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Total 22 records

    Resting-State electroencephalogram (EEG) coherence over frontal regions in paranormal beliefs

    , Article Basic and Clinical Neuroscience ; Volume 13, Issue 4 , 2022 , Pages 573-584 ; 2008126X (ISSN) Narmashiri, A ; Hatami, J ; Khosrowabadi, R ; Sohrabi, A ; Sharif University of Technology
    Iran University of Medical Sciences  2022
    Abstract
    Introduction: Paranormal beliefs are defined as the belief in extrasensory perception, precognition, witchcraft, and telekinesis, magical thinking, psychokinesis, superstitions. Previous studies corroborate that executive brain functions underpin paranormal beliefs. To test this hypotheses, neurophysiological studies of brain activity are required. Methods: A sample of 20 students (10 girls, Mean±SD age: 22.50±4.07 years) were included in the current study. The absolute power of resting-state electroencephalogram (EEG) was analyzed in intra-hemispheric and inter-hemispheric coherence with eyes open. The paranormal beliefs were determined based on the total score of the revised paranormal... 

    Synchronization Analysis of EEG-Based Brain Functional Network

    , M.Sc. Thesis Sharif University of Technology Alamfard, Vahid (Author) ; Manzuri, Mohammad Taghi (Supervisor)
    Abstract
    It is believed that the synchronized activity of different brain areas, is the main cause of information binding inside the brain. Tis is definitely one of the most exciting challenges in modelling modern complex systems. Brain disorders such as schizophrenia,Alzheimer’s disease, epilepsy, autism and Parkinson’s disease are associated with abnormal synchronization abilities of neural networks. Functional connections can be assessed indirectly by measuring the electrophysiological criteria of ynchronization.Traditionally, in the study of neurophysiological, synchronizations are assessed by analyzing the coherence of frequency-domain characteristics of time series in standard methods for... 

    EEG Brain Functional Network Analysis in Cortex Level

    , M.Sc. Thesis Sharif University of Technology Pedrood, Bahman (Author) ; Jalili, Mahdi (Supervisor)
    Abstract
    Complex networks science have received tremendous attention in recent years and the brain is one of the systems to which graph theoretical tools have been applied. Alzheimer’s disease (AD) is a neurodegenerative disease affecting many of elderly population. AD changes the anatomy of the brain, which subsequently results in changes in its functions. These changes have been frequently reported in signals recorded from the brain (such as MEG, fMRI and EEG). Among these neuroimaging techniques EEG is one of the most aproprate methods for extracting functional connectivites according to high temporal resolution. In this thesis, we aimed at analyzing the properties of EEG-based functional networks... 

    Constructing EEG-Based Brain Functional Connectome Using Network-based Statistics

    , M.Sc. Thesis Sharif University of Technology Barzegaran, Elham (Author) ; Jalili, Mahdi (Supervisor)
    Abstract
    In recent years, there have been increasing attempts to study brain connectivity. Among a number of brain mapping techniques, Electroencephalography is an easy to use and cheap method that can be used in the study of brain function. One way of understanding the intricate wiring pattern and functions of brain is to consider it as a complex network. In this approach, a graph of brain functions, based on the functional relation of recorded electric signals, is constructed and then the network is evaluated with a number of network metrics that measure its different aspect of structure. Different neurological and psychological diseases can affect the connectivity power within the brain; as a... 

    Analysis of Functional Connectivity Among Brain Networks Using FMRI

    , M.Sc. Thesis Sharif University of Technology Rahmati Kargar, Behnam (Author) ; Vosughi Vahdat, Bijan (Supervisor) ; Amini, Arash (Supervisor)
    Abstract
    Development of the fMRI imaging method gives the scientists the opportunity to record functional images from the brain with high spatial resolution and several researches were conducted on this field. Autistic people’s brain has functional differences with normal people. In this paper these differences have been studied. At first fMRI datasets from autistic subjects and control have been recorded and preprocessed. Then the independent components from these datasets have been extracted using group ICA method. Any independent component is an image depicting a brain network. There is a time series for each image which shows the temporal variations of each component. In the next step, the... 

