concurrently with the multifocal stimulation of different network subregions. The goals of this project include optimizing the targeting of brain subregions within the Frontoparietal Network (FPN) and Sensorimotor Network (SMN), validated through structural and functional imaging techniques. By investigating the effects of bifocal stimulation on network connectivity, particularly focusing on the connectivity changes in alpha/theta synchronization between the DLPFC and Posterior Parietal Cortex (PPC), the project aims to advance our understanding of network-level brain connectivity. The anticipated impact is to improve our understanding of network-level brain dysfunctions and to potentially develop more effective TMS therapies for neuropsychiatric disorders.