Digital-twin optimized transcranial temporal interference electrical stimulation alters rat brain activity patterns and metabolism including deep structures

Authors

Wenk, P., Ahmadi, K., Mertens, D., Akter, F., Kalantari, A., Michalek, A., Zaehle, T., Aswendt, M., Ruhnau, P., Findeisen, R., Budinger, E.

Abstract

Non-invasive deep-brain stimulation (DBS) using transcranial alternating current stimulation (tACS) with temporal interference (TI) has emerged as a promising approach for therapeutic applications in motor and neuropsychiatric disorders. Here, we present a preclinical TI tACS protocol for adult rats that follows a systems approach: an anatomically realistic finite-element digital twin of the rat head is used to optimize electrode placement and injected currents for a deep target, and the model predictions are then tested in vivo. We combine, minimal invasive TI tACS with functional MRI (fMRI) to characterize stimulation-related brain-wide neural responses, alterations in functional connectivity, and changes in neurotransmitter levels. The optimized montage targeted in particular the ventral (motor-related) thalamus. Stimulation-evoked fMRI revealed robust bilateral activation across both subcortical and cortical regions, such as the thalamus, hippocampus, amygdala, retrosplenial and anterior cingulate cortex, which, in turn, reflects direct and indirect activations of brain circuitries by TI tACS. Changes in the connectivity patterns during resting-state fMRI were limited (e.g., fimbria of the hippocampus), but partially overlapped with regional stimulation-evoked fMRI. Therefore, we assume only a short-term influence of TI on neural networks following a single stimulation. MR spectroscopy indicated a trend towards an increased glutamate/GABA ratio in the thalamus. Overall, we demonstrate that TI is a feasible and effective approach for non-invasive DBS in rodents, and that digital twin-based optimization combined with in vivo validation provides a workflow towards individualized stimulation and a foundation for future mechanistic and translational studies in disease models.

Preprint server: bioRxiv
The authors list and abstract were imported from bioRxiv on 02 Oct 2026.

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