Dendritic spikes expand the range of well-tolerated population noise structures

Abstract

The brain operates surprisingly well despite the noisy nature of individual neurons. The central mechanism for noise mitigation in the nervous system is thought to involve averaging over multiple noise-corrupted inputs. Subsequently, there has been considerable interest recently to identify noise structures that can be averaged out to preserve reliable signal encoding. By analyzing realistic synaptic integration in biophysically accurate neuronal models, I report a role for a complementary de-noising approach mediated by focal dendritic spikes. Dendritic spikes might seem unlikely candidates for noise reduction due to their miniscule integration compartments and poor averaging abilities. Nonetheless, the extra thresholding step introduced by dendritic spike generation could increase neuronal tolerance for a broad category of noise structures, some of which cannot be resolved well with averaging. Computations with multiple dendritic spikes compensate for compartment size constraints and expand the repertoire of conditions that can be reliably processed by neuronal populations.