Standard neuroimaging techniques can observe but cannot probe or modulate a human brain circuit, thus severely limiting our ability to study the causality, directionality, and malleability of a circuit. This project combines modalities to produce a novel technique to observe, probe, and modulate human brain circuits with a clear biological basis and with high spatial and temporal resolution. Specifically, this research will define and model the functional neural properties of the central executive network (CEN), a circuit critical for decision making and implicated in many psychiatric disorders. A greater understanding will enhance our ability to modulate the CEN, the target of FDA-approved brain stimulation treatments like transcranial magnetic stimulation (TMS). The proposed research involves a series of experiments to be performed at Stanford University and Aix-Marseille University, building on a data sharing platform and stimulation methodologies developed at these two sites. The project consists of three aims: (1) Investigate the excitability, connectivity, and neuronal properties within the CEN, (2) Derive accurate tools to delineate CEN connectivity in healthy and depressed populations, and (3) Characterize inter-individual variability within the CEN and test if localization at the individual level can more effectively modulate this circuit. This novel approach first utilizes a large database of brain stimulation recordings to map the circuit of interest at an unparalleled level of detail, develop the transfer function to validate non-invasive measures of connectivity, and apply these insights to improve targeted stimulation treatments. One scientific outcome is to produce the most precise, causal, electrophysiology-grounded, functional parcellation maps of the human CEN to date. These maps will quantify the directionality, causality, and neuronal properties (axon delay, excitability and inhibitory time constants) to and from each subunit of the CEN. They will be freely available using an already established robust data sharing infrastructure and will be highly impactful to researchers interested in understanding, modeling, and predicting complex frontal lobe behavior. A second scientific outcome are novel non-invasive measures of connectivity grounded in electrophysiology. These measures will be freely available to enable other researchers to causally probe brain circuits and study brain-behavior relationships and disease pathophysiology. Future work will derive biologically grounded non-invasive measures from each brain circuit. This research has a broader impact by implementing a US-France collaboration using data sharing infrastructure developed from the European Human Brain Project. Although data sharing is standard in neuroimaging, it is unfortunately rare among electrophysiologists; thus, there is great potential to move towards other large knowledge and data sharing initiatives. This research also has public health relevance as it focuses on developing more targeted and effective treatments for mental health disorders, which have a lifetime incidence of nearly 50%. The pandemic has increased those currently suffering from depression or anxiety, and preliminary data show a high incidence of post-infection new onset mental health diagnoses. This research identifies CEN abnormalities in depression and tests a novel method to localize and modulate the CEN on an individual level. If successful, this individualized and circuit-based approach would represent a paradigm shift in brain stimulation treatments. Finally, as TMS is now FDA-approved or being investigated for treatment of almost all psychiatric and neurological disorders, this novel approach of circuit dissection and individualized brain stimulation has broad treatment and societal implications.