Abstract:
The swift evolution of biofeedback control has opened up new voyages in
the field of biomedical engineering and provides powerful perspective to
researchers for viewing many real problems such as tumor, surgeries of sensitive
parts of body, control of glucose level of a patient, heart diseases and brain
disorders associated with humans. Consequently, mysterious and intricate
biological phenomena can now be studied and investigated by utilizing the
knowledge of control and nonlinear dynamics of physical systems. The emerging
theory of biofeedback control can be more fruitful for understanding the brain
functioning in order to cope with various neural disorders. Neuron, being an
innate sophisticated structural entity of nervous system, plays an imperative role
owing to its chief biophysical features and key mechanism of operations, for
effective transmission of neuronal signals to the brain and the muscles. The probe
of neuron doctrine gives an insight into understanding of brain information
processing and information transmittance among neurons which may further
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corroborate a close relevance between the synchronization of neural systems and
the information of cerebral process. Thus, neuronal synchronization under deep
brain stimulation has become a potential application in the study of clinical
treatment mechanisms for neurodegenerative disorders. Moreover, the famous
FitzHugh-Nagumo (FHN) model under external electrical stimulation (EES; e.g.
deep brain stimulation), is extensively used as synchronization study tool for its
utility in symbolizing the dynamical behavior of neurons. The embryonic impact
of biofeedback control in improving external therapies for patients suffering
cognitive disorders such as Parkinson’s disease, epilepsy and dystonia is the main
motivation to this research work.
“This thesis presents an efficient novel mechanism for synchronization of two
different, chaotic and distant coupled neurons with unknown parameters
subjected to external electrical stimulation and disturbances”
This research investigates the chaotic behavior and synchronization of two
different coupled chaotic FitzHugh-Nagumo (FHN) neurons with unknown
parameters under external electrical stimulation (EES). The coupled FHN neurons
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of different parameters admit unidirectional and bidirectional gap junctions in the
medium between them. Dynamical properties, such as increase in synchronization
error as a consequence of the deviation of neuronal parameters for unlike neurons,
the effect of difference in coupling strengths caused by the unidirectional gap
junctions, and the impact of large time-delay due to separation of neurons, are
studied in exploring the behavior of the coupled system. A novel integral-based
nonlinear adaptive control scheme to cope with infeasibility of the recovery
variable, for synchronization of two coupled delayed chaotic FHN neurons of
different and unknown parameters under uncertain EES is derived. Further, to
guarantee robust synchronization of different neurons against disturbances, the
proposed control methodology is modified to achieve the uniformly ultimately
bounded synchronization. The parametric estimation errors can be reduced by
selecting suitable control parameters. The effectiveness of the proposed control
scheme is illustrated via simulation results.
Keywords: Chaos synchronization; FitzHugh-Nagumo model; External electrical
stimulation; Robust adaptive control; Lyapunov function.