Amir Hossein Ghaderi

Elucidation of the neural correlates of time perception constitutes an important research topic in cognitive neuroscience. The focus to date has been on durations in the millisecond to seconds range, but here we used electroencephalography (EEG) to examine brain functional connectivity during much longer durations (i.e., 15 min). For this purpose,...

Objective. Transcranial photobiomodulation (tPBM) is a recently proposed non-invasive brain stimulation approach with various effects on the nervous system from the cells to the whole brain networks. Specially in the neural network level, tPBM can alter the topology and synchronizability of functional brain networks. However, the functional propert...

Abstract Parietal and frontal cortex are involved in saccade generation, and their output signals modify visual signals throughout cortex. Local signals associated with these interactions are well described, but their large-scale progression and network dynamics are unknown. Here, we combined source localized electroencephalography (EEG) and graph...

Deep brain stimulation (DBS) has shown therapeutic benefits for treatment resistant depression (TRD). Stimulation of the subcallosal cingulate gyrus (SCG) aims to alter dysregulation between subcortical and cortex. However, the 50% response rates for SCG-DBS indicates that selection of appropriate patients is challenging. Since stimulation influenc...

As the brain is dynamic and complex, knowledge of brain signal variability and complexity is crucial in our understanding of brain function. Recent resting-fMRI studies revealed links between BOLD signal variability or complexity with static/dynamics features of functional brain networks (FBN). However, no study has examined the relationships betwe...

Background Internet addiction disorder (IAD) is listed as a disorder requiring further studies in the diagnostic and statistical manual of mental disorders (DSM-V). Psychological studies showed significant co-morbidity of IAD with depression, alcohol abuse, and anxiety disorder. Etiology and genetic bases of IAD are unclear. Aims Present study aim...

Openness to experience is one of the big five traits of personality which recently has been the subject of several studies in neuroscience due to its importance in understanding various cognitive functions. However, the neural basis of openness to experience is still unclear. Previous studies have found largely heterogeneous results, suggesting tha...

We developed an artificial neural network method for characterising crucial physical plasma parameters (i.e. temperature, electron density, and abundance ratios of ionisation states) in a fast and precise manner that...

Various models (e.g., scalar, state-dependent network, and vector models) have been proposed to explain the global aspects of time perception, but they have not been tested against specific visual phenomena like perisaccadic time compression and novel stimulus time dilation. Here, in two separate experiments (N=31), we tested how the perceived dura...

Intra-individual transient temporal fluctuations in brain signal, as measured by fMRI blood oxygenation level dependent (BOLD) variability, is increasingly considered an important signal rather than measurement noise. Evidence from computational and cognitive neuroscience suggests that signal variability is a good proxy-measure of brain functional...

Functional brain networks alterations in bipolar disorder: evidence from EEG and Graph theoretical analysis Bipolar disorder (BD) is characterized by different functional changes in the brain. BD adversely affects human behavior, speech, and cognition. However, the neural basis of BD is still poorly understood. In this study, we apply graph theory...

Parietal and frontal cortex are involved in saccade generation, but their output signals also modify visual signals throughout cortex. These signals produce well-documented behavioral phenomena (saccades, saccadic suppression, various perisaccadic perceptual distortions) but their underlying influence on cortical network dynamics is not known. Here...

Background: Multiple sclerosis (MS) is a chronic inflammatory disease leading to demyelination and axonal loss in the central nervous system that causes focal lesions of gray and white matter. However, the functional impairments of brain networks in this disease are still unspecified and need to be clearer. Materials and Methods: In the present st...

Various models (e.g., scalar, state-dependent network, and vector models) have been proposed to explain the global aspects of time perception, but they have not been tested against specific visual phenomena like perisaccadic time compression and novel stimulus time dilation. Here, in two separate experiments (N = 31), we tested how the perceived du...

Bipolar disorders (BD) is characterized by different functional changing in the brain. It adversely affect human behaviour, speech, and cognition. Furthermore, due to this disorders, people tend to make a decisions which may lead to negative consequences. The question then arises is what does happen in the brain in BD condition? Since the brain is...

Visual preferences of colors are supposed to be different between people who suffer from major depressive disorder (MDD) and non-depressed people (Nolan et al, Perceptual and Motor Skill, 1995). However, this issue has not been investigated in relation to various dimensions of colors (hue, saturation, and value). Here, we investigated whether the p...

Various spatial and temporal distortions occur around the time of a saccade (Morrone et al. Nature Neuroscience 2005), presumably associated with disruptions in cortical networks. However, these effects have not been investigated using network science approaches like graph theory analysis (GTA). Here, we constructed functional brain networks in a p...

The brain may be considered as a synchronized dynamic network with several coherent dynamical units. However, concerns remain whether synchronizability is a stable state in the brain networks. If so, which index can best reveal the synchronizability in brain networks? To answer these questions, we tested the application of the spectral graph theory...

Various models (e.g. scalar, state-dependent network, and vector models) have been proposed to explain the global aspects of time perception, but they have not been tested against specific visual phenomena like perisaccadic time compression and novel stimulus time dilation. Here, we tested how the perceived duration of a novel stimulus is influence...

