During communication in real-life settings, our brain often needs to integrate auditory and
visual information, and at the same time actively focus on the relevant sources of information, …

Frequency tagging has been successfully used to investigate selective stimulus processing
in electroencephalography (EEG) or magnetoencephalography (MEG) studies. Recently, …

… Based on the data from the exploratory dataset (N = 40), we selected five time windows
in the ERPs to test our hypotheses on the confirmatory dataset. For our occipital-perioccipital …

Selective brain responses to objects arise within a few hundreds of milliseconds of neural
processing, suggesting that visual object recognition is mediated by rapid feed-forward …

Feed-forward deep convolutional neural networks (DCNNs) are, under specific conditions,
matching and even surpassing human performance in object recognition in natural scenes. …

… The current study complements the results from Seijdel et al. (2021) by testing the ability of
deep residual networks to explain the different amounts of recurrent processing in neural data …

… Figure adapted with permission from Seijdel et al. (2021). … , these post hoc test results on
DCNNs need to be interpreted with caution as they are based on a small sample size (n = 5). …

A fundamental component of interacting with our environment is gathering and interpretation
of sensory information. When investigating how perceptual information influences decision-…

… of plausible candidates for position n + 1 (provided that this … a transition from word n’s part of
speech to that of word n + 1 (… from word n‘s part of speech to that of word n–1 in case word n–…

… Author links open overlay panel AR Smits a b , N. Seijdel a c , HS Scholte a c , CA
Heywood d , RW Kentridge d , EHF de Haan a b c … N. Kriegeskorte, M. Mur, DA Ruff, R. …