Yashar Sarbaz

University of Tabriz, Tebriz, East Azarbaijan, Iran

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Publications (26)34.78 Total impact

  • Samira Abbasi, Ataollah Abbasi, Yashar Sarbaz
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    ABSTRACT: Purkinje neurons are the sole output neuron of the cerebellar cortex, and they generate high-frequency action potentials. Electrophysiological dysfunction of Purkinje neurons causes cerebellar ataxia. Mutant med mice have the lack of expression of the Scn8a gene. This gene encodes the NaV1.6 protein. In med Purkinje neurons, regular high-frequency firing is slowed, and med mice are ataxic. The aim of this study was to propose the neuroprotective drugs which could be useful for ataxia treatment in med mice, and to investigate the neuroprotective effects of these drugs by simulation. Simulation results showed that Kv4 channel inhibitors and BK channel activators restored the normal electrophysiological properties of the med Purkinje neurons. 4-Aminopyridine (4-AP) and acetazolamide (ACTZ) were proposed as neuroprotective drugs for Kv4 channel inhibitor and BK channel activator, respectively.
    Computer methods and programs in biomedicine 11/2013; · 1.56 Impact Factor
  • Yasaman Vaghei, Yashar Sarbaz, Ahmad Ghanbari
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    ABSTRACT: The Lotka-Volterra or predator-prey models contain a pair of first order, non-linear, differential equations, which describe the dynamics of two species interaction in biological systems. Hence, accurate simulation strategies development for mentioned equations is crucial. In this paper, first, the presented model equations are simulated by ARX, ARMAX and BJ parametric models of the Identification Toolbox in MATLAB software. Afterwards, this simulation has been done in the Neural Network Toolbox by Feed-Forward and Elman networks with equal number of neurons, layers and same transfer functions. Finally, the results of these two simulations have been compared to introduce the best simulation methodology. It is shown that more accurate results are achieved by Elman network. In addition, the paper demonstrates that the simulation error can be decreased by simply increasing the number of these neural networks’ neurons.
    ASME 2013 International Mechanical Engineering Congress and Exposition; 11/2013
  • Samira Abbasi, Ataollah Abbasi, Yashar Sarbaz
    The Journal of neuropsychiatry and clinical neurosciences 10/2013; 25(4):E41. · 2.34 Impact Factor
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    ABSTRACT: Parkinson's disease (PD) is a widespread progressive neural degenerative disease. Patients encounter problems in carrying out ordinary voluntary movements such as gaiting and writing. Effects of tremor, rigidity, and bradykinesia are seen in writing. Since the diagnosis of PD is based on the presence of cardinal symptoms, therefore voluntary movements like writing could be helpful as an indicator in this process. Handwriting analysis can be a suitable method to separate patients from normal individuals. We recorded handwriting data from 17 normal and 13 PD subjects, and then used mathematical analysis in order to extract proper features. At the end of the study, we used these selected features in a classifier. We achieved 93.89% accuracy in the test phase. Hence, this tool may be aid in the diagnosing of both PD and suspected PD individuals in the early stages of the disease.
    Journal of Mechanics in Medicine and Biology 05/2013; 13(03). · 0.76 Impact Factor
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    Samira Abbasi, Ataollah Abbasi, Yashar Sarbaz
    5th International Conference of Cognitive Science (ICCS 2013), Tehran, Iran; 05/2013
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    ABSTRACT: This work proposes feature extraction of lung sounds using wavelet coefficients and their classification by neural network and support vector machines. The lung sounds were classified into 6 classes. The results stated the advantages of a support vector machines for the classification of normal and abnormal lung sounds, and indicated that SVMs are a highly successful classifier with accuracy about 93.51 - 100 for classification of lung sounds.
    2013 21st Iranian Conference on Electrical Engineering (ICEE); 01/2013
  • The Journal of neuropsychiatry and clinical neurosciences 06/2012; 24(3):10010. · 2.34 Impact Factor
  • The Journal of neuropsychiatry and clinical neurosciences 06/2012; 24(3):10048. · 2.34 Impact Factor
