Biology subjects

Towhidkhah, F.

Publications and source records attributed to Towhidkhah, F..

9 recordsLinked to original sources

bioRxiv2025

Effects of Visual Deprivation on Gait Stability During Treadmill Walking: Insights from a Bipedal Model

Walking, a fundamental daily activity, relies on sensory input from the somatosensory, visual, and vestibular systems, with vision playing a key role in providing information. When vision is impaired, individuals adjust their walking patterns to maintain stability. This study developed a simplified sagittal model to examine how visual deprivation affects treadmill walking at a controlled speed while ensuring dynamic stability. The model provides a framework for exploring outcomes that are challenging to assess experimentally. We hypothesized that the model would align with experimental data on step frequency, step length, and stability while predicting the steps that could lead to falls without vision. This study presents a bipedal model with two degrees of freedom, controlled by a hierarchical system. Two bio-inspired constraints were implemented: a speed constraint to match with treadmill pace, and a stability constraint to maintain walking stability. The weight of the feedback signal related to joint angles was modified to simulate vision loss. Visual deprivation increased step frequency and decreased step length to prevent falls. Additionally, prolonged deprivation led to step length fluctuations and increased constraint errors, ultimately causing falls. These findings align with human data, validating the potential of the model for rehabilitation research in individuals with visual impairments.

bioengineering↗

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

Group and Individual Level Variations between Symmetric and Asymmetric DLPFC Montages for tDCS over Large Scale Brain Network Nodes

Two challenges to optimizing transcranial direct current stimulation (tDCS) are selecting between, often similar, electrode montages and accounting for inter-individual differences in response. These two factors are related by how tDCS montage determines current flow through the brain considered across or within individuals. MRI-based computational head models (CHMs) predict how brain anatomy determine electric field (EF) patterns for a given tDCS montage. Because conventional tDCS produces diffuse brain current flow, stimulation outcomes may be understood as modulation of global networks. Therefore, we developed network-led, rather than region-led, approach. We specifically considered two common frontal tDCS montages that nominally target the dorsolateral prefrontal cortex; asymmetric unilateral (anode/cathode: F4/Fp1) and symmetric bilateral (F4/F3) electrode montages. CHMs of 66 participants were constructed. We showed that cathode location significantly affects EFs in the limbic network. Furthermore, using a finer parcellation of large-scale networks, we found significant differences in some of main nodes within a network, even if there is no difference at the network level. This study generally demonstrates a methodology for considering the components of large-scale networks in CHMs instead of targeting a single region and specifically provides insight into how symmetric vs asymmetric frontal tDCS may differentially modulate networks across a population.

bioengineering↗

bioRxiv2019

A simple CPG-based model to generate human hip moment pattern in walking by generating stiffness and equilibrium point trajectories

Equilibrium point hypothesis (its developed version named as referent control theory) presents a theory about how the central nerves system (CNS) generates human movements. On the other hand, it has been shown that nerves circuits known as central pattern generators (CPG) likely produce motor commands to the muscles in rhythmic motions. In the present study, we designed a bio-inspired walking model, by coupling double pendulum to CPGs that produces equilibrium and stiffness trajectories as reciprocal and co-activation commands. As a basic model, it is has been shown that this model can regenerate pattern of a hip moment in the swing phase by high correlation ({rho} = 0.970) with experimental data. Moreover, it has been reported that a global electromyography (EMG) minima occurs in the mid-swing phase when the hip is more flexed in comparison with the other leg. Our model showed that equilibrium and actual hip angle trajectories match each other in mid-swing, similar to the mentioned posture, that is consistent with previous findings. Such a model can be used in active exoskeletons and prosthesis to make proper active stiffness and torque.

bioengineering↗

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↗

bioRxiv2019

Hip retraction enhances walking stability on a ramp: an equilibrium point hypothesis-based study

Hip retraction is a phenomenon observed in human walking. The swing leg rotates backward at the end of the motion. Its positive effect on motion stability was reported in the literature based on some simple models for running or walking. In this study, it is shown that hip retraction angle increases in humans during their ascending and descending walk on a stair. In previous studies, hip retraction was modeled by defining a proper motion for the swing leg. According to the equilibrium point hypothesis, the central nervous system (CNS) defines only the equilibrium point(s) and stiffness(es) for body joint(s) to control the human motion. Human body motion emerges as its natural response as a result of the external forces and the defined equilibrium points of joints. Considering the hip torque as a spring-like model with an equilibrium point and stiffness, this study revealed that the hip retraction can be generated by the natural response of the swing leg. Besides, the stabilizing effect of hip retraction was demonstrated by a model for humans ascending and descending walking on a ramp with a range of positive and negative angles, respectively. The findings suggest that the CNS needs to define equilibrium point just ahead of the stance leg to take advantage of the hip retraction effect on ascending and descending walks on a ramp.

bioengineering↗

bioRxiv2018

The accuracy of estimating time to contact in transversal motion and head-on motion

The ability to estimate precisely the time to contact (TTC) of the objects is necessary for planning actions in dynamic environments. TTC estimation is involved in many everyday activities with different levels of difficulty. Although tracking a ball that moves at a constant speed and estimating the time it reaches a non-moving target can be fairly simple, tracking a fast moving car with inconsistent speeds and estimating the time it reaches another car is rather difficult. In this study, we asked participants to estimate TTC of an object in transversal and head-on motions. The object became invisible shortly after movement initiation. The results demonstrated that TTC estimation for transversal motion is more accurate than for head-on motion. We present a mathematical model to explain why humans are better in estimating TTC for transversal motion than for head-on motion.

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↗

bioRxiv2018

Drift-diffusion explains response variability and capacity for tracking objects

1.Being able to track objects that surround us is key for planning actions in dynamic environments. However, rigorous cognitive models for tracking of one or more objects are currently lacking. In this study, we asked human subjects to judge the time to contact (TTC) a finish line for one or two objects that became invisible shortly after moving. We showed that the pattern of subject responses had an error variance best explained by an inverse Gaussian distribution and consistent with the output of a biased drift-diffusion model. Furthermore, we demonstrated that the pattern of errors made when tracking two objects showed a level of dependence that was consistent with subjects using a single decision variable for reporting the TTC for two objects. This finding reveals a serious limitation in the capacity for tracking multiple objects resulting in error propagation between objects. Apart from explaining our own data, our approach helps interpret previous findings such as asymmetric interference when tracking multiple objects.

neuroscience↗