data analysis methods in fMRI
Statistical Analysis Methods for the fMRI Data
... MRI data analysis. After com- pleting the data collection using the fMRI, first step of analysis is to apply the preprocessing stages to the data to prepare them for different ...
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Temporal-spatial modeling for fMRI data
... the analysis, including trend removal and correlation structure ...original data compared with most parametric methods and is more resistant to high frequency ...event-related fMRI ...
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A Neighborhood Method for Statistical Analysis of fMRI Data
... both methods corresponding to any p-value or threshold level (T-statistics) can be obtain with the use of SPM package ...both methods by applying the lower four sequentially threshold levels as shown in ...
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SPATIO-TEMPORAL DATA ANALYSIS WITH NON-LINEAR FILTERS: BRAIN MAPPING WITH fMRI DATA
... To calculate functional maps, a segmentation of activated from non-activated areas is performed on the basis of the time course of signal intensity, applying various statistical methods. Commonly, split t-test, ...
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Analysis of Resting-State fMRI Topological Graph Theory Properties in Methamphetamine Drug Users Applying Box-Counting Fractal Dimension
... the analysis of fMRI data, in particular the resting state data is Functional Connectiv- ity ...common methods of functional connec- tivity analysis are graph theory and ...
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Diagnostic power of default mode network resting state fMRI in the detection of Alzheimer's disease
... state fMRI as a noninvasive, readily available, and radiation exposure-free biomarker of incipient AD (Greicius et ...allow fMRI to be used as a diagnostic procedure on an individual basis (Greicius et ...
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δ-MAPS: from spatio-temporal data to a weighted and lagged network between functional domains
... Another broad family of spatio-temporal dimensionality reduction methods is based on unsupervised clustering. Such algorithms can be grouped into region-growing (e.g., (Blumensath et al. 2012; Lu et al. 2003)), ...
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Artificial Neural Networks for fMRI Data Analysis: A Survey
... raw fMRI data over space and time, averaged fMRI data over a block, Beta values from a GLM analysis or average of several voxels in an ...In fMRI the number of features is ...
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Cerebral response to subject’s own name showed high prognostic value in traumatic vegetative state
... using fMRI; 13 patients were scanned twice in the same day, respecting the exact same conditions in both ...reported data from visual analysis of fMRI activation patterns were corroborated ...
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Modeling and inference of multisubject fMRI data
... neuroimaging data, including PET and functional magnetic resonance imaging ...developed methods and software for: nonparametric analysis of PET fMRI data, inference methods which ...
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Integrating fMRI and SNP data for biomarker identification for schizophrenia with a sparse representation based variable selection method
... simulation data set to demonstrate its multi-resolution ...integrative analysis of two different SCZ data sets, a Single-nucleotide polymorphism (SNP) data set and a functional resonance ...
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Resting State fMRI: A Review of Methods and Clinical Applications
... Resting-state fMRI measures spontaneous low-frequency fluctuations in the BOLD signal to investigate the functional architecture of the ...Various methods exist for analyzing resting-state data, ...
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Introduction to fMRI: experimental design and data analysis
... Although animal studies provide an unprecedented approach to study neural mechanisms at cellular level, the limited communication and cognitive capabilities restricts the investigation of brain function in animals. ...
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Accelerated estimation and inference for heritability of fMRI data
... develop methods for the analysis of genetic herit- ability suitable for brain imaging ...twin data can be accounted for by the genetic influ- ences; this can be considered for a single observable ...
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Novel data-driven analysis methods for real-time fMRI and simultaneous EEG-fMRI neuroimaging
... explore fMRI data for related activations in voxels (Lemieux et ...way fMRI data is used as a constraint to solve the inverse problem of source localization in EEG data (Phillips et ...
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Knowledge Discovery through Computational Methods on EEG and fMRI Data
... or fMRI data, it is required to parametrize the ...the data alone. The authors in [1] study fMRI which is a noninvasive method to understand the state of ones ...But fMRI lacks temporal ...
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Power Spectral Density Analysis of Time Series of Pixel of Functional Magnetic Resonance Image for Different Motor Activity
... using fMRI modality.Aim:This paper deals with the analysis of power spectrum of pixel time series for different motor ...The analysis is to relate the power magnitude of the spike in the power ...
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Statistical methods for analysis of genetic data
... When Cabanski et al. (2010) proposed SWISS, they dealt with the multiclass case in the same manner as the two class case. That is, TSS is calculated by summing the squared distance between each point and the overall ...
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Spatial Data Mining Analysis Methods
... coordinating spatial information with characteristics in the investigation procedure, and utilizing multidimensional information to break down various properties. To coordinate the spatial neighbourhood into ...
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Assessment of biofeedback rehabilitation in post-stroke patients combining fMRI and gait analysis: a case study
... of fMRI data analysis. Indeed the evaluated fMRI index after the rehabilitation protocol evidenced a decreased, more focused activation of the brain areas during the execution of the movement ...
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