Research Publications

Introduction For many neuroprosthetic devices, strength-duration curves indicate that the total injected charge determines the response of neurons to electrical stimulation. However, when pulse duration is much longer than the chronaxie of the strength-duration curve, this relationship breaks down. Instead, the neural response is dominated by the electric field across the neuron. We show that the chronaxie depends on a number of factors including the mode of stimulation (longitudinal/transverse), the electrode-neuron separation and neuron-dependent factors. In some cases the chronaxie is much shorter than commonly used pulse durations, implying that under certain conditions the electric field is the dominant factor in stimulating a neuron. Methods We derived an analytic expression for the neural response to electrical stimulation, taking into account longitudinal and transverse modes of stimulation. This solution relates the parameters of the stimulation waveform to the neuron properties including its diameter, width of the extracellular space, intracellular and extracellular resistivity, membrane resistance, membrane capacitance, and electrode-neuron separation. We investigated the validity of the analytic expression using finite element analysis. Results The results give two time constants for membrane depolarisation: a longitudinal time constant, L (≈0.1-10ms), and a transverse time constant, T (0.1-10s). For extremely short pulse durations (T<T), depolarisation is capacitive and thus depends on charge. For extremely long pulse durations (T>L), depolarisation is resistive and thus depends on electric field. For intermediate (typical) pulse durations, depolarisation is related to either charge or electric field depending on whether the longitudinal or transverse mode is dominant. Conclusion These results give insight into the biophysics of electrical stimulation and provide a basis for understanding how electrical stimulus parameters affect neural response. Funding source This research was supported by the Australian Research Council (ARC) through its Special Research Initiative (SRI) in Bionic Vision Science and Technology grant to Bionic Vision Australia (BVA).