Search results for "Tensor"
showing 10 items of 550 documents
Low-rank approximation based non-negative multi-way array decomposition on event-related potentials
2014
Non-negative tensor factorization (NTF) has been successfully applied to analyze event-related potentials (ERPs), and shown superiority in terms of capturing multi-domain features. However, the time-frequency representation of ERPs by higher-order tensors are usually large-scale, which prevents the popularity of most tensor factorization algorithms. To overcome this issue, we introduce a non-negative canonical polyadic decomposition (NCPD) based on low-rank approximation (LRA) and hierarchical alternating least square (HALS) techniques. We applied NCPD (LRAHALS and benchmark HALS) and CPD to extract multi-domain features of a visual ERP. The features and components extracted by LRAHALS NCPD…
Identification of proprioceptive thalamocortical tracts in children: comparison of fMRI, MEG, and manual seeding of probabilistic tractography
2022
Publisher Copyright: © The Author(s) 2022. Published by Oxford University Press. Studying white matter connections with tractography is a promising approach to understand the development of different brain processes, such as proprioception. An emerging method is to use functional brain imaging to select the cortical seed points for tractography, which is considered to improve the functional relevance and validity of the studied connections. However, it is unknown whether different functional seeding methods affect the spatial and microstructural properties of the given white matter connection. Here, we compared functional magnetic resonance imaging, magnetoencephalography, and manual seedin…
Exploring Oscillatory Dysconnectivity Networks in Major Depression During Resting State Using Coupled Tensor Decomposition
2022
Dysconnectivity of large-scale brain networks has been linked to major depression disorder (MDD) during resting state. Recent researches show that the temporal evolution of brain networks regulated by oscillations reveals novel mechanisms and neural characteristics of MDD. Our study applied a novel coupled tensor decomposition model to investigate the dysconnectivity networks characterized by spatio-temporal-spectral modes of covariation in MDD using resting electroencephalography. The phase lag index is used to calculate the functional connectivity within each time window at each frequency bin. Then, two adjacency tensors with the dimension of time frequency connectivity subject are constr…
Identifying Oscillatory Hyperconnectivity and Hypoconnectivity Networks in Major Depression Using Coupled Tensor Decomposition
2021
AbstractPrevious researches demonstrate that major depression disorder (MDD) is associated with widespread network dysconnectivity, and the dynamics of functional connectivity networks are important to delineate the neural mechanisms of MDD. Cortical electroencephalography (EEG) oscillations act as coordinators to connect different brain regions, and various assemblies of oscillations can form different networks to support different cognitive tasks. Studies have demonstrated that the dysconnectivity of EEG oscillatory networks is related with MDD. In this study, we investigated the oscillatory hyperconnectivity and hypoconnectivity networks in MDD under a naturalistic and continuous stimuli…
Shared and Unshared Feature Extraction in Major Depression During Music Listening Using Constrained Tensor Factorization
2021
Ongoing electroencephalography (EEG) signals are recorded as a mixture of stimulus-elicited EEG, spontaneous EEG and noises, which poses a huge challenge to current data analyzing techniques, especially when different groups of participants are expected to have common or highly correlated brain activities and some individual dynamics. In this study, we proposed a data-driven shared and unshared feature extraction framework based on nonnegative and coupled tensor factorization, which aims to conduct group-level analysis for the EEG signals from major depression disorder (MDD) patients and healthy controls (HC) when freely listening to music. Constrained tensor factorization not only preserve…
Increasing Stability of EEG Components Extraction Using Sparsity Regularized Tensor Decomposition
2018
Tensor decomposition has been widely employed for EEG signal processing in recent years. Constrained and regularized tensor decomposition often attains more meaningful and interpretable results. In this study, we applied sparse nonnegative CANDECOMP/PARAFAC tensor decomposition to ongoing EEG data under naturalistic music stimulus. Interesting temporal, spectral and spatial components highly related with music features were extracted. We explored the ongoing EEG decomposition results and properties in a wide range of sparsity levels, and proposed a paradigm to select reasonable sparsity regularization parameters. The stability of interesting components extraction from fourteen subjects’ dat…
Effects of the type of recovery training on the concentric strength of the knee extensors
1997
The aim of this study was to examine the effects of specific concentric and eccentric training on concentric muscular strength following an initial standardized period of excessive training that combined concentric and eccentric actions. For a period of 12 weeks, 37 young elite female basketball players performed standardized training, which included concentric and eccentric actions at 70% and 110% of one-repetition maximum (1-RM), respectively. They were then divided into three groups that followed 12 week programmes which included concentric (C-E/C, n = 13), eccentric (C-E/E, n = 13) or a combination of both concentric and eccentric (C-E/-E, n = 11) exercises. The standardized and specifi…
Diagnostic potential of the diffusion tensor tractography with fractional anisotropy in the diagnosis and treatment of cervical spondylotic and postt…
2016
Background: Diffusion tensor imaging (DTI) is a magnetic resonance imaging (MRI)-based methodology widely used for the evaluation of microstructural integrity of the central nervous system (CNS), particularly of brain white matter fibers and bundles. Methods: The most common parameters evaluated in a DTI study are the fractional anisotropy (FA) and mean diffusivity (MD). Combining FA and MD analyses is commonly used in the evaluation of various types of brain pathologies, such as brain tumors, where a combined analysis allows an accurate tumor characterization. Results: Recent studies have shown that FA and MD could be of value in non-oncologic spinal pathology. In this regard, it has been …
DEGENERATIVE CERVICAL MYELOPATHY: REVIEW OF SURGICAL OUTCOME PREDICTORS AND NEED FOR MULTIMODAL APPROACH
2020
Degenerative cervical myelopathy is the most common cause of spinal cord injury in the elderly population in the developed world, and it significantly affects the quality of life of patients and their caregivers. Surgery remains the only treatment option able to halt disease progression and provide neurological recovery for most patients. Although it has remained challenging to predict exactly who will experience improvement after surgery, increasingly it has been shown that clinical, imaging, and electrophysiological factors can predict, with relatively good capacity, those more likely to benefit. Clinically, the baseline neurological impairment appears to be strongly related to the outcom…
Changes in Exercise Performance and Hormonal Concentrations Over a Big Ten Soccer Season in Starters and Nonstarters
2004
As a consequence of the physiological demands experienced during a competitive soccer season, the antagonistic relationship between anabolic and catabolic processes can affect performance. Twenty-five male collegiate soccer players were studied throughout a season (11 weeks) to investigate the effects of long-term training and competition. Subjects were grouped as starters (S; n = 11) and nonstarters (NS; n = 14). Measures of physical performance, body composition, and hormonal concentrations (testosterone [T] and cortisol [C]) were assessed preseason (T1) and 5 times throughout the season (T2-T6). Starters and NS participated in 83.06% and 16.95% of total game time, respectively. Nonstarte…