Biology subjects

Jamali, Y.

Publications and source records attributed to Jamali, Y..

3 recordsLinked to original sources

bioRxiv2023

Criticality and partial synchronization analysis in Wilson-Cowan and Jansen-Rit neural mass models

Synchronization is a phenomenon observed in neuronal networks involved in diverse brain activities. Neural mass models such as Wilson-Cowan (WC) and Jansen-Rit (JR) manifest synchronized states. Although they have been studied for decades, their ability to demonstrate second-order phase transition (SOPT) and criticality has not received enough attention, which serves as candidates for the development of healthy brain networks. In this study, two networks of coupled WC and JR nodes with small-world topologies were constructed and Kuramoto order parameter (KOP) was used to quantify the amount of synchronization. In addition, we investigated the presence of SOPT using the synchronization coefficient of variation. Both networks reached high synchrony by changing the coupling weight between their nodes. Moreover, they exhibited abrupt changes in the synchronization at certain values of the control parameter not necessarily related to a phase transition. While SOPT was observed only in JR model, neither WC nor JR model showed power-law behavior. Our study further investigated the global synchronization phenomenon that is known to exist in pathological brain states, such as seizure. JR model showed global synchronization, while WC model seemed to be more suitable in producing partially synchronized patterns. Corresponding author summaryYousef Jamali received his M.Sc. degree in physics from Sharif University, Tehran, Iran, in 2004, and his Ph.D. degree in physics from Sharif University, Tehran, Iran, in 2009. After finishing his Ph.D. thesis, in 2009, he got two years postdoctoral research associate position at the University of California at Berkeley, Department of Bioengineering. He is currently an Associate Professor in the Applied Mathematics Department (Biomathematics division), at Tarbiat Modares University, Tehran, Iran. His current research interests include the interdisciplinary area of the complex system especially on the modeling of brain. In fact, his interests are how the brain works at the critical state and how this complex system synchronized under different conditions.

neuroscience↗

bioRxiv2019

A new method of brain stimulation at ultra-high frequency

Nerve stimulation via micro-electrode implants is one of the neurostimulation approaches which is used frequently in the medical treatment of some brain disorders, neural prosthetics, brain-machine interfaces and also in the cyborg. In this method, the electrical stimulation signal can be categorized by the frequency band: low frequency, high frequency, and ultra-high frequency. The stimulation should be less destructive, more smooth, and controllable. In this article, we present a brief description of the mechanism underlying the ultra-high frequency stimulation. In the flowing, from an informatics perspective, we propose a state-of-the-art, low destructive, and highly efficient stimulation method at the low amplitude ultra-high frequency signal. In this method, we have tried to reduce the adaptation of the nerve system by modulating the stimulation signal via a low frequency rectangular random wave. By this method, we could reach the \"almost zero discharge\" with minimum destructive effect in the experimental test on the fish nervous system.

neuroscience↗

bioRxiv2019

Theory of cyborg: a new approach to fish locomotion control

Cyborg in the brain-machine interface field has attracted more attention in recent years. To control a creature via a machine called cyborg method, three stages are considerable: stimulation of neurons, neural response, and the behavioral reaction of the subject. Our main concern was to know how electrical stimulation induces neural activity and leads to a behavioral response. Additionally, we were interested to explore which type of electrical stimulation is optimal from different aspects such as maximum response with minimum induction stimulus field, minimum damage of the tissue and the electrode, reduction of the noxiousness of stimuli or pain in the living creature. In this article, we proposed a new model for the induction of neural activity led to locomotion responses through an electrical stimulation. Furthermore, based on this model, we developed a new approach of electrical neural stimulation to provide a better locomotion control of living beings. This approach was verified through the empirical data of fish cyborg. We stimulated the fish brain by use of an ultra-high frequency signal which careered by a random low frequency. According to our model, we could control the locomotion of fish in a novel and innovative way. In this study, we categorized the different cyborg methods based on the nervous system areas and the stimulation signal properties to reach the better and optimal behavioral control of creature. According to this, we proposed a new stimulation method theoretically and confirmed it experimentally.

bioengineering↗