mpdcm: A toolbox for massively parallel dynamic causal modeling
Background Dynamic causal modeling (DCM) for fMRI is an established method for
Bayesian system identification and inference on effective brain connectivity. DCM relies on a …
Bayesian system identification and inference on effective brain connectivity. DCM relies on a …
A novel fMRI group data analysis method based on data-driven reference extracting from group subjects
Group-independent component analysis (GICA) is a well-established blind source
separation technique that has been widely applied to study multi-subject functional magnetic …
separation technique that has been widely applied to study multi-subject functional magnetic …
Brain functional plasticity driven by career experience: a resting-state fMRI study of the seafarer
The functional connectome derived from BOLD resting-state functional magnetic resonance
imaging data represents meaningful functional organizations and a shift between distinct …
imaging data represents meaningful functional organizations and a shift between distinct …
[PDF][PDF] Performance of medical image processing algorithms implemented in CUDA running on GPU based machine
T Kalaiselvi, P Sriramakrishnan… - International Journal of …, 2018 - mecs-press.org
This paper illustrates the design and performance evaluation of few algorithms used for
analysing the medical image volumes on the massive parallel graphics processing unit …
analysing the medical image volumes on the massive parallel graphics processing unit …
FPGA-based muscle synergy extraction for surface EMG gesture classification
To the present day, a multitude of studies aims to understand how the Central Nervous
System (CNS) translates neural pulses to muscle motor tasks, through the analysis of …
System (CNS) translates neural pulses to muscle motor tasks, through the analysis of …
Development of multithread acquisition system for high quality EEG signal measurement
W Apriadi, HS Gani, P Prayitno… - Journal of Physics …, 2021 - iopscience.iop.org
This work was concerned on development of the EEG acquisition and EEG signal
processing by adding active electrodes and implementing multithread techniques. By using …
processing by adding active electrodes and implementing multithread techniques. By using …
[PDF][PDF] Performance analysis of morphological operations in CPU and GPU for accelerating digital image applications
T Kalaiselvi, P Sriramakrishnan… - International Journal of …, 2016 - academia.edu
In this paper, we evaluate the performance of morphological operations in central
processing unit (CPU) and graphics processing unit (GPU) on various sizes of image and …
processing unit (CPU) and graphics processing unit (GPU) on various sizes of image and …
A multi-variate blind source separation algorithm
M Goldhacker, P Keck, A Igel, EW Lang… - Computer methods and …, 2017 - Elsevier
Background and objective The study follows the proposal of decomposing a given data
matrix into a product of independent spatial and temporal component matrices. A multi …
matrix into a product of independent spatial and temporal component matrices. A multi …
Functional connectivity analysis of the neural bases of emotion regulation: A comparison of independent component method with density-based k-means clustering …
Functional magnetic resonance imaging (fMRI) is an important tool in neuroscience for
assessing connectivity and interactions between distant areas of the brain. To find and …
assessing connectivity and interactions between distant areas of the brain. To find and …
[PDF][PDF] 功能磁共振成像视角下的脑功能连通性分析与脑可塑性
曾卫明， 王倪传， 石玉虎， 颜虹杰 - 数据采集与处理, 2016 - researchgate.net
依据功能磁共振成像技术探究脑功能可塑性, 对解码人脑认知活动与模拟类脑智能具有十分重要
的意义, 同时也是一项极具挑战性的工作. 然而, 脑功能可塑性可通过脑功能连通的变异性来体现 …
的意义, 同时也是一项极具挑战性的工作. 然而, 脑功能可塑性可通过脑功能连通的变异性来体现 …