The measurement of the neural activation dynamics, e.g., the membrane time constant, finds applications for studying brain functions, diagnosis, and treatment of neurological and psychiatric disorders.
Traditionally, the membrane time constant is estimated by using strength-duration (SD) curves, which illustrate interdependencies between threshold stimulus strength and duration in activating the nerve. However, acquiring a SD curve requires an offline measurement of motor thresholds at multiple pulse durations, which is a time consuming process and records data blindly before they are analyzed.
This paper proposes a tool for online sequential parameter estimation of neural dynamics and input-output curves with closed-loop controllable transcranial magnetic stimulation (cTMS), based on Fisher information optimization. It is shown that the membrane time constant and coupling gain could be estimated with a satisfactory level of estimation by acquiring two IO curves at two different pulse widths. The proposed SPE technique results in a more accurate estimation, compared to that obtained from a SD curve with two pulse widths.