Biology subjects

Baghdadi, G.

Publications and source records attributed to Baghdadi, G..

5 recordsLinked to original sources

bioRxiv2021

The Effect of Attention Load on Balance Control Performance

Posture balance control is an essential ability that is affected by the attention load. We investigated the effect of attention load on posture balance control experimentally and computationally. Fifteen young individuals participated in an experiment containing simultaneous performing of a balance control task and an auditory task. A previous computational model was extended by introducing the effect of attention load as a gain in a Proportional-Integral-Derivative (PID) controller. Results demonstrated that the sensitivity of the posture balance control to the attention load should be considered besides other influential factors in designing sport or physical rehabilitation exercises. Simulations suggested that the issues of joint impedance stiffness or viscosity might also be compensated by changing the attention load.

neuroscience↗

bioRxiv2020

A new Petri Net Model of Working Memory to Predict the Root Causes of Attention Deficit Disorder Symptoms

Working memory is a system that helps us to store, retrieve, and manipulate information for a short period. The improper function of working memory is highly reported in people with attention deficit disorder. Attention deficit disorder is one of the most common disruptive behavioral disorders in children. Finding the actual reasons that may lead to inattentive symptoms is still an enigma for scientists. In this study, a model was proposed to show the flow of information through sensory, long-term, and working memory based on the Petri net approach. A new "selective updating" mechanism is also suggested. It is speculated that the central executive part of working memory uses this mechanism for updating the less important content with new incoming essential inputs. The analysis of the proposed model shows how an abnormality in the time setting or unexpected delays in information transmission may lead to some symptoms of inattention. These predictions about the possible causes of inattentive symptoms would be valuable for psychologists to find new possible treatments. This study also illustrates the great potential of Petri net approach for modeling and analysis of biological systems.

neuroscience↗

bioRxiv2020

Detection of Static, Dynamic, and No Tactile Friction Based on Non-linear dynamics of EEG Signals: A Preliminary Study

Touching an object leads to a frictional interaction between the skin and the object. There are two kinds of friction: the first contact that leads to static friction and the dragging phase that leads to dynamic friction. No study has been performed to show the effect of friction type on EEG signals. The main goal of the current study is to investigate the effect of tactile friction on non-linear features of EEG signals. Participants performed a tactile task that each of its trials had three states: the sensation of 1) static friction, 2) dynamic friction, and 3) no friction. During the experiment, EEG signals were recorded, and different linear and non-linear EEG indices were extracted and analyzed to find the effect of the tactile friction on EEG signals. Linear features such as spectral features were not a good choice to distinguish between the states. However, non-linear features such as Lyapunov exponent, Higuchis dimension, and Hurst exponent had the potential to separate the mentioned states. Results also showed signs of predictability (negative Lyapunov exponent) in the signals recorded during dynamic friction and the existence of long-range dependency (memory) in EEG signals recorded during all states. The complexity of the tactile system in Theta band was also higher than the Delta band. The results of this research not only increase our knowledge about brain non-linear dynamics in response to tactile friction but also lead to a design of a preliminary system that can automatically detect friction between the skin and surfaces.

neuroscience↗

bioRxiv2019

Using the Concepts of Time-delayed Feedback Control in Biofeedback Systems in Children with ADD: A Preliminary Study

The reported efficacy of biofeedback is not consistent across studies. One issue that has not been addressed in previous studies is the effect of the reference signal in a biofeedback system.\n\nWe compared the effects of two different reference signals using a computational model and human experiments. One reference signal was fixed, and the other was variable and was designed based on time-delayed feedback control concepts. The computational model consists of a plant and a controller. Groups of typically developing and children with attention deficit disorder (ADD) participated in our experiments.\n\nThe computational model showed that time-delayed reference feedback control could have more positive effects on the performance than using a fixed reference signal. The model prediction was consistent with the results obtained from the experiments performed on children with ADD. However, in typically developing children, using time-delayed reference feedback control had a negative effect. Our preliminary results, which need to be investigated on more subjects, indicate the importance of selecting the reference signal in biofeedback systems according to the characteristics of each participant. The results remind the importance of \"single-case methodology\" in neurocognitive rehabilitation systems. Using computational concepts, some other predictions have also been provided, which need more investigations.

neuroscience↗

bioRxiv2018

A Modified Hodgkin-Huxley model to Show the Effect of Motor Cortex Stimulation on the Trigeminal Neuralgia Network

BackgroundTrigeminal neuralgia (TN) is a severe neuropathic pain, which has an electric shock like characteristic. There are some common treatments for this pain such as medicine, microvascular decompression or radio frequency. In this regard, transcranial direct current stimulation (tDCS) is another therapeutic method to reduce the pain, which has been recently attracting the therapists attention. The positive effect of tDCS on TN was shown in many previous studies. However, the mechanism of tDCS effect has remained unclear\n\nObjectiveThis study aims to model the neuronal behavior of the main known regions of the brain participating in TN pathways to study the effect of transcranial direct current stimulation\n\nMethodThe proposed model consists of several blocks (block diagram): 1) trigeminal nerve, 2) trigeminal ganglion, 3) PAG (Periaqueductal gray in the brainstem), 4) thalamus, 5) motor cortex (M1) and 6) somatosensory cortex (S1). Each of these components represented by a modified Hodgkin-Huxley (HH) model (a mathematical model). The modification of the HH model was done based on some neurological facts of pain sodium channels. The input of the model is any stimuli to trigeminal nerve, which cause the pain, and the output is the activity of the somatosensory cortex. An external current, which is considered as electrical current, was applied to the motor cortex block of the model\n\nResultThe results showed that by decreasing the conductivity of the slow sodium channels (pain channels) and applying tDCS over the M1, the activity of the somatosensory cortex would be reduced. This reduction can cause pain relief\n\nConclusionThe proposed model provided some possible suggestions about the relationship between the effects of tDCS and associated components in TN, and also the relationship between the pain measurement index, somatosensory cortex activity, and the strength of tDCS.

neuroscience↗