Computational Modeling of Subdural Cortical Stimulation: A Quantitative Spatiotemporal Analysis of Action Potential Initiation in a High‐Density Multicompartment Model

Objective Computational modeling studies were performed to identify presynaptic elements of cortical neurons that are activated by subdural electrical stimulation. Materials and Methods The computer model consists of layers of multicompartmental neurons arranged in 3D space in an anatomically realistic fashion inside a 4.8 × 4.8 × 3.4 mm volume of gray matter modeled as a homogenous and isotropic medium. The model was subjected to an electric field generated by a circular disk electrode. Results The initiation of presynaptic action potentials ( PAPs ) in neurons takes place predominantly in the axon initial segment ( AIS ) or ectopically in axonal branch terminals. PAPs that were initiated in only one axonal terminal were typically followed by a second PAP (spike duplet) resulting from the activation of the AIS by the antidromically propagating initial PAP . There were significant time delays (up to 0.5 ms) in the propagation of these ectopically initiated PAPs along the axons to nonactivated axonal branches and, associated with these delays, latencies in the occurrence of spike duplets in different axonal terminals. The effect of the dendritic arbor 3D structure on the AIS activation threshold was contingent on whether the net axonal and somato‐dendritic current flows made an antagonistic or synergetic contribution. Conclusions This study examines the effects of subdural electrical stimulation on a high‐density network consisting of several populations of multicompartment cell types. The effect of dendritic arbor structure on the axonal activation threshold is prominent in the case of multipolar neurons with large‐diameter symmetric dendrites (basal/apical) that are oriented parallel to the electric field lines. The timing of presynaptic terminal activation after stimulation is not determined solely by the axonal delay (orthodromic propagation) but depends on the details of the applied stimulation field and axonal branching structure, which may be important factors in characterizing the effects of electrical stimulation in neuromodulation systems.