On the distribution of cross-validated Mahalanobis distances
By Jörn Diedrichsen, Serge B. Provost, Hossein Zareamoghaddam Brain, Mind Institute, W. University, Department of Statistical, A. Sciences. 2016
47 citations recorded by the source corpus.
We present analytical expressions for the means and covariances of the sample distribution of the cross-validated Mahalanobis distance. This measure has proven to be especially useful in the context of representational similarity analysis (RSA) of neural activity patterns as measured by means of functional magnetic resonance imaging (fMRI). These expressions allow us to construct a normal approximation to the estimated distances, which in turn enables powerful inference on the measured statistics. Using the results, the difference between two distances can be statistically assessed, and the measured structure of the distances can be efficiently compared to predictions from computational models.
Subfields: Cognitive Neuroscience
View Paper: https://www.semanticscholar.org/paper/77d1d8e53308d74caebddfac1fbda41777f998ed
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In Cognitive Neuroscience
- Joset A. Etzel
- Jörn Diedrichsen
- Michael C. Freund
- Todd S. Braver
- Nikolaus Kriegeskorte
- Ovidiu V. Lungu
- Habib Benali
- Julien Doyon
Citations in the corpus
- Consolidation alters motor sequence-specific distributed representations (2018, methodology): “In the current study, we computed the cross-validated Mahalanobis distance (Nili et al., 2014; Walther et al., 2016; Diedrichsen et al., 2016), which is an unbiased metric that uses multivariate normalization by estimating the covariance from the GLM fitting residuals and regularizing it through Led”
- Inferring brain-computational mechanisms with models of activity measurements (2016, background): “Moreover, one of us recently derived a multinormal approximation of the distribution of crossnobis RDMs in closed form (Diedrichsen et al., 2016).”
- Neural Coding of Cognitive Control: The Representational Similarity Analysis Approach. (2020, background): “, [78]) − increased variance [125] − each condition must appear in multiple runs • examples not discussed • See: [106,126]”