Intentional Navigation and Phase Transition Analysis in Amygdala of KIV Model 2005-01-3381
Previous study on the KIV model proved that it is feasible to extract information from the amygdala for navigation tasks. In this work, we observed the chaotic dynamics of the KIV model by analyzing the global phase transitions that occur in the amygdala. By using the Hilbert transform, we are able to capture the fast global synchronized spatial patterns of amplitude modulation (AM) in the Amygdala. The ultimate goal for identifying the phase transition within the amygdala is to aid the system for decision-making while navigating in a challenging environment with an intentional behavior. In this paper, we will concentrate on the phase transition analysis in the amygdala of the KIV model. Our experiment has shown the detection of phase transition in the amygdala can be done by Hilbert transform.
Citation: Wong, M., Myers, M., Kozma, R., Demir, R. et al., "Intentional Navigation and Phase Transition Analysis in Amygdala of KIV Model," SAE Technical Paper 2005-01-3381, 2005, https://doi.org/10.4271/2005-01-3381. Download Citation
Author(s):
Ming Chuen (Derek) Wong, Mark Myers, Robert Kozma, R. Murat Demir, Rajkumar Thirumalainambi
Affiliated:
Division of Computer Science, Mathematics department, The University of Memphis
Pages: 8
Event:
Aerospace Technology Conference and Exposition
ISSN:
0148-7191
e-ISSN:
2688-3627
Also in:
SAE 2005 Transactions Journal of Aerospace-V114-1
Related Topics:
Navigation and guidance systems
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