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    ABSTRACT: Some previous studies have focused on chaotic properties of Parkinson's disease (PD). It seems that considering PD from dynamical systems perspective is a relevant method that may lead to better understanding of the disease. There is some ambiguity about chaotic nature in PD symptoms and normal behaviour. Some studies claim that normal gait has somehow a chaotic behaviour and disturbed gait in PD has decreased chaotic nature. However, it is worth noting that the basis of this idea is the difference of fractal behaviour in gait of normal and PD patients, which is concluded from Long Range Correlation (LRC) indices. Our primary calculations show that a large number of normal persons and patients have similar LRC. It seems that chaotic studies on PD need a different view. Because of short time recording of symptoms, accurate calculation of chaotic features is tough. On the other hand, long time recording of symptoms is experimentally difficult. In this research, we have first designed a physiologically plausible model for normal and PD gait. Then, after validating the model with neural network classifier, we used the model for extracting long time simulation of stride in normal and PD persons. These long time simulations were then used for calculating the chaotic features of gait. According to change of phase space behaviour and alteration of three largest lyapunov exponents, it was observed that simulated normal persons act as chaotic systems in stride production, but simulated PD does not have chaotic dynamics and is stochastic. Based on our results, it may be claimed that normal gait has chaotic nature which is disturbed in PD state. Surely, long time real recordings from gait signal in normal persons and PD patients are necessary to warranty this hypothesis.
    Journal of Theoretical Biology 05/2012; 307:160-7. · 2.35 Impact Factor
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    ABSTRACT: Freezing of gait (FOG) is a disabling symptom of Parkinson's disease (PD). In this study, we used the model of PD gait behavior for comparing normal and PD persons in order to simulate FOG and find its pathophysiology and probable treatments. We observed in the adapted model that the dopaminergic weights were reduced and the amount of dopaminergic bias was increased. These findings show that the aggravation of the disease and severe resistance of neurons to dopamine agonists may be the main cause of the FOG. Based on our model three therapeutic strategies may be proposed: decreasing the cortex signal to basal ganglia, using high dose glutamate antagonist, and using less glutamate antagonist with some amounts of gabapentin.
    Medical Hypotheses 11/2011; 78(2):258-61. · 1.18 Impact Factor
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    ABSTRACT: In this study, we present a model for the gait of normal and Parkinson's disease (PD) persons. Gait is semi-periodic and has fractal properties. Sine circle map (SCM) relation has a sinusoidal term and can show chaotic behaviour. Therefore, we used SCM as a basis for our model structure. Moreover, some similarities exist between the parameters of this relation and basal ganglia (BG) structure. This relation can explain the complex behaviours and the complex structure of BG. The presented model can simulate the BG behaviour globally. A model parameter, Ω, has a key role in the model response. We showed that when Ω is between 0.6 and 0.8, the model simulates the behaviour of normal persons; the amounts greater or less than this range correspond to PD persons. Our statistical tests show that there is a significant difference between the Ω of normal and PD patients. We conclude that Ω can be introduced as a parameter to distinguish normal and PD persons. Additionally, our results showed that Spearman correlation between the Ω and the severity of PD is 0.586. This parameter may be a good index of PD severity.
    Neuroscience Letters 11/2011; 509(2):72-5. · 2.03 Impact Factor
  • The Journal of neuropsychiatry and clinical neurosciences 01/2011; 23(3):E22. · 2.34 Impact Factor
  • The Journal of neuropsychiatry and clinical neurosciences 01/2010; 22(2):E12-3. · 2.34 Impact Factor
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    ABSTRACT: Parkinsonian patients mostly show some movement disorders. Gait disorder is one of the cardinal ones of them. In this study, we have paid attention to gait and presented a black box model for producing stride time series. We tried to present a model on the basis of a chaotic relation for normal and PD persons. Since gait is semi-periodic and has fractal properties, we used sine circle map relation. It is possible to suppose similarities between the parameters of this relation and BG structure. Therefore, this relation can explain the complex behaviours and complex structure of BG. The presented model can simulate globally the BG behaviour. Ω parameter of the model has a key role in the model response. It is the main factor which determines that the model is representing a normal person or a PD patient. Our statistical tests show that there is significant difference between the Ω of normal and PD patients. We conclude that Ω can be introduced as a parameter to distinguish normal and PD persons.
    01/2010;
  • The Journal of neuropsychiatry and clinical neurosciences 01/2010; 22(1):123.E34. · 2.34 Impact Factor
  • The Journal of neuropsychiatry and clinical neurosciences 02/2009; 21(1):101-2. · 2.34 Impact Factor
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    The Journal of neuropsychiatry and clinical neurosciences 02/2009; 21(1):98-9. · 2.34 Impact Factor
  • The Journal of neuropsychiatry and clinical neurosciences 01/2009; 21(4):470-1. · 2.34 Impact Factor
