DOI: 10.1371/journal.pcbi.1014895 ISSN: 1553-7358

Cell-type dependence of effects from transcranial electric brain stimulation

Susanne Dahle, Gaute T. Einevoll, Torbjørn V. Ness
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There is an urgent need for better treatment options for many neurological conditions, including Alzheimer’s disease, Parkinson’s disease, depression, and epilepsy. Transcranial electrical stimulation (tES) is a non-invasive, safe, inexpensive, and promising method that could address some of this unmet need. The therapeutic value of tES has been well demonstrated, but the effect is highly variable. To enable tES to reach its full potential requires a better understanding of how tES modulates neural activity so that tES treatments can be tailored to specific neurological conditions and individual patients. The neural response to tES is, however, highly complex, and the parameter space involved in optimizing tES treatments is daunting. This has made it difficult to obtain general insights into how tES modulates neural activity, and a central challenge lies in the cell-type-specific and frequency-dependent nature of these responses. In this study, we investigated cell-type-specific neuronal responses to tES over a broad frequency range, using a large database of biophysically detailed neuron models. We found that pyramidal cells respond strongly to low-frequency tES, but their responses drop sharply with frequency. In contrast, inhibitory neurons show a smaller reduction and, on average, become more responsive than pyramidal cells above

~ 60
Hz. By leveraging a reciprocity theorem we demonstrated that the effect of tES on a given cell-type is proportional to the frequency-dependent current-dipole moment that determines the EEG-signal contribution of this cell-type. We further identified the dendritic asymmetry as key in determining tES responses across the frequency spectrum. Counterintuitively, we also found that while total cell length increases tES sensitivity at low frequencies, it can have the opposite effect at high frequencies. Furthermore, we derived an analytical formula for idealized neuron models which can approximately predict the tES sensitivity of different cell types at any given frequency. By characterizing the role of morphology and stimulation frequency in determining tES responses of single cells, this is an important step towards a better understanding of tES at the fundamental level. These results also provide an efficient and accurate method for characterizing and comparing the tES responses of different neural populations across the frequency spectrum, which facilitates optimizing tES for cell-type specific targeting.

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