Correlated connectivity and the distribution of firing rates in the neocortex
| dc.creator | Koulakov, Alexei | |
| dc.creator | Hromadka, Tomas | |
| dc.creator | Zador, Anthony M. | |
| dc.date | 2008-09-09 | |
| dc.date.accessioned | 2026-07-07T10:01:47Z | |
| dc.date.available | 2026-07-07T10:01:47Z | |
| dc.description | Two recent experimental observations pose a challenge to many cortical models. First, the activity in the auditory cortex is sparse, and firing rates can be described by a lognormal distribution. Second, the distribution of non-zero synaptic strengths between nearby cortical neurons can also be described by a lognormal distribution. Here we use a simple model of cortical activity to reconcile these observations. The model makes the experimentally testable prediction that synaptic efficacies onto a given cortical neuron are statistically correlated, i.e. it predicts that some neurons receive many more strong connections than other neurons. We propose a simple Hebb-like learning rule which gives rise to both lognormal firing rates and synaptic efficacies. Our results represent a first step toward reconciling sparse activity and sparse connectivity in cortical networks. | |
| dc.identifier | https://arxiv.org/abs/0809.1630 | |
| dc.identifier | http://arxiv.org/abs/0809.1630 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/168748 | |
| dc.subject | Neurons and Cognition | |
| dc.title | Correlated connectivity and the distribution of firing rates in the neocortex | |
| dc.type | text |