Temporal interference stimulation (TIS) is a novel non‐invasive neuromodulation technique enabling targeted stimulation of deep brain structures with enhanced focality. By applying multiple high‐frequency (≥ 1 kHz) electric fields with a small frequency difference (Δ f ), TIS generates a low‐frequency amplitude‐modulated envelope at the interference focus, modulating neural activity while minimizing superficial stimulation. Since its introduction, research has rapidly explored TIS's computational foundations, biophysical mechanisms, experimental validation, and therapeutic potential. This review synthesizes advancements, detailing computational optimization strategies for personalized targeting and dynamical modeling insights into neuronal mechanisms like nonlinear ion channel rectification, which underpin TIS efficacy. Preclinical and human studies validating functional outcomes (e.g., memory, motor) and assessing the safety profile are evaluated, confirming TIS's ability to modulate deep targets like the hippocampus and striatum. TIS is compared with conventional tES and invasive DBS, highlighting its unique advantages (non‐invasive depth access) and limitations (lower focal intensity, modeling complexity). Emerging clinical applications in disorders like Alzheimer's, Parkinson's, epilepsy, and depression are discussed. Future directions focus on refining protocols, enhancing personalization (e.g., multi‐channel, closed‐loop), and establishing long‐term safety/efficacy. This review consolidates multidisciplinary findings to advance TIS translation from experimental concepts toward clinical reality as a potentially transformative neuromodulation tool.

While motor deficits in Parkinson’s disease (PD) are well-studied, the role of somatosensory processing in postural instability remains unclear. It is unknown whether sensory gating, a mechanism for filtering irrelevant sensory input, is impaired during standing balance in individuals with PD. To address this, we investigated cortical sensory processing in individuals with PD, age-matched older adults (OA), and young adults (YA) as they performed four balance tasks of increasing difficulty. We measured postural sway using a force platform and recorded somatosensory-evoked potentials (SEPs) from the primary somatosensory cortex (S1) following tibial nerve stimulation. Our results showed a clear dissociation between behavior and neurophysiology. Although postural sway was comparable between the PD and OA groups, only the OA and YA groups showed intact sensory gating, with SEP amplitudes decreasing as the balance challenge increased. In contrast, participants with PD demonstrated consistently elevated SEP amplitudes across all conditions. This study provides the first direct evidence of impaired sensory gating during standing balance in PD. These findings indicate a fundamental deficit in the cortical processing of sensory information essential for postural control. Consequently, they underscore the critical need for therapeutic interventions that target sensory integration deficits, not just motor symptoms. Key points: Healthy young and older adults demonstrate intact sensory gating during standing balance, with somatosensory-evoked potential (SEP) amplitudes decreasing as postural difficulty increases. Individuals with Parkinson’s disease (PD) show impaired sensory gating, with elevated SEP amplitudes that are not appropriately modulated by increasing postural demands. Despite comparable postural sway to healthy older adults, the PD group exhibited fundamentally different neurophysiological responses to balance challenges. This dissociation between motor performance and neurophysiology indicates a primary deficit in cortical sensory processing in PD. Impaired sensory gating may reflect a key, independent contributor to postural instability in PD, highlighting the need to target sensory deficits in treatment.

Transcranial Direct-Current Stimulation (tDCS), as a safe and non-invasive neuromodulator, has been recently the center of attention for the treatment and management of neurological disorders. However, the intervening mechanisms of tDCS are not completely understood, and in consequence, it was not possible or advisable to utilize it as an effective treatment. In this work, by integrating a neural mass model of the thalamocortical system, which can generate and induce different types of seizures, and the physiological aspects of the interaction between tDCS and the brain, such as permissible current and how it must be involved in different neural populations, we have proposed a basic model. Then, by connecting several units of the basic model and applying a learning rule to calculate properly the connectivity weights between units, a multi-zone model is established. Our simulation results explained the ever-increasing connectivity between pre-and post-stimulation, an accepted feature of tDCS. Then, we described computationally (based on bifurcation analysis) how this change in connectivity can lead to a reduction in epileptic susceptibility.