نتایج جستجو برای: voxel pattern analysismvpa
تعداد نتایج: 361371 فیلتر نتایج به سال:
We propose a statistical learning model for classifying cognitive processes based on distributed patterns of neural activation in the brain, acquired via functional magnetic resonance imaging (fMRI). In the proposed learning method, local meshes are formed around each voxel. The distance between voxels in the mesh is determined by using a functional neighbourhood concept. In order to define the...
A multivariate source-based morphometry (SBM) method for processing fractional anisotropy (FA) data is presented. SBM utilizes independent component analysis (ICA) and decomposes an FA image into spatial maps and loading coefficients. The loading coefficients represent the relative degree each component contributes to a given subject's FA map. We hypothesized that SBM analysis on a large datase...
The scaled subprofile model (SSM)(1-4) is a multivariate PCA-based algorithm that identifies major sources of variation in patient and control group brain image data while rejecting lesser components (Figure 1). Applied directly to voxel-by-voxel covariance data of steady-state multimodality images, an entire group image set can be reduced to a few significant linearly independent covariance pa...
This paper reports on a micro saddle coil for local high-resolution magnetic resonance imaging (MRI) fabricated by embedding a flexible coil pattern into a polydimethyilsiloxane (PDMS) tube. We can change the sensitivity of the micro coil by deforming the shape of the coil from a saddle-shaped mode to a planar-shaped mode. The inductance, the resistance, and the Q-factor of the coil in the sadd...
Human observers can recognize real-world visual scenes with great efficiency. Cortical regions such as the parahippocampal place area (PPA) and retrosplenial complex (RSC) have been implicated in scene recognition, but the specific representations supported by these regions are largely unknown. We used functional magnetic resonance imaging adaptation (fMRIa) and multi-voxel pattern analysis (MV...
Posterior cortical atrophy (PCA) is characterized by basic visual and high order visual-spatial dysfunctions. In this study, we investigated long-distance deafferentation processes within the frontal-parietal-occipital network in ten PCA patients using a MRI-PET combined approach. Objective voxel-based [18F]FDG-PET imaging measured metabolic changes in single patients. Comprehensive investigati...
The relationships between β-amyloid (Aβ), tau and neurodegeneration within Alzheimer's Disease pathogenesis are not fully understood. To explore these associations in vivo, we evaluated 30 Aβ PET-positive patients (mean ± sd age 62.4 ± 8.3) with mild probable AD and 12 Aβ PET-negative healthy controls (HC) (mean ± sd age 77.3 ± 6.9) as comparison. All participants underwent 3 T MRI, 11C-PiB (Aβ...
Multi-voxel pattern analyses (MVPA) are often performed on unsmoothed data, which is very different from the general practice of large smoothing extents in standard voxel-based analyses. In this report, we studied the effect of smoothing on MVPA results in a motor paradigm. Subjects pressed four buttons with two different fingers of the two hands in response to auditory commands. Overall, indep...
Structural MRI and functional imaging by SPECT as well as 18F-FDG PET are widely used in the diagnosis of Alzheimer's disease (AD). Metabolic and perfusion reductions in the parietotemporal association cortex are recognized as a diagnostic pattern for AD. Outstanding progress in the diagnostic accuracy of these modalities has been achieved with statistical analysis on a voxel-by-voxel basis aft...
There are many scenarios where a 3D shape is represented by a voxel occupancy grid. Oftentimes it is desirable to convert data from this format to a triangulated mesh that represents the surface of the volume described by the occupied voxels. Algorithms such as Marching Cubes [8] or Dual Contouring [6] can be applied, or each square voxel face could be converted to two triangles directly [9]. U...
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