Diego Fernández Slezak

This paper shows that age information is essential for Alzheimer's Disease detection using brain MRI, outperforming age-invariant methods and revealing flaws in brain-age gap as a biomarker.

The paper examines the temporal alignment between EEG responses and neural network activations, finding that early EEG components match low-level features and later components match semantic representations.

The paper decodes semantic content from EEG data during rapid serial visual presentation by distinguishing between image statistics and semantics, finding simpler models are more robust to statistical biases.