Alexander Walther

Diverse deep neural networks all predict human IT well, after training and fitting

The paper compares nine DNN architectures to explain human inferior temporal cortex representational geometry, finding trained models outperform untrained ones and all architectures achieve similar performance after training and fitting.

Inferring exemplar discriminability in brain representations

The paper evaluates statistical tests for detecting discriminability between brain response patterns to exemplars and recommends more powerful methods over the standard t test.

Local opposite orientation preferences in V1: fMRI sensitivity to fine-grained pattern information

This study shows that fMRI can detect fine-grained orientation preferences in V1, challenging the global-areal-map hypothesis and demonstrating that local neuronal selectivity contributes to orientation decoding.

Mind the drift - improving sensitivity to fMRI pattern information by accounting for temporal pattern drift

This paper shows that temporal pattern drift in fMRI data affects pattern similarity estimates and proposes methods to recover orientation information.