Multi-packet regions in stabilized continuous attractor networks

Authors:
Thomas P. Trappenberg;Dominic I. Standage
Affiliations:
Faculty of Computer Science, 6050, University Avenue, Dalhousie University, Halifax, Canada B3H 1W5;Faculty of Computer Science, 6050, University Avenue, Dalhousie University, Halifax, Canada B3H 1W5
Venue:
Neurocomputing
Year:
2005

Citing 2
Cited 2

Network amplification of local fluctuations causes high spike rate variability, fractal firing patterns and oscillatory local field potentials

Neural Computation
Self-organising continuous attractor networks with multiple activity packets, and the representation of space

Neural Networks

2005 Special Issue: Modelling divided visual attention with a winner-take-all network

Neural Networks - 2005 Special issue: IJCNN 2005
Persistent storage capability impairs decision making in a biophysical network model

Neural Networks

Quantified Score

Hi-index	0.01

Visualization

Abstract

Continuous attractor neural networks are recurrent networks with center-surround interaction profiles that are common ingredients in many neuroscientific models. We study realizations of multiple non-equidistant activity packets in this model. These states are not stable without further stabilizing mechanisms, but we show they can exist for long periods. While these states must be avoided in winner-take-all applications, they demonstrate that multiple working memories can be sustained in a model with global inhibition.