ArticleJournal of mathematical neuroscience2018
Investigating the Correlation-Firing Rate Relationship in Heterogeneous Recurrent Networks.
Article in Journal of mathematical neuroscience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Dynamic Hippocampal CA2 Responses to Contextual Spatial Novelty.Frontiers in systems neuroscience · 2022Article
- Article
- Differences in olfactory bulb mitral cell spiking with ortho- and retronasal stimulation revealed by data-driven models.PLoS computational biology · 2021Article
- Optimal Interplay between Synaptic Strengths and Network Structure Enhances Activity Fluctuations and Information Propagation in Hierarchical Modular Networks.Brain sciences · 2020Article
- Efficient calculation of heterogeneous non-equilibrium statistics in coupled firing-rate models.Journal of mathematical neuroscience · 2019Article
- Special Issue from the 2017 International Conference on Mathematical Neuroscience.Journal of mathematical neuroscience · 2019Article
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Authors and funding
2 authors.
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Abstract
The structure of spiking activity in cortical networks has important implications for how the brain ultimately codes sensory signals. However, our understanding of how network and intrinsic cellular mechanisms affect spiking is still incomplete. In particular, whether cell pairs in a neural network show a positive (or no) relationship between pairwise spike count correlation and average firing rate is generally unknown. This relationship is important because it has been observed experimentally in some sensory systems, and it can enhance information in a common population code. Here we extend our prior work in developing mathematical tools to succinctly characterize the correlation and firing rate relationship in heterogeneous coupled networks. We find that very modest changes in how heterogeneous networks occupy parameter space can dramatically alter the correlation-firing rate relationship.
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