Effects of tDCS of the DLPFC on brain networks: A hybrid brain modeling study

Transcranial direct current stimulation (tDCS) has shown promise in treating neurological disorders, particularly through dorsolateral prefrontal cortex (DLPFC) targeting. However, the effects of DLPFC-tDCS on brain functional networks and the underlying propagation mechanisms remain poorly understood. We present a novel tDCS hybrid brain model (tDCS-HBM) that incorporates tDCS-induced gray matter electric fields into a large-scale brain network model, considering their relationship with membrane potential to effectively predict spatiotemporal dynamics. Using this model, we simulated brain activity in response to tDCS over the left (F3-Fp2) and right DLPFC (F4-Fp1). Our results demonstrate that tDCS enhances brain complexity and flexibility, leading to increased functional connectivity (FC) across the whole brain and an improvement in global network efficiency. Dynamic analysis reveals an initial FC decline, followed by widespread enhancement originating from inferior and orbital frontal regions. Importantly, right DLPFC-tDCS induces strong FC associated with the ventral attention network. These changes in topological metrics and spatiotemporal patterns are consistent with prior modeling and empirical findings, validating the utility of our tDCS-HBM in understanding propagation mechanisms. Our hybrid model holds the potential to predict the stimulation effects of modulation protocols, providing precise guidance for clinical neuromodulation interventions.Author summary: Non-invasive brain stimulation techniques are increasingly being explored as additional treatments for neurological and psychiatric disorders. However, due to individual anatomical differences and the incomplete understanding of the underlying mechanisms of brain stimulation, there is still no general agreement on the optimal stimulation protocols. Transcranial Direct Current Stimulation (tDCS), a non-invasive brain stimulation technique, modulates brain activity by applying low-intensity electrical currents through electrodes placed on the scalp. In this study, we proposed a computational model of tDCS-HBM (tDCS-Hybrid Brain Model) to predict brain responses to tDCS and provide theoretical support for the optimization of stimulation targets. Using this model, we systematically evaluated the effects of different tDCS stimulation protocols. The results indicated that tDCS enhanced global brain efficiency and functional connectivity, particularly with stimulation of the right dorsolateral prefrontal cortex (DLPFC), which strengthened the functional connectivity of the ventral attention network with other subnetworks, potentially improving alertness. Furthermore, we found that brain responses to tDCS were largely modulated by structural connectivity, providing new insights into the optimization of tDCS treatment protocols. Our approach offers theoretical guidance for the personalized implementation of clinical non-invasive brain stimulation treatments, contributing to the advancement of precision medicine.