MIDAS utilizes localized discriminative learning to produce a statistic whose significance can be assessed by analytic approximation of permutation testing.

Jul 1, 2018 · In MIDAS, locally linear discriminative learning is applied to estimate the pattern that best discriminates between two groups, or predicts a ...

Jul 1, 2018 · The proposed method is applied to a functional study of truth-telling and deception as well as a structural study of aging. Abstract.

MIDAS utilizes localized discriminative learning to produce a statistic whose significance can be assessed by analytic approximation of permutation testing.

ABSTRACT. Statistical mapping of normative or pathological changes in the brain is of utmost importance for our understanding of its structure and function.

The statistical maps are based on regionally linear multivariate discriminative analysis. P-value maps are based on an analytic approximation of permutation ...

We present a novel statistical mapping framework for the analysis of neuroimaging studies. •. Proposed statistic involves regional activations and ...

Bibliographic details on Regionally discriminative multivariate statistical mapping.

Information mapping techniques, such as searchlight, which use pattern classifiers to exploit multivariate information and obtain more powerful statistical maps ...

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