    Evaluation of Functional and Structural Networks of Healthy Macaque Monkey Brains and Comparison with Macaque Monkeys with Parkinson’s in Previous Research

    , M.Sc. Thesis Sharif University of Technology Yousef Abadi, Matin (Author) ; Rabiee, Hamid Reza (Supervisor)
    Abstract
    The brain is one of the most critical parts of the body with a lot of complexity. The treatment of brain diseases has always been in an aura of uncertainty due to its high sensitivity. In the meantime, Parkinson's disease has become the second most frequent brain disease after Alzheimer's, involving more than two percent of the population over 65 years of age. One of the biggest questions in this field is how the Parkinson's process is formed. This question has already received much attention from the pathophysiological point of view but has not been answered from the functional and structural brain network's point of view. This research compares healthy macaque monkeys' functional and... 

    EEG-based functional brain networks: Hemispheric differences in males and females

    , Article Networks and Heterogeneous Media ; Volume 10, Issue 1 , March , 2015 , Pages 223-232 ; 15561801 (ISSN) Jalili, M ; Sharif University of Technology
    American Institute of Mathematical Sciences  2015
    Abstract
    Functional connectivity in human brain can be represented as a network using electroencephalography (EEG) signals. Network representation of EEG time series can be an efficient vehicle to understand the underlying mechanisms of brain function. Brain functional networks whose nodes are brain regions and edges correspond to functional links between them are characterized by neurobiologically meaningful graph theory metrics. This study investigates the degree to which graph theory metrics are sex dependent. To this end, EEGs from 24 healthy female subjects and 21 healthy male subjects were recorded in eyes-closed resting state conditions. The connectivity matrices were extracted using... 

    Interview based connectivity analysis of EEG in order to detect deception

    , Article Medical Hypotheses ; Volume 136 , 2020 Daneshi Kohan, M ; Motie NasrAbadi, A ; sharifi, A ; Bagher Shamsollahi, M ; Sharif University of Technology
    Churchill Livingstone  2020
    Abstract
    Deception is mentioned as an expression or action which hides the truth and deception detection as a concept to uncover the truth. In this research, a connectivity analysis of Electro Encephalography study is presented regarding cognitive processes of an instructed liar/truth-teller about identity during an interview. In this survey, connectivity analysis is applied because it can provide unique information about brain activity patterns of lying and interaction among brain regions. The novelty of this paper lies in applying an open-ended questions interview protocol during EEG recording. We recruited 40 healthy participants to record EEG signal during the interview. For each subject,... 

    Constructing brain functional networks from EEG: Partial and unpartial correlations

    , Article Journal of Integrative Neuroscience ; Volume 10, Issue 2 , 2011 , Pages 213-232 ; 02196352 (ISSN) Jalili, M ; Knyazeva, M. G ; Sharif University of Technology
    Abstract
    We consider electroencephalograms (EEGs) of healthy individuals and compare the properties of the brain functional networks found through two methods: unpartialized and partialized cross-correlations. The networks obtained by partial correlations are fundamentally different from those constructed through unpartial correlations in terms of graph metrics. In particular, they have completely different connection efficiency, clustering coefficient, assortativity, degree variability, and synchronization properties. Unpartial correlations are simple to compute and they can be easily applied to large-scale systems, yet they cannot prevent the prediction of non-direct edges. In contrast, partial... 

    Analyzing Directed Functional Brain Networks Based On Electroencephalogram Data

    , M.Sc. Thesis Sharif University of Technology Afshari, Saeedeh (Author) ; Rabiei, Hamid Reza (Supervisor)
    Abstract
    Over the past few years, various studies have demonstrated that the complex networks can be used to model the structure and functions of human brain. Some of these studies indi- cated that diseases such as Alzheimer, Epilepsy, and Schizophrenia can cause changes in this network. The main idea behind the methods proposed to analyze human brain’s behav- ior, is to identify regions of the brain with specific tasks. Recent studies show that multiple regions of human brain are involved in complex activities, so it’s important to detect their interactions. Using functional high resolution multichannel neurophysiological signals, like electroencephalographic (EEG) and magnetoencephalographic... 

    Multilayer Network Approach to Brain Connectivity Analysis in Cognitive Disorder

    , M.Sc. Thesis Sharif University of Technology Talezade Lari, Emran (Author) ; Rabiee, Hamid Reza (Supervisor) ; Manzori, Mohammad Taghi (Supervisor)
    Abstract
    Brain is the most complex part of the human body. This three pound organ acting as seed of intelligence, database of memories, interpreter of the senses, and managing our movement. Network neuroscience plays an important role in revealing hidden aspects of brain functions. Recently, multilayer network models have been proposed to achieve a deeper analysis on the brain networks. Multilayer network is a framework that can represent multiple relations between nodes. In a single layer brain network, different shared information methods can be used to find connection between Regions of Interests (ROIs), but in a multilayer approach, ROIs can have multiple connections in different domains such as... 

    Hammerstein-Wiener model: A new approach to the estimation of formal neural information

    , Article Basic and Clinical Neuroscience ; Volume 3, Issue 4 , 2012 , Pages 45-51 ; 2008126X (ISSN) Abbasi Asl, R ; Khorsandi, R ; Vosooghi Vahdat, B ; Sharif University of Technology
    Abstract
    A new approach is introduced to estimate the formal information of neurons. Formal Information, mainly discusses about the aspects of the response that is related to the stimulus. Estimation is based on introducing a mathematical nonlinear model with Hammerstein-Wiener system estimator. This method of system identification consists of three blocks to completely describe the nonlinearity of input and output and linear behaviour of the model. The introduced model is trained by 166 spikes of neurons and other 166 spikes are used to test and validate the model. The simulation results show the R-Value of 92.6 % between estimated and reference information rate. This shows improvement of 1.41 % in... 

    Failure tolerance of motif structure in biological networks

    , Article PLoS ONE ; Volume 6, Issue 5 , May , 2011 ; 19326203 (ISSN) Mirzasoleiman, B ; Jalili, M ; Sharif University of Technology
    2011
    Abstract
    Complex networks serve as generic models for many biological systems that have been shown to share a number of common structural properties such as power-law degree distribution and small-worldness. Real-world networks are composed of building blocks called motifs that are indeed specific subgraphs of (usually) small number of nodes. Network motifs are important in the functionality of complex networks, and the role of some motifs such as feed-forward loop in many biological networks has been heavily studied. On the other hand, many biological networks have shown some degrees of robustness in terms of their efficiency and connectedness against failures in their components. In this paper we... 

    Resiliency of cortical neural networks against cascaded failures

    , Article NeuroReport ; Volume 26, Issue 12 , 2015 , Pages 718-722 ; 09594965 (ISSN) Jalili, M ; Sharif University of Technology
    Lippincott Williams and Wilkins  2015
    Abstract
    Network tools have been extensively applied to study the properties of brain functional and anatomical networks. In this paper, resiliency of Caenorhabditis elegans cortical networks against cascaded failures is studied. To this end, directed network formed by chemical connections and undirected network formed by electrical couplings through gap junctions are considered. Furthermore, two types of C. elegans networks are studied: the whole cortical network of the hermaphrodite type and the network of the posterior cortex in male C. elegans. The results show that resiliency of hermaphrodite and male networks is different. The male cortical network of chemical synapses shows extensively weaker... 

    Functional brain networks in parkinson's disease

    , Article 24th Iranian Conference on Biomedical Engineering and 2017 2nd International Iranian Conference on Biomedical Engineering, ICBME 2017, 30 November 2017 through 1 December 2017 ; 2018 ; 9781538636091 (ISBN) Akbari, S ; Fatemizadeh, E ; Reza Deevband, M ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2018
    Abstract
    Parkinson's disease (PD) is the second most common and progressive neurological disorder. Parkinson's signs are caused by dysfunction in PD patient's brain network. Newly, resting state functional magnetic resonance imaging has been utilized to assess the altered functional connectivity in PD patients. In this study, we investigated the properties of the brain network topology in 19 PD patients compared to 17 normal healthy group by means of graph theory. In addition, we used four different graph formation methods to explore linear and nonlinear relationships between fMRI signals. Each correlation measure created a weighted graph for each subject. Different graph characteristics have been... 

    Spatiotemporal signatures of surprise captured by magnetoencephalography

    , Article Frontiers in Systems Neuroscience ; Volume 16 , 2022 ; 16625137 (ISSN) Mousavi, Z ; Kiani, M. M ; Aghajan, H ; Sharif University of Technology
    Frontiers Media S.A  2022
    Abstract
    Surprise and social influence are linked through several neuropsychological mechanisms. By garnering attention, causing arousal, and motivating engagement, surprise provides a context for effective or durable social influence. Attention to a surprising event motivates the formation of an explanation or updating of models, while high arousal experiences due to surprise promote memory formation. They both encourage engagement with the surprising event through efforts aimed at understanding the situation. By affecting the behavior of the individual or a social group via setting an attractive engagement context, surprise plays an important role in shaping personal and social change. Surprise is... 

    Psychogenic seizures and frontal disconnection: EEG synchronisation study

    , Article Journal of Neurology, Neurosurgery and Psychiatry ; Volume 82, Issue 5 , 2011 , Pages 505-511 ; 00223050 (ISSN) Knyazeva, M. G ; Jalili, M ; Frackowiak, R. S ; Rossetti, A. O ; Sharif University of Technology
    2011
    Abstract
    Objective Psychogenic non-epileptic seizures (PNES) are paroxysmal events that, in contrast to epileptic seizures, are related to psychological causes without the presence of epileptiform EEG changes. Recent models suggest a multifactorial basis for PNES. A potentially paramount, but currently poorly understood factor is the interplay between psychiatric features and a specific vulnerability of the brain leading to a clinical picture that resembles epilepsy. Hypothesising that functional cerebral network abnormalities may predispose to the clinical phenotype, the authors undertook a characterisation of the functional connectivity in PNES patients. Methods The authors analysed the whole-head... 

    Investigating time-varying functional connectivity derived from the Jackknife Correlation method for distinguishing between emotions in fMRI data

    , Article Cognitive Neurodynamics ; Volume 14, Issue 4 , 2020 , Pages 457-471 Ghahari, S ; Farahani, N ; Fatemizadeh, E ; Motie Nasrabadi, A ; Sharif University of Technology
    Springer  2020
    Abstract
    Investigating human brain activity during expressing emotional states provides deep insight into complex cognitive functions and neurological correlations inside the brain. To be able to resemble the brain function in the best manner, a complex and natural stimulus should be applied as well, the method used for data analysis should have fewer assumptions, simplifications, and parameter adjustment. In this study, we examined a functional magnetic resonance imaging dataset obtained during an emotional audio-movie stimulus associated with human life. We used Jackknife Correlation (JC) method to derive a representation of time-varying functional connectivity. We applied different binary measures... 

    Overexpression of protein kinase Mζ in the hippocampus mitigates alzheimer's disease-related cognitive deficit in rats

    , Article Brain Research Bulletin ; Volume 166 , 2021 , Pages 64-72 ; 03619230 (ISSN) Amini, N ; Roosta Azad, R ; Motamedi, F ; Mirzapour Delavar, H ; Ghasemi, S ; Aliakbari, S ; Pourbadie, H. G ; Sharif University of Technology
    Elsevier Inc  2021
    Abstract
    Accumulation of amyloid beta (Aβ) soluble forms in the cerebral parenchyma is the mainstream concept underlying memory deficit in the early phase of Alzheimer's disease (AD). PKMζ plays a critical role in the maintenance of long-term memory. Yet, the role of this brain-specific enzyme has not been addressed in AD. We examined the impact of hippocampal PKMζ overexpression on AD-related memory impairment in rats. Oligomeric form of Aβ (oAβ) or vehicle was bilaterally microinjected into the dorsal hippocampus of male Wistar rats under stereotaxic surgery. One week later, 2 μl of lentiviral vector (108 T.U. / ml.) encoding PKMζ genome was microinjected into the dorsal hippocampus. Seven days... 

    Modeling the Parkinson's tremor and its treatments

    , Article Journal of Theoretical Biology ; Volume 236, Issue 3 , 2005 , Pages 311-322 ; 00225193 (ISSN) Haeri, M ; Sarbaz, Y ; Gharibzadeh, S ; Sharif University of Technology
    2005
    Abstract
    In this paper, we discuss modeling issues of the Parkinson's tremor. Through the work we have employed physiological structure as well as functioning of the parts in brain that are involved in the disease. To obtain more practical similarity, random behaviors of the connection paths are also considered. Medication or treatment of the disease both by drug prescription and electrical signal stimulation are modeled based on the same model introduced for the disease itself. Two new medication strategies are proposed based on the model to reduce the side effects caused by the present drug prescription. © 2005 Elsevier Ltd. All rights reserved