Sentence examples for multivariate pattern of from inspiring English sources

The central characteristic of this approach (compared to a conventional statistical parametric mapping-like approach) is its identification of a multivariate pattern of voxels and their characteristic activation levels that collectively identify the neural response to a stimulus.

The optimal hyperplane was computed based on the whole multivariate pattern of FA values across each DTI image.

Importantly, these 'parasitic' voxel-voxel associations can be detected only by examining the multivariate pattern of damage across the entire brain, and across the entire group.

A new machine learning methodology, the brain development index (BDI) [ 38], summarizes the multivariate pattern of structural brain development using a large sample of subjects ages 8 22, and can accurately delineate trajectories of brain development.

Third, the need for multivariate analysis has long been known in the neuroimaging field no serious neuroscientist would predict diagnosis from a single pixel or voxel in an image the multivariate pattern of signals is paramount.

The optimal hyperplane was computed based on the whole multivariate pattern of ReHo map across each image and could most accurately capture the relationship between each example and its respective label.

The null hypothesis is of no difference between the two multivariate patterns of scores, that is the subjects in the two laboratories do not differ in their responses to the stimuli.

PCA explores multivariate patterns of all forest patch types versus spatial processes based on correlation matrices and frames clusters and relates spatial heterogeneity among variables correlated with one another and responsive to multiple principal components (PC).

The CalCOFI data set is re-sampled here to show that a reduced sampling program one based on a few stations along a single transect (cf >50 stations along 6 transects for CalCOFI) or one based on a shorter time series can, within limits, obtain similar single-species and multivariate patterns of abundance.

Likewise, the multivariate patterns of shape variation among individuals and of fluctuating asymmetry show a close association.

Moreover, by applying machine learning or pattern-based classification methods to fMRI data (reviewed in [11] [13]), such studies have succeeded in finding a mapping between multivariate patterns of brain activity and a given object category.