In this article, we propose current source density (CSD) as a marker for diagnosis of Attention Deficit and Hyperactivity Disorder (ADHD) children for the first time. A source localization method (sLORETA) was used to find the source of abnormality in the CSD in electrical distribution of different frequency bands in resting state EEG for the ADHD...

Subjective time is compressed during saccades, whereas it is dilated during presentation of a novel stimulus. Classical time perception models, such as the internal clock model (which suggests a pacemaker to create subjective time), cannot describe these apparent time distortions. Other models have been proposed to explain these individual effects,...

The duration of visual stimuli that occur just before and during saccades may be perceived as half of those that occur during fixation (Morrone et al., Nature neuroscience 2005). On the other hand, novel stimuli are perceived as lasting longer than repeated stimuli (Pariyadath & Eagleman, PLoS One 2012). Since these temporal distortions do not foll...

To characterize differences between different state-related brain networks, statistical graph theory approaches have been employed to identify informative, topological properties. However, dynamical properties have been studied little in this regard. Our goal here was to introduce spectral graph theory as a reliable approach to determine dynamic pr...

The neural basis of demanding mathematical problem solving is currently indeterminate and unclear. Mathematical problem solving engages higher order cognition and a complex associative activity of functional neural networks occurs during demanding problem solving. Twenty right handed subjects (mean age: 24.6 years; SD =3.97 years; 50% female) parti...

Neural network-based investigations of stuttering have begun to provide a possible integrative account for the large number of brain-based anomalies associated with stuttering. Here we used resting-state EEG to investigate functional brain networks in adults who stutter (AWS). Participants were 19 AWS and 52 age-, and gender-matched normally fluent...

Background: The thermal conductivity of fluids can be calculated by several computational methods. However, these methods are reliable only at the confined levels of density, and there is no specific computational method for calculating thermal conductivity in the wide ranges of density. Methods: In this paper, two methods, an Artificial Neural Net...

Internet addiction disorder (IAD) is listed in section III, as a disorder requiring further studies in the latest diagnostic and statistical manual of mental disorders (DSM-V). Psychological studies were showed significant co-morbidity of Internet addiction disorder (IAD) with depression, alcohol abuse and anxiety disorder. Etiology and genetic bas...

Background and Aim : Methamphetamine is a neurotoxin and potent psycho-stimulant with addictive effects. The high rate of methamphetamine abuse among young adults and women of childbearing age makes it imperative to clarify the long-term effects of Methamphetamine exposure on the offspring. Present study aimed to assess the effects of parental Meth...

Background and Aim : Methamphetamine is a strong addictive neurotoxin that stimulates the central nervous system and affects several pathways and metabolisms in different organs. Methamphetamine abuse changes behavioral characteristic which in some cases includes psychotic symptoms. Different individuals, show different psychiatric symptoms and bra...

Frontal cortex activity in the left hemisphere during depression is reduced. Transcranial direct current stimulation (tDCS) is a non-invasive neuromodulation technique that can increase frontal cortex activity. Therapy based on tDCS and positive psychology (PP) therapy was applied improving patients’ quality of life. The present study compared thre...

Introduction: Contrary to Diagnostic and Statistical Manual of Mental Disorders (DSM-5), fifth edition, some studies indicate that ADHD-inattentive presentation (ADHD-I) is a distinct diagnostic disorder and not an ADHD presentation. Methods: In this study, 12 ADHD-combined presentation (ADHD-C), 10 ADHD-I, and 13 controls were enrolled and their...

Introduction: The term sleep disorder refers to difficulty in initiating sleep, maintaining it or a relaxing sleep despite having enough time to sleep. Cognitive behavioral therapy is a non-drug multi-dimensional treatment that targets behavioral and cognitive factors of this disorder. Some studies have shown that psychiatric and neurological disor...

Objectives: The aetiology and molecular mechanisms of schizophrenia (SCZ) and paranoid personality disorder (PPD) are not yet clarified. The present study aimed to assess the role of mitochondrial complex I and cell bioenergetic pathways in the aetiology and characteristics of SCZ and PPD. Methods: mRNA levels of all genomic and mitochondrial genes...

EEG and graph theory was used for investigating of functional brain connectivity in individuals who stutter and possible relation between their time perception deficit and functional brain network impairment was investigated.

Recently artificial neural networks (ANNs) have become crucial for the analysis of several phenomena in the world. Stock market prices is a nonlinear phenomenon that several studies are accomplished in this context using ANN. Determine the input dimension of network is a basic problem in application of ANN to prediction of stock prices. On the othe...

There are some computational models for fluids viscosity calculation. However, each of these models is reliable in confined density. In this comparative study two methods are evaluated for viscosity prediction in all range of density. We determine the effectiveness of each of the models and we demonstrate the strengths and weaknesses of them. Visco...

The behavior of nonlinear systems can be analyzed by artificial neural networks. Air temperature change is one example of the nonlinear systems. In this work, a new neural network method is proposed for forecasting maximum air temperature in two cities. In this method, the regular graph concept is used to construct some partially connected neural n...

This paper introduces a new 3-step face detection algorithm using MATLAB software. This 3-step algorithm is based on skin mask, number of holes in each region and Support Vector Machine (SVM) for face detection in RGB images. Due to the use of just 10 levels images in the proposed algorithm, the SVM training step is accomplished so fast. In additio...