Find models by
Find models for
Find models of
Distinct integration properties of noisy inputs in active dendritic subunits (Poleg-Polsky 2019)
Download zip file
Help downloading and running models
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 integrated linearly in a way that preserves reliable signal encoding. By analyzing realistic synaptic integration in biophysically accurate neuronal models, I report a complementary de-noising approach that is mediated by focal dendritic spikes. Dendritic spikes might seem to be 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 increases neuronal tolerance for a broad category of noise structures, some of which cannot be resolved well with averaging. This property of active dendrites compensates for compartment size constraints and expands the repertoire of conditions that can be processed by neuronal populations.
Poleg-Polsky A (2019) Dendritic spikes expand the range of well-tolerated population noise structures.
(Click on a link to find other models with that property)
Neuron or other electrically excitable cell;
Neocortex L2/3 pyramidal GLU cell;
Neocortex primary motor area pyramidal layer 5 corticospinal cell;
Polsky, Alon [alonpol at tx.technion.ac.il];
for information about:
Neocortex L2/3 pyramidal GLU cell
Other models using layer_5.hoc:
Effects of neural morphology on global and focal NMDA-spikes (Poleg-Polsky 2015)
Other models using mosinit.hoc:
Multiplication by NMDA receptors in Direction Selective Ganglion cells (Poleg-Polsky & Diamond 2016)
NMDA spikes in basal dendrites of L5 pyramidal neurons (Polsky et al. 2009)
File not selected
<- Select file from this column.