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primary-motor-cortex
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Decoding Hand Trajectory from Primary Motor Cortex ECoG Using Time Delay Neural Network
, Article Communications in Computer and Information Science ; Vol. 459 CCIS, issue , September , 2014 , p. 237-247 ; Vigneron, V ; Shamsollahi, M. B ; Guessoum, A ; Sharif University of Technology
Abstract
Brain-machines - also termed neural prostheses, could potentially increase substantially the quality of life for people suffering from motor disorders or even brain palsy. In this paper we investigate the non-stationary continuous decoding problem associated to the rat's hand position. To this aim, intracortical data (also named ECoG for electrocorticogram) are processed in successive stages: spike detection, spike sorting, and intention extraction from the firing rate signal. The two important questions to answer in our experiment are (i) is it realistic to link time events from the primary motor cortex with some time-delay mapping tool and are some inputs more suitable for this mapping...
Transcranial DC stimulation modifies functional connectivity of large-scale brain networks in abstinent methamphetamine users
, Article Brain and Behavior ; Volume 8, Issue 3 , 2018 ; 21623279 (ISSN) ; Ebrahimpoor, M ; Hariri, A ; Nitsche, M. A ; Hatami, J ; Fatemizadeh, E ; Oghabian, M. A ; Ekhtiari, H ; Sharif University of Technology
John Wiley and Sons Ltd
2018
Abstract
Background: Transcranial direct current stimulation (tDCS) is a noninvasive brain stimulation tool suited to alter cortical excitability and activity via the application of weak direct electrical currents. An increasing number of studies in the addiction literature suggests that tDCS modulates subjective self-reported craving through stimulation of dorsolateral prefrontal cortex (DLPFC). The major goal of this study was to explore effects of bilateral DLPFC stimulation on resting state networks (RSNs) in association with drug craving modulation. We targeted three large-scale RSNs; the default mode network (DMN), the executive control network (ECN), and the salience network (SN). Methods:...
Multiclass classification of patients during different stages of Alzheimer's disease using fMRI time-series
, Article Biomedical Physics and Engineering Express ; Volume 6, Issue 5 , 2020 ; Fatemizadeh, E ; Motie Nasrabadi, A ; Sharif University of Technology
IOP Publishing Ltd
2020
Abstract
Alzheimer's Disease (AD) begins several years before the symptoms develop. It starts with Mild Cognitive Impairment (MCI) which can be separated into Early MCI and Late MCI (EMCI and LMCI). Functional connectivity analysis and classification are done among the different stages of illness with Functional Magnetic Resonance Imaging (fMRI). In this study, in addition to the four stages including healthy, EMCI, LMCI, and AD, the patients have been tracked for a year. Indeed, the classification has been done among 7 groups to analyze the functional connectivity changes in one year in different stages. After generating the functional connectivity graphs for eliminating the weak links, three...