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    ABSTRACT: Huntington's disease is a movement disorder originated from malfunctioning of Basal Ganglia (BG). There are some models for this disease, most of them being conceptual. So, it seems that considering all physiological information and structural specifications to develop a holistic model is needed. We introduce a computational model based on experimental and physiological findings. Parts of the brain known to be involved in Huntington's disease are all considered in our model and most features of the movement disorders have been appeared in the model. This mathematical model has considered the involved parts of the brain in a fairly accurate way, explaining the behavior and mechanism of the disease according to the physiological information. Our model has several advantages. It is able to simulate the normal and Huntington's disease stride time intervals. It shows how the present treatment, i.e. diazepam, is able to ameliorate the gait disorder. In this research we assessed the effects of changing some neurotransmitter levels in order to propose new treatments. Although we showed that gamma amino butyric acid (GABA) blockers reduce Huntington's disease movement disorder, but we discussed that it is unfair to use this route for treatment. We evaluated our model response to increment of GABA, alone and observed that the gait disorder was strengthened. Our novel idea in this regard is resuscitation of BG loop in order to maintain its major physiological functions, and at the same time raising the threshold in order to weaken the internal disturbances. Our last idea about BG treatment is to decrease glutamate. Our model was able to show the effectiveness of this treatment on Huntington's disease disturbances. We propose that experimental studies should be designed in which these two novel methods of treatment will be evaluated. This validation would implement a milestone in treatment of such a debilitating disease at Huntington.
    Journal of Theoretical Biology 06/2008; 254(2):361-7. · 2.35 Impact Factor
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    ABSTRACT: Huntington's disease is caused by degeneration or malfunctioning of basal ganglia. Although the exact pathophysiology of this disease is not clear, it seems that abnormal glutamate release is involved in producing movement disorders. Few simulations are done on Huntington's disease. Since a complex movement disorder is seen in this disease, a mathematical model is needed to analyze it. We designed a computational model based on physiological findings. The model block diagram is proposed. The glutamate abnormality of the disease is considered as an environment noise and is designated as a random number generator in the model. To designate inhibitory and excitatory effect of neurotransmitters on each block, we used Hill functions. We designated the internal behavior of blocks using a closed loop system. Proper transfer functions are assumed for each block in our model. In order to separate normal and diseased conditions, we included noise in all glutamate related blocks and put it dependent to a parameter, g. All nominal quantities used in the model are chosen by try and error. The response of the model is presented for different values of g in health and illness states. In this study, we have designated g=1 for healthy and g=10 for illness states. In the healthy state, our model's output is zero. However, it produces an abrupt movement in Huntington's disease, like what is seen in chorea. While reducing g from 10 to 3 causes the size of answer to be reduced, putting the g below 3 will cause cessation of jerky movement. Some of our model's response properties, as the period between each two abrupt movements, size of movement and the shape of movement curve are completely stochastic, being another significant similarity between our model and the real conditions. According to all similarities between the model and Huntington's disease, any change in the model parameters can resemble real changes. We evaluated some parameters, as substance P and GABA levels, in the basal ganglia model and showed that increasing these variables are able to ameliorate the patient's symptoms. We suggest that prescribing drugs such as gabapentin could improve the symptoms. Surely, clinical trials are needed to validate this suggestion.
    Medical Hypotheses 02/2007; 68(5):1154-8. · 1.18 Impact Factor

Publication Stats

27 Citations
34.78 Total Impact Points

Institutions

  • 2013
    • University of Tabriz
      • School of Engineering Emerging Technology
      Tebriz, East Azarbaijan, Iran
  • 2007–2013
    • Sahand University of Technology
      Tebriz, East Azarbaijan, Iran
  • 2008–2011
    • Amirkabir University of Technology
      • Department of Biomedical Engineering
      Tehrān, Ostan-e Tehran, Iran
    • Shahed University
      • Department of Biomedical Engineering
      Tehrān, Ostan-e Tehran, Iran
  • 2005
    • Sharif University of Technology
      • Department of Electrical Engineering
      Tehrān, Ostan-e Tehran, Iran