Biological Systems Modeling
Hossein Banki-Koshki; Seyyed Ali Seyyedsalehi
Volume 17, Issue 2 , September 2023, , Pages 100-110
Abstract
Neuronal synchronization as a significant cognitive phenomenon of the human brain, has attracted the interest of neuroscience researchers in recent years. This phenomenon is generally investigated in discrete and continuous neuronal models or experimentally recorded signals of the brain. In this study, ...
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Neuronal synchronization as a significant cognitive phenomenon of the human brain, has attracted the interest of neuroscience researchers in recent years. This phenomenon is generally investigated in discrete and continuous neuronal models or experimentally recorded signals of the brain. In this study, for the first time, we investigate the weight synchronization instead of neuronal synchrony, in the training step of the artificial feedforward neural networks. The findings of the study show that the generalized weight synchronization occurs both during the training mode and in the non-training mode. Furthermore, as the training is completed, the synchronization increases between the weights. In this study, a new method is introduced in order to detect synchrony patterns using signal derivative and hierarchical clustering. We have also presented a criterion to quantify weight synchronization in different layers of the neural network. Accordingly, the results demonstrate that the lower layers of the network have a significantly higher level of weight synchrony than the upper layers.
Biological Systems Modeling
Arman Marzban; Elham Amini Boroujeni
Volume 16, Issue 4 , March 2023, , Pages 31-40
Abstract
Considering that mathematical modeling is helpful in describing and analyzing the behavior of epidemic diseases. On the other hand, the accuracy and degree of freedom in modeling fractional order systems are more than that of integer order systems due to the presence of long-term memory property. This ...
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Considering that mathematical modeling is helpful in describing and analyzing the behavior of epidemic diseases. On the other hand, the accuracy and degree of freedom in modeling fractional order systems are more than that of integer order systems due to the presence of long-term memory property. This paper extends the existing integer order model of Covid-19 disease to fractional order systems using fractional order calculations.The proposed model’s positivity and bounded answers are proved using the invariant region theorem. Using the fixed point theory in Banach space, the existence and uniqueness of the solution of the proposed fractional order model are proved. The behavior of both integer and fractional order has been simulated and evaluated using real information published for Covid-19 in Thailand. The higher efficiency and accuracy of the proposed model of fractional order are confirmed in the simulation results.keywords: Covid-19, Fractional order Calculus, Mathematical modeling, The existence and uniqueness of the answer
Biological Systems Modeling
Mohsen Kamelian Rad; Mohammad Ali Ahmadi Pajouh; Mehrdad Saviz
Volume 15, Issue 2 , August 2021, , Pages 175-186
Abstract
Transcutaneous electrical stimulation of peripheral nerve fibers has always been an important field of research. Many studies indicate the possibility to block the conduction of nerve fibers by using high frequency alternating currents (HFAC). According to the fact that the stimulation of narrower fibers ...
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Transcutaneous electrical stimulation of peripheral nerve fibers has always been an important field of research. Many studies indicate the possibility to block the conduction of nerve fibers by using high frequency alternating currents (HFAC). According to the fact that the stimulation of narrower fibers is always accompanied by activation of thicker fibers, in this study, current regions for selective stimulation of different nerve fibers without activating other fibers have been obtained. This success is achieved through the nerve conduction block using HFAC (5-20 KHz). Stimulation current regions is a part of the intensity-frequency diagram which by choosing the excitation parameters in this area, only some target fibers are stimulated according to their diameters. The McIntyre nerve fiber model was used to perform these simulations; The sodium-potassium pump model has also been added to it and its effects have been investigated. A unipolar electrode is considered which acts as a point current source at different distances from the nerve fibers, and selective excitation spaces are obtained for the Aδ and Aβ fibers. The appropriate frequency range for excitation of different fibers is 5 kHz and above, while the desired current for selective excitation of Aδ and Aβ fibers is given by two polynomial equations of order 2 and 3, respectively, which are fitted to the middle of selective parameter space of each nerve fiber. Also, the excitation current varies from about 0.8 to 1.8 mA for Aδ fibers and from about 0.55 to 0.95 mA for Aβ fibers. In all of the simulations mentioned in this article, the sinusoidal waveform is used.
Biological Systems Modeling
Seyede Fatemeh Ghoreishian Amiri; Mohammad Pooyan
Volume 14, Issue 4 , February 2021, , Pages 321-331
Abstract
Parkinson's disease (PD) is a neurological disorder that mainly affects dopamine-producing neurons and motor system. The most obvious symptoms of PD are tremor, slow movement, stiffness and difficulty with walking. Walking in PD is slower than normal walking. In this paper, the gait in patients ...
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Parkinson's disease (PD) is a neurological disorder that mainly affects dopamine-producing neurons and motor system. The most obvious symptoms of PD are tremor, slow movement, stiffness and difficulty with walking. Walking in PD is slower than normal walking. In this paper, the gait in patients with PD is modeled by a mathematical and computational method. This model includes structures which are involved in PD, such as basal ganglia, thalamus, cortex, supplementary motor area (SMA), muscle and joint-load dynamics. The output of the model is walking speed in PD. The output value is 0.83 m/s, which is in the range reported by clinical results (0.18-1.21 m/s). Some methods which increase the gait speed in PD are investigated too. These methods include deep brain stimulation, drug prescription and strengthening the muscles. The results show that each of these methods will improve the gait speed, in fact, by using these methods, the value of output increases and approaches the walking speed range in healthy individuals (1.36-1.30 m/s). Moreover, the effect of rigidity on gait speed is studied; it has been observed that the stiffness and speed of the gait are inversely related. Finally a control method is offered which improve the gait speed by increasing the magnitude response of the closed-loop system.
