Chapter 8 Non-Linear Summation of Synaptic Currents on Spinal Motoneurons: Lessons from Simulations of the Behaviour of Anatomically Realistic Models

Abstract

Publisher Summary The input/output properties of the spinal motoneurons are deceptively simple. As described by Granit, Kernell, and co-workers, the steady-state frequency of action potentials generated by motoneurons—the output—is related to the current reaching the soma because of pre-synaptic activity—the input—in a close to linear manner. This straightforward relationship, however, conceals a large number of nonlinear factors that play critical roles in transforming pre-synaptic activity into trains of action potentials. Some of these factors become more apparent if the input/output function is expanded to include the relationship between the current arriving at the soma by pre-synaptic activity and the magnitude of pre-synaptic activity. This function depends on several factors, such as the frequency of action potentials arriving at synapses on the surface of the motoneuron and the number of active synapses. These factors have the potential to introduce large nonlinearities into the relationship between the level of pre-synaptic activity and the frequency of action potentials generated by motoneurons. The importance of nonlinear summation of synaptic currents in determining the input/output properties of motoneurons is poorly understood. This problem can be partially attributed to the difficulty of measuring the magnitude of the nonlinearity in experimental situations where the precise number and location of active synapses are known. To address this problem, this chapter builds compartmental models of motoneurons, based on detailed measurement of the geometry of their dendritic trees. Simulated synapses on the dendritic trees of these models are activated and the resulting current that reaches the cell body is measured in the chapter. The results of these simulations indicate that a substantial fraction of the current generated by individual synapses is lost because of nonlinear summation.