Results 1 to 10 of about 834 (68)

Statistical Analysis of fMRI Time-Series: A Critical Review of the GLM Approach

Frontiers in Human Neuroscience, 2011
Functional Magnetic Resonance Imaging (fMRI) is one of the most widely used tools to study the neural underpinnings of human cognition. Standard analysis of fMRI data relies on a General Linear Model (GLM) approach to separate stimulus induced signals ...
Martin M Monti
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Enhanced design matrix for task-related fMRI data analysis

NeuroImage, 2021
In this paper, we introduce a novel methodology for the analysis of task-related fMRI data. In particular, we propose an alternative way for constructing the design matrix, based on the newly suggested Information-Assisted Dictionary Learning (IADL ...
Manuel Morante, Yannis Kopsinis, Christos Chatzichristos, Athanassios Protopapas, Sergios Theodoridis   +4 more
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On Constrained Principal Component (CPCA) with Application on Bootstrap [PDF]

The Egyptian Statistical Journal, 2018
Linear model (LM) provide the advance in regression analysis, where it was consideres an important development of the last 45 years, following general linear model (GLM), principal component analysis (PCA) and constrained principal component analysis ...
Alaa Abd Elmegaly, Salah Mohamed
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Functional transcranial Doppler: Selection of methods for statistical analysis and representation of changes in flow velocity

Health Science Reports, 2021
Introduction Transcranial Doppler (TCD) is a method used to study cerebral hemodynamics. In the majority of TCD studies, regression analysis and analysis of variance are the most frequently applied statistical methods.
Stephan T. Egger, Julio Bobes, Erich Seifritz, Stefan Vetter, Daniel Schuepbach   +4 more
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Habit-DisHabit Design with a Quadratic Equation: A Better Model of the Hemodynamic Changes in Preschoolers during the Dimension Change Card Sorting Task

Children, 2023
General linear modeling (GLM) has been widely employed to estimate the hemodynamic changes observed by functional near infrared spectroscopy (fNIRS) technology, which are found to be nonlinear rather than linear, however.
Dandan Wu, Chunqi Chang, Jinfeng Yang, Jiutong Luo, Sha Xie, Hui Li   +5 more
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Novel Ensemble Approaches of Machine Learning Techniques in Modeling the Gully Erosion Susceptibility

Remote Sensing, 2020
Gully erosion has become one of the major environmental issues, due to the severity of its impact in many parts of the world. Gully erosion directly and indirectly affects agriculture and infrastructural development.
Alireza Arabameri, Omid Asadi Nalivan, Sunil Saha, Jagabandhu Roy, Biswajeet Pradhan, John P. Tiefenbacher, Phuong Thao Thi Ngo   +6 more
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Modelling Impulse Response Function of Functional Infrared Imaging for General Linear Model Analysis of Autonomic Activity

Sensors, 2019
Functional infrared imaging (fIRI) is a validated procedure to infer autonomic arousal. Currently, fIRI signals are analysed through descriptive metrics, such as average temperature changes in a region of interest (ROI).
David Perpetuini, Daniela Cardone, Chiara Filippini, Antonio Maria Chiarelli, Arcangelo Merla   +4 more
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Inter-subject correlation in fMRI: method validation against stimulus-model based analysis. [PDF]

PLoS ONE, 2012
Within functional magnetic resonance imaging (fMRI), the use of the traditional general linear model (GLM) based analysis methods is often restricted to strictly controlled research setups requiring a parametric activation model.
Juha Pajula, Jukka-Pekka Kauppi, Jussi Tohka, Jussi Tohka   +3 more
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Spatial Bayesian GLM on the cortical surface produces reliable task activations in individuals and groups

NeuroImage, 2022
The general linear model (GLM) is a widely popular and convenient tool for estimating the functional brain response and identifying areas of significant activation during a task or stimulus.
Daniel Spencer, Yu Ryan Yue, David Bolin, Sarah Ryan, Amanda F. Mejia   +4 more
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Identification of microsatellite markers linked to grain discoloration disease in rice genotypes [PDF]

مجله بیوتکنولوژی کشاورزی, 2020
Objective Rice grain discoloration disease is emerging as a major threat in improved and late ripening varieties in the north of Iran that deteriorates grain quality and physical properties.
Somayeh Dariush, Mostafa Darvishnia, ali akbar ebadi   +2 more
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