Intrinsic Cellular Properties and Connectivity Density Determine Variable Clustering Patterns in Randomly Connected Inhibitory Neural Networks

Frontiers in Neural Circuits - Switzerland
doi 10.3389/fncir.2016.00082
Full Text
Abstract

Available in full text

Date
Authors
Publisher

Frontiers Media SA

Related search

Fully Connected Neural Networks Ensemble With Signal Strength Clustering for Indoor Localization in Wireless Sensor Networks

International Journal of Distributed Sensor Networks
Computer NetworksEngineeringCommunications
2015English

Pseudo Almost-Periodic Solution of Shunting Inhibitory Cellular Neural Networks With Delay

Journal of Applied Mathematics
Applied Mathematics
2011English

Variable Radii Connected Sensor Cover in Sensor Networks

ACM Transactions on Sensor Networks
Computer NetworksCommunications
2009English

Density-Connected Subspace Clustering for High-Dimensional Data

2004English

Intrinsic Connectivity Networks Underlying Individual Differences in Control-Averse Behavior

Human Brain Mapping
Nuclear MedicineRadiologyUltrasound TechnologyAnatomyRadiologicalNeurologyImaging
2018English

Phase Transitions in Dilute, Locally Connected Neural Networks

Physical Review A
1992English

Networks With Lateral Connectivity. I. Dynamic Properties Mediated by the Balance of Intrinsic Excitation and Inhibition

Journal of Neurophysiology
NeurosciencePhysiology
1996English

A Scalable FPGA Architecture for Randomly Connected Networks of Hodgkin-Huxley Neurons

Frontiers in Neuroscience
Neuroscience
2018English

A Survey of Partially Connected Neural Networks

International Journal of Neural Systems
MedicineComputer NetworksCommunications
1997English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2024 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy