Computational Modeling of Transcranial Electric Stimulation in Anemic Conditions: A Hodgkin-Huxley and Finite Element Analysis

Computational models of tES typically assume normal physiological conditions. The effect of systemic metabolic disorders like anemia on tES efficacy remains unexplored. This study investigates the effects of transcranial electric stimulation (tES) on neuronal firing rates discussing a computational model that can be integrated to high-resolution MRI data and intracranial field measurements.Here, a combined Finite Element Method (FEM) and Hodgkin-Huxley (H-H) model was developed to investigate how anemia-induced ionic alterations modulate neuronal responses to tDCS and tACS. By applying principles of quasi-static electromagnetic fields within the FEniCS platform for computational modeling, and utilizing frequency and conductances within Hodgkin-Huxley model parameters in the context of anemia, it was shown that low-intensity tES can significantly modulate neuronal activity in the motor cortex and hippocampus.Under low-intensity tDCS, our model predicted a 20% change in neuronal firing in anemic conditions compared to control. The results align with previous research, suggesting the potential of tES to enhance synaptic plasticity and cognitive functions, particularly in conditions such as Alzheimer’s disease.Our framework provides a foundation for personalizing tES parameters for patients with comorbid anemia. This research underscores the importance of computational modeling in predicting the neuromodulatory effects of tES and highlights the need for further cognitive neuroscience studies in anemia to explore the long-term impacts and underlying mechanisms of these effects.