Geometrical determinant of nonlinear synaptic integration in human cortical pyramidal neurons

TL;DR

This study reveals that the nonlinear synaptic integration threshold in human cortical pyramidal neurons is geometrically determined by the shortest path distance from synapses to the apical trunk, a fundamental property shared with rodents.

Contribution

It uncovers a linear relationship between synaptic distance and integration nonlinearity threshold, highlighting a universal geometric rule in pyramidal neurons across species.

Findings

Nonlinearity threshold linearly depends on synaptic distance from the soma.

Similar rules are observed in both human and rodent pyramidal neurons.

Tumor or epilepsy alters membrane properties but preserves the geometric relationship.

Abstract

Neurons integrate synaptic inputs and convert them to action potential output at electrically distant locations. The computational power of a neuron is hence enhanced by subcellular compartmentalization and nonlinear synaptic integration, but the biophysical determinants of these features in human neurons are not completely understood. By examining the synaptic input-output function of human neocortical pyramidal neurons, we found that the nonlinearity threshold at the soma was linearly determined by the shortest path distance from the synapse to the apical trunk, and the slope of this relationship was consistent throughout the dendritic arbor. Analogous rules were found from both supragranular and infragranular layers of the rodent cortex, suggesting that these represent a fundamental property of pyramidal neurons. Additionally, we found that neurons associated with tumor or epilepsy had distinct membrane properties, but the nonlinearity threshold was shifted in amplitude such that the slope of its relationship with synaptic distance remained consistent.