Loading...
Search for: computational-neuro-science
0.006 seconds

    Analysis of Functional Brain Connectivity Using EEG Signals for Classification of Brain States

    , M.Sc. Thesis Sharif University of Technology Ghodsi, Saeed (Author) ; Karbalai Aghajan, Hamid (Supervisor) ; Mohamadzadeh, Hoda ($item.subfieldsMap.e)
    Abstract
    Different perceptual, cognitive, and emotional situations results in a kind of information flow in the brain by means of coordinated neuronal oscillations. Analysing these oscillations, especially synchronizations of different brain regions, can illustrate the brain response to the aforementioned situations. In the literature, connectivity between brain regions is divided into the three groups of structural, effective, and functional, s.t. the first one referes to the connectivity between nearby regions, while the second and third ones focus on the synchronization of oscillations of arbitrary located regions. Although EEG is not the best choice for analyzing functional connectivity between... 

    Geometrical Structure of Neuron Morphology

    , Ph.D. Dissertation Sharif University of Technology Farhoodi, Roozbeh (Author) ; Fotouhi, Morteza (Supervisor)
    Abstract
    The tree structure of neuron morphologies has excited neuroscientists since their discovery in the 19-th century. Many theories assign computational meaning to morphologies, but it is still hard to generate realistic looking morphologies. There are a few growth models for generating neuron morphologies that correctly reproduce some features (e.g. branching angles) of morphologies, but they tend to fall short on other features. Here we present an approach that builds a generative model by extracting a set of human-chosen features from a database of neurons by using the naïve Bayes approach. Then by starting from a neuron with a soma we use statistical sampling techniques to generate... 

    Synchronization in Inhibitory Neural Networks

    , M.Sc. Thesis Sharif University of Technology Mehrani Ardebili, Mohsen (Author) ; Moghimi Araghi, Saman (Supervisor)
    Abstract
    Centuries passed and the human knew himself as the protagonist who searches around nature and discovers the phenomena. But after the birth of ``neuroscience", his wisdom and the process of reasoning were also added to the list of uncovered subjects. Since its arrival, many scientists started investigating ``reasoning", "sleep", ``memory disorders" etc. with a such framework. One of the main branches of this stream is the ``Synchronization" problem when the neurons get synced in the matter of spiking likelihood. ``Synchronization" means a lot to the community, because it is said that it is one major symptom of Epilepsy. With that said, we need to get to the root of this effect. It seems... 

    Reconstruction of Visual Experience from Brain’s Visual Cortex Data Using
    Deep Learning

    , M.Sc. Thesis Sharif University of Technology (Author) ; Karbalaee Aghajan, Hamid (Supervisor) ; Soleymani, Mahdieh (Co-Supervisor)
    Abstract
    e study of the brain’s neural activity is an active research area in computational neuroscience aiming to provide insights about the functionality of the brain as well as dysfunctions that underlie disorders. Functional Magnetic Resonance Imaging (fMRI) plays an important role in brain studies by providing non-invasive records of neural activities during a specific task with location sensitivity. Recent advances in statistics and machine learning offer powerful tools for paern recognition and processing of fMRI data. In this thesis, we decode information recorded via fMRI from the visual cortex to reconstruct images presented to subjects. Current reconstruction methods face numerous...