48 citations · 102 across the 5 of their papers we have counts for
5 papers
Statistical inference on representational geometries
Heiko H. Schütt, Alexander D. Kipnis, Jörn Diedrichsen +1
Neuroscience has recently made much progress, expanding the complexity of both neural-activity measurements and brain-computational models. However, we lack robust methods for conn…
Comparing representational geometries using whitened unbiased-distance-matrix similarity
Jörn Diedrichsen, Eva Berlot, Marieke Mur +3
Representational similarity analysis (RSA) tests models of brain computation by investigating how neural activity patterns reflect experimental conditions. Instead of predicting ac…
Inferring brain-computational mechanisms with models of activity measurements
Nikolaus Kriegeskorte, Jörn Diedrichsen
High-resolution functional imaging is providing increasingly rich measurements of brain activity in animals and humans. A major challenge is to leverage such data to gain insight i…
On the distribution of cross-validated Mahalanobis distances
Jörn Diedrichsen, Serge Provost, Hossein Zareamoghaddam
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 use…
Motor skill learning by increasing the movement planning horizon
Luke Bashford, Dmitry Kobak, Carsten Mehring
We investigated motor skill learning using a path tracking task, where human subjects had to track various curved paths as fast as possible, in the absence of any external perturba…