Analysis of phase transitions in KIV with amygdala during simulated navigation control

Author

Kozma, Robert ; Myers, Mark

Author_Institution

Div. of Comput. Sci., Memphis Univ., TN, USA

Volume

1

fYear

2005

fDate

31 July-4 Aug. 2005

Firstpage

125

Abstract

A biologically inspired dynamical neural network model called KIV is used in this work to design autonomous agents. The KIV set models the vertebrate limbic system. Previous studies indicated that KIV is able to provide a control algorithm for navigation and decision-making for autonomous mobile agents. In this work we use Hilbert transform to capture global synchronized spatio-temporal patterns of amplitude modulation in KIV. We identify phase transition in the simulated amygdala and show that it shares several important features of EEC signals.

Keywords

Hilbert transforms; mobile robots; navigation; neurocontrollers; EEC signals; Hilbert transform; KIV; amplitude modulation; amygdala; autonomous agents; autonomous mobile agents; decision making; dynamical neural network model; global synchronized spatio-temporal patterns; navigation control; phase transitions; vertebrate limbic system; Analytical models; Animals; Biological system modeling; Brain modeling; Chaos; Computational modeling; Computer science; Electroencephalography; Frequency synchronization; Navigation;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 2005. IJCNN '05. Proceedings. 2005 IEEE International Joint Conference on

Print_ISBN

0-7803-9048-2

Type

conf

DOI

10.1109/IJCNN.2005.1555817

Filename